diff --git "a/SenseVoiceSmall.mlmodelc/model.mil" "b/SenseVoiceSmall.mlmodelc/model.mil" new file mode 100644--- /dev/null +++ "b/SenseVoiceSmall.mlmodelc/model.mil" @@ -0,0 +1,5141 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3520.4.1"}, {"coremlc-version", "3520.5.1"}, {"coremltools-component-torch", "2.5.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.3.0"}})] +{ + func main(tensor language, tensor speech, tensor speech_lengths, tensor textnorm) [FlexibleShapeInformation = tuple, dict, tensor>>, tuple, dict, dict, tensor>>>>((("DefaultShapes", {{"speech", [1, 1800, 560]}}), ("EnumeratedShapes", {{"language_1_1_1_1_1_speech_1_1_1_1024_560_speech_lengths_1_1_1_1_1_textnorm_1_1_1_1_1_", {{"language", [1]}, {"speech", [1, 1024, 560]}, {"speech_lengths", [1]}, {"textnorm", [1]}}}, {"language_1_1_1_1_1_speech_1_1_1_128_560_speech_lengths_1_1_1_1_1_textnorm_1_1_1_1_1_", {{"language", [1]}, {"speech", [1, 128, 560]}, {"speech_lengths", [1]}, {"textnorm", [1]}}}, {"language_1_1_1_1_1_speech_1_1_1_1800_560_speech_lengths_1_1_1_1_1_textnorm_1_1_1_1_1_", {{"language", [1]}, {"speech", [1, 1800, 560]}, {"speech_lengths", [1]}, {"textnorm", [1]}}}, {"language_1_1_1_1_1_speech_1_1_1_256_560_speech_lengths_1_1_1_1_1_textnorm_1_1_1_1_1_", {{"language", [1]}, {"speech", [1, 256, 560]}, {"speech_lengths", [1]}, {"textnorm", [1]}}}, {"language_1_1_1_1_1_speech_1_1_1_512_560_speech_lengths_1_1_1_1_1_textnorm_1_1_1_1_1_", {{"language", [1]}, {"speech", [1, 512, 560]}, {"speech_lengths", [1]}, {"textnorm", [1]}}}})))] { + tensor var_16 = const()[name = tensor("op_16"), val = tensor([1, 1])]; + tensor input_1 = reshape(shape = var_16, x = language)[name = tensor("input_1")]; + tensor lang_q_axis_0 = const()[name = tensor("lang_q_axis_0"), val = tensor(0)]; + tensor lang_q_batch_dims_0 = const()[name = tensor("lang_q_batch_dims_0"), val = tensor(0)]; + tensor lang_q_validate_indices_0 = const()[name = tensor("lang_q_validate_indices_0"), val = tensor(false)]; + tensor embed_weight_to_fp16 = const()[name = tensor("embed_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor input_1_to_int16_dtype_0 = const()[name = tensor("input_1_to_int16_dtype_0"), val = tensor("int16")]; + tensor input_1_to_int16 = cast(dtype = input_1_to_int16_dtype_0, x = input_1)[name = tensor("cast_523")]; + tensor lang_q_cast_fp16_cast_uint16 = gather(axis = lang_q_axis_0, batch_dims = lang_q_batch_dims_0, indices = input_1_to_int16, validate_indices = lang_q_validate_indices_0, x = embed_weight_to_fp16)[name = tensor("lang_q_cast_fp16_cast_uint16")]; + tensor var_29 = const()[name = tensor("op_29"), val = tensor([1, 1])]; + tensor input_3 = reshape(shape = var_29, x = textnorm)[name = tensor("input_3")]; + tensor style_q_axis_0 = const()[name = tensor("style_q_axis_0"), val = tensor(0)]; + tensor style_q_batch_dims_0 = const()[name = tensor("style_q_batch_dims_0"), val = tensor(0)]; + tensor style_q_validate_indices_0 = const()[name = tensor("style_q_validate_indices_0"), val = tensor(false)]; + tensor input_3_to_uint16_dtype_0 = const()[name = tensor("input_3_to_uint16_dtype_0"), val = tensor("uint16")]; + tensor input_3_to_uint16 = cast(dtype = input_3_to_uint16_dtype_0, x = input_3)[name = tensor("cast_522")]; + tensor style_q_cast_fp16_cast_uint16 = gather(axis = style_q_axis_0, batch_dims = style_q_batch_dims_0, indices = input_3_to_uint16, validate_indices = style_q_validate_indices_0, x = embed_weight_to_fp16)[name = tensor("style_q_cast_fp16_cast_uint16")]; + tensor var_40 = const()[name = tensor("op_40"), val = tensor(1)]; + tensor xs_pad_interleave_0 = const()[name = tensor("xs_pad_interleave_0"), val = tensor(false)]; + tensor event_q_to_fp16 = const()[name = tensor("event_q_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18048)))]; + tensor speech_to_fp16_dtype_0 = const()[name = tensor("speech_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor speech_to_fp16 = cast(dtype = speech_to_fp16_dtype_0, x = speech)[name = tensor("cast_521")]; + tensor xs_pad_cast_fp16 = concat(axis = var_40, interleave = xs_pad_interleave_0, values = (lang_q_cast_fp16_cast_uint16, event_q_to_fp16, style_q_cast_fp16_cast_uint16, speech_to_fp16))[name = tensor("xs_pad_cast_fp16")]; + tensor var_43 = const()[name = tensor("op_43"), val = tensor(4)]; + tensor lengths = add(x = speech_lengths, y = var_43)[name = tensor("lengths")]; + tensor var_58 = const()[name = tensor("op_58"), val = tensor(2)]; + tensor var_61 = const()[name = tensor("op_61"), val = tensor(-1)]; + tensor var_66 = const()[name = tensor("op_66"), val = tensor(0)]; + tensor var_67 = const()[name = tensor("op_67"), val = tensor(1)]; + tensor var_210_shape_cast_fp16 = shape(x = xs_pad_cast_fp16)[name = tensor("op_210_shape_cast_fp16")]; + tensor gather_0_axis_0 = const()[name = tensor("gather_0_axis_0"), val = tensor(0)]; + tensor gather_0_batch_dims_0 = const()[name = tensor("gather_0_batch_dims_0"), val = tensor(0)]; + tensor gather_0_validate_indices_0 = const()[name = tensor("gather_0_validate_indices_0"), val = tensor(false)]; + tensor var_210_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_210_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; + tensor select_0_to_uint16 = const()[name = tensor("select_0_to_uint16"), val = tensor(1)]; + tensor var_210_shape_cast_fp16_to_uint16 = cast(dtype = var_210_shape_cast_fp16_to_uint16_dtype_0, x = var_210_shape_cast_fp16)[name = tensor("cast_520")]; + tensor gather_0_cast_uint16 = gather(axis = gather_0_axis_0, batch_dims = gather_0_batch_dims_0, indices = select_0_to_uint16, validate_indices = gather_0_validate_indices_0, x = var_210_shape_cast_fp16_to_uint16)[name = tensor("gather_0_cast_uint16")]; + tensor gather_0_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_0_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; + tensor gather_0_cast_uint16_to_int32 = cast(dtype = gather_0_cast_uint16_to_int32_dtype_0, x = gather_0_cast_uint16)[name = tensor("cast_519")]; + tensor var_211 = range_1d(end = gather_0_cast_uint16_to_int32, start = var_66, step = var_67)[name = tensor("op_211")]; + tensor matrix_axes_0 = const()[name = tensor("matrix_axes_0"), val = tensor([-1])]; + tensor matrix = expand_dims(axes = matrix_axes_0, x = lengths)[name = tensor("matrix")]; + tensor mask_1 = less(x = var_211, y = matrix)[name = tensor("mask_1")]; + tensor var_219_axes_0 = const()[name = tensor("op_219_axes_0"), val = tensor([1])]; + tensor cast_8_to_fp16_dtype_0 = const()[name = tensor("cast_8_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor mask_1_to_fp16 = cast(dtype = cast_8_to_fp16_dtype_0, x = mask_1)[name = tensor("cast_518")]; + tensor var_219_cast_fp16 = expand_dims(axes = var_219_axes_0, x = mask_1_to_fp16)[name = tensor("op_219_cast_fp16")]; + tensor var_57_to_fp16 = const()[name = tensor("op_57_to_fp16"), val = tensor(0x1.6ap+4)]; + tensor x_1_cast_fp16 = mul(x = xs_pad_cast_fp16, y = var_57_to_fp16)[name = tensor("x_1_cast_fp16")]; + tensor var_222_shape_cast_fp16 = shape(x = x_1_cast_fp16)[name = tensor("op_222_shape_cast_fp16")]; + tensor gather_1_axis_0 = const()[name = tensor("gather_1_axis_0"), val = tensor(0)]; + tensor gather_1_batch_dims_0 = const()[name = tensor("gather_1_batch_dims_0"), val = tensor(0)]; + tensor gather_1_validate_indices_0 = const()[name = tensor("gather_1_validate_indices_0"), val = tensor(false)]; + tensor var_222_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_222_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; + tensor select_1_to_uint16 = const()[name = tensor("select_1_to_uint16"), val = tensor(1)]; + tensor var_222_shape_cast_fp16_to_uint16 = cast(dtype = var_222_shape_cast_fp16_to_uint16_dtype_0, x = var_222_shape_cast_fp16)[name = tensor("cast_517")]; + tensor gather_1_cast_uint16 = gather(axis = gather_1_axis_0, batch_dims = gather_1_batch_dims_0, indices = select_1_to_uint16, validate_indices = gather_1_validate_indices_0, x = var_222_shape_cast_fp16_to_uint16)[name = tensor("gather_1_cast_uint16")]; + tensor gather_1_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_1_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; + tensor var_226 = const()[name = tensor("op_226"), val = tensor(1)]; + tensor gather_1_cast_uint16_to_int32 = cast(dtype = gather_1_cast_uint16_to_int32_dtype_0, x = gather_1_cast_uint16)[name = tensor("cast_516")]; + tensor var_227 = add(x = gather_1_cast_uint16_to_int32, y = var_226)[name = tensor("op_227")]; + tensor const_0 = const()[name = tensor("const_0"), val = tensor(1)]; + tensor var_229 = range_1d(end = var_227, start = var_67, step = const_0)[name = tensor("op_229")]; + tensor var_230_axes_0 = const()[name = tensor("op_230_axes_0"), val = tensor([0])]; + tensor var_230 = expand_dims(axes = var_230_axes_0, x = var_229)[name = tensor("op_230")]; + tensor var_252 = const()[name = tensor("op_252"), val = tensor([1, -1, 1])]; + tensor cast_10_to_fp16_dtype_0 = const()[name = tensor("cast_10_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor var_230_to_fp16 = cast(dtype = cast_10_to_fp16_dtype_0, x = var_230)[name = tensor("cast_515")]; + tensor var_253_cast_fp16 = reshape(shape = var_252, x = var_230_to_fp16)[name = tensor("op_253_cast_fp16")]; + tensor var_255_to_fp16 = const()[name = tensor("op_255_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20352)))]; + tensor scaled_time_cast_fp16 = mul(x = var_253_cast_fp16, y = var_255_to_fp16)[name = tensor("scaled_time_cast_fp16")]; + tensor var_257_cast_fp16 = sin(x = scaled_time_cast_fp16)[name = tensor("op_257_cast_fp16")]; + tensor var_258_cast_fp16 = cos(x = scaled_time_cast_fp16)[name = tensor("op_258_cast_fp16")]; + tensor encoding_interleave_0 = const()[name = tensor("encoding_interleave_0"), val = tensor(false)]; + tensor encoding_cast_fp16 = concat(axis = var_58, interleave = encoding_interleave_0, values = (var_257_cast_fp16, var_258_cast_fp16))[name = tensor("encoding_cast_fp16")]; + tensor input_7_cast_fp16 = add(x = x_1_cast_fp16, y = encoding_cast_fp16)[name = tensor("input_7_cast_fp16")]; + tensor output_1_axes_0 = const()[name = tensor("output_1_axes_0"), val = tensor([-1])]; + tensor const_6_to_fp16 = const()[name = tensor("const_6_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20992)))]; + tensor const_7_to_fp16 = const()[name = tensor("const_7_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22208)))]; + tensor var_46_to_fp16 = const()[name = tensor("op_46_to_fp16"), val = tensor(0x1.5p-17)]; + tensor output_1_cast_fp16 = layer_norm(axes = output_1_axes_0, beta = const_7_to_fp16, epsilon = var_46_to_fp16, gamma = const_6_to_fp16, x = input_7_cast_fp16)[name = tensor("output_1_cast_fp16")]; + tensor encoder_encoders0_0_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders0_0_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23424)))]; + tensor encoder_encoders0_0_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders0_0_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1743808)))]; + tensor linear_0_cast_fp16 = linear(bias = encoder_encoders0_0_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders0_0_self_attn_linear_q_k_v_weight_to_fp16, x = output_1_cast_fp16)[name = tensor("linear_0_cast_fp16")]; + tensor tile_0 = const()[name = tensor("tile_0"), val = tensor([512, 512, 512])]; + tensor var_284_axis_0 = const()[name = tensor("op_284_axis_0"), val = tensor(-1)]; + tensor var_284_cast_fp16_0, tensor var_284_cast_fp16_1, tensor var_284_cast_fp16_2 = split(axis = var_284_axis_0, split_sizes = tile_0, x = linear_0_cast_fp16)[name = tensor("op_284_cast_fp16")]; + tensor concat_0x = const()[name = tensor("concat_0x"), val = tensor([1, -1, 4, 128])]; + tensor var_289_cast_fp16 = reshape(shape = concat_0x, x = var_284_cast_fp16_0)[name = tensor("op_289_cast_fp16")]; + tensor concat_1x = const()[name = tensor("concat_1x"), val = tensor([1, -1, 4, 128])]; + tensor var_292_cast_fp16 = reshape(shape = concat_1x, x = var_284_cast_fp16_1)[name = tensor("op_292_cast_fp16")]; + tensor concat_2x = const()[name = tensor("concat_2x"), val = tensor([1, -1, 4, 128])]; + tensor var_295_cast_fp16 = reshape(shape = concat_2x, x = var_284_cast_fp16_2)[name = tensor("op_295_cast_fp16")]; + tensor value_1_perm_0 = const()[name = tensor("value_1_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_298 = const()[name = tensor("op_298"), val = tensor([1, -1, 1])]; + tensor mask_7_cast_fp16 = reshape(shape = var_298, x = var_219_cast_fp16)[name = tensor("mask_7_cast_fp16")]; + tensor inputs_1_cast_fp16 = mul(x = var_284_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_1_cast_fp16")]; + tensor input_11_perm_0 = const()[name = tensor("input_11_perm_0"), val = tensor([0, 2, 1])]; + tensor input_13_pad_0 = const()[name = tensor("input_13_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_13_mode_0 = const()[name = tensor("input_13_mode_0"), val = tensor("constant")]; + tensor const_9_to_fp16 = const()[name = tensor("const_9_to_fp16"), val = tensor(0x0p+0)]; + tensor input_11_cast_fp16 = transpose(perm = input_11_perm_0, x = inputs_1_cast_fp16)[name = tensor("transpose_768")]; + tensor input_13_cast_fp16 = pad(constant_val = const_9_to_fp16, mode = input_13_mode_0, pad = input_13_pad_0, x = input_11_cast_fp16)[name = tensor("input_13_cast_fp16")]; + tensor x_5_pad_type_0 = const()[name = tensor("x_5_pad_type_0"), val = tensor("valid")]; + tensor x_5_groups_0 = const()[name = tensor("x_5_groups_0"), val = tensor(512)]; + tensor x_5_strides_0 = const()[name = tensor("x_5_strides_0"), val = tensor([1])]; + tensor x_5_pad_0 = const()[name = tensor("x_5_pad_0"), val = tensor([0, 0])]; + tensor x_5_dilations_0 = const()[name = tensor("x_5_dilations_0"), val = tensor([1])]; + tensor encoder_encoders0_0_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders0_0_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1746944)))]; + tensor x_5_cast_fp16 = conv(dilations = x_5_dilations_0, groups = x_5_groups_0, pad = x_5_pad_0, pad_type = x_5_pad_type_0, strides = x_5_strides_0, weight = encoder_encoders0_0_self_attn_fsmn_block_weight_to_fp16, x = input_13_cast_fp16)[name = tensor("x_5_cast_fp16")]; + tensor x_7_perm_0 = const()[name = tensor("x_7_perm_0"), val = tensor([0, 2, 1])]; + tensor x_7_cast_fp16 = transpose(perm = x_7_perm_0, x = x_5_cast_fp16)[name = tensor("transpose_767")]; + tensor input_15_cast_fp16 = add(x = x_7_cast_fp16, y = inputs_1_cast_fp16)[name = tensor("input_15_cast_fp16")]; + tensor fsmn_memory_1_cast_fp16 = mul(x = input_15_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_1_cast_fp16")]; + tensor var_314_to_fp16 = const()[name = tensor("op_314_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_3_cast_fp16 = mul(x = var_289_cast_fp16, y = var_314_to_fp16)[name = tensor("q_h_3_cast_fp16")]; + tensor scores_1_transpose_x_0 = const()[name = tensor("scores_1_transpose_x_0"), val = tensor(false)]; + tensor scores_1_transpose_y_0 = const()[name = tensor("scores_1_transpose_y_0"), val = tensor(false)]; + tensor transpose_210_perm_0 = const()[name = tensor("transpose_210_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_211_perm_0 = const()[name = tensor("transpose_211_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_211 = transpose(perm = transpose_211_perm_0, x = var_292_cast_fp16)[name = tensor("transpose_765")]; + tensor transpose_210 = transpose(perm = transpose_210_perm_0, x = q_h_3_cast_fp16)[name = tensor("transpose_766")]; + tensor scores_1_cast_fp16 = matmul(transpose_x = scores_1_transpose_x_0, transpose_y = scores_1_transpose_y_0, x = transpose_210, y = transpose_211)[name = tensor("scores_1_cast_fp16")]; + tensor var_319_axes_0 = const()[name = tensor("op_319_axes_0"), val = tensor([1])]; + tensor var_319_cast_fp16 = expand_dims(axes = var_319_axes_0, x = var_219_cast_fp16)[name = tensor("op_319_cast_fp16")]; + tensor var_66_promoted_to_fp16 = const()[name = tensor("op_66_promoted_to_fp16"), val = tensor(0x0p+0)]; + tensor mask_9_cast_fp16 = equal(x = var_319_cast_fp16, y = var_66_promoted_to_fp16)[name = tensor("mask_9_cast_fp16")]; + tensor var_48_to_fp16 = const()[name = tensor("op_48_to_fp16"), val = tensor(-inf)]; + tensor scores_3_cast_fp16 = select(a = var_48_to_fp16, b = scores_1_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_3_cast_fp16")]; + tensor var_322_cast_fp16 = softmax(axis = var_61, x = scores_3_cast_fp16)[name = tensor("op_322_cast_fp16")]; + tensor var_53_to_fp16 = const()[name = tensor("op_53_to_fp16"), val = tensor(0x0p+0)]; + tensor input_17_cast_fp16 = select(a = var_53_to_fp16, b = var_322_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_17_cast_fp16")]; + tensor x_11_transpose_x_0 = const()[name = tensor("x_11_transpose_x_0"), val = tensor(false)]; + tensor x_11_transpose_y_0 = const()[name = tensor("x_11_transpose_y_0"), val = tensor(false)]; + tensor value_1_cast_fp16 = transpose(perm = value_1_perm_0, x = var_295_cast_fp16)[name = tensor("transpose_769")]; + tensor x_11_cast_fp16 = matmul(transpose_x = x_11_transpose_x_0, transpose_y = x_11_transpose_y_0, x = input_17_cast_fp16, y = value_1_cast_fp16)[name = tensor("x_11_cast_fp16")]; + tensor var_326_perm_0 = const()[name = tensor("op_326_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_328 = const()[name = tensor("op_328"), val = tensor([1, -1, 512])]; + tensor var_326_cast_fp16 = transpose(perm = var_326_perm_0, x = x_11_cast_fp16)[name = tensor("transpose_764")]; + tensor input_19_cast_fp16 = reshape(shape = var_328, x = var_326_cast_fp16)[name = tensor("input_19_cast_fp16")]; + tensor encoder_encoders0_0_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders0_0_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1758272)))]; + tensor encoder_encoders0_0_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders0_0_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2282624)))]; + tensor linear_1_cast_fp16 = linear(bias = encoder_encoders0_0_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders0_0_self_attn_linear_out_weight_to_fp16, x = input_19_cast_fp16)[name = tensor("linear_1_cast_fp16")]; + tensor input_21_cast_fp16 = add(x = linear_1_cast_fp16, y = fsmn_memory_1_cast_fp16)[name = tensor("input_21_cast_fp16")]; + tensor output_3_axes_0 = const()[name = tensor("output_3_axes_0"), val = tensor([-1])]; + tensor const_10_to_fp16 = const()[name = tensor("const_10_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2283712)))]; + tensor const_11_to_fp16 = const()[name = tensor("const_11_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2284800)))]; + tensor output_3_cast_fp16 = layer_norm(axes = output_3_axes_0, beta = const_11_to_fp16, epsilon = var_46_to_fp16, gamma = const_10_to_fp16, x = input_21_cast_fp16)[name = tensor("output_3_cast_fp16")]; + tensor encoder_encoders0_0_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders0_0_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2285888)))]; + tensor encoder_encoders0_0_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders0_0_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4383104)))]; + tensor linear_2_cast_fp16 = linear(bias = encoder_encoders0_0_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders0_0_feed_forward_w_1_weight_to_fp16, x = output_3_cast_fp16)[name = tensor("linear_2_cast_fp16")]; + tensor input_31_cast_fp16 = relu(x = linear_2_cast_fp16)[name = tensor("input_31_cast_fp16")]; + tensor encoder_encoders0_0_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders0_0_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4387264)))]; + tensor encoder_encoders0_0_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders0_0_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6484480)))]; + tensor linear_3_cast_fp16 = linear(bias = encoder_encoders0_0_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders0_0_feed_forward_w_2_weight_to_fp16, x = input_31_cast_fp16)[name = tensor("linear_3_cast_fp16")]; + tensor input_37_cast_fp16 = add(x = input_21_cast_fp16, y = linear_3_cast_fp16)[name = tensor("input_37_cast_fp16")]; + tensor output_5_axes_0 = const()[name = tensor("output_5_axes_0"), val = tensor([-1])]; + tensor const_12_to_fp16 = const()[name = tensor("const_12_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6485568)))]; + tensor const_13_to_fp16 = const()[name = tensor("const_13_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6486656)))]; + tensor output_5_cast_fp16 = layer_norm(axes = output_5_axes_0, beta = const_13_to_fp16, epsilon = var_46_to_fp16, gamma = const_12_to_fp16, x = input_37_cast_fp16)[name = tensor("output_5_cast_fp16")]; + tensor encoder_encoders_0_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_0_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6487744)))]; + tensor encoder_encoders_0_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_0_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8060672)))]; + tensor linear_4_cast_fp16 = linear(bias = encoder_encoders_0_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_0_self_attn_linear_q_k_v_weight_to_fp16, x = output_5_cast_fp16)[name = tensor("linear_4_cast_fp16")]; + tensor tile_1 = const()[name = tensor("tile_1"), val = tensor([512, 512, 512])]; + tensor var_385_axis_0 = const()[name = tensor("op_385_axis_0"), val = tensor(-1)]; + tensor var_385_cast_fp16_0, tensor var_385_cast_fp16_1, tensor var_385_cast_fp16_2 = split(axis = var_385_axis_0, split_sizes = tile_1, x = linear_4_cast_fp16)[name = tensor("op_385_cast_fp16")]; + tensor concat_3x = const()[name = tensor("concat_3x"), val = tensor([1, -1, 4, 128])]; + tensor var_390_cast_fp16 = reshape(shape = concat_3x, x = var_385_cast_fp16_0)[name = tensor("op_390_cast_fp16")]; + tensor concat_4x = const()[name = tensor("concat_4x"), val = tensor([1, -1, 4, 128])]; + tensor var_393_cast_fp16 = reshape(shape = concat_4x, x = var_385_cast_fp16_1)[name = tensor("op_393_cast_fp16")]; + tensor concat_5x = const()[name = tensor("concat_5x"), val = tensor([1, -1, 4, 128])]; + tensor var_396_cast_fp16 = reshape(shape = concat_5x, x = var_385_cast_fp16_2)[name = tensor("op_396_cast_fp16")]; + tensor value_3_perm_0 = const()[name = tensor("value_3_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_3_cast_fp16 = mul(x = var_385_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_3_cast_fp16")]; + tensor input_41_perm_0 = const()[name = tensor("input_41_perm_0"), val = tensor([0, 2, 1])]; + tensor input_43_pad_0 = const()[name = tensor("input_43_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_43_mode_0 = const()[name = tensor("input_43_mode_0"), val = tensor("constant")]; + tensor const_15_to_fp16 = const()[name = tensor("const_15_to_fp16"), val = tensor(0x0p+0)]; + tensor input_41_cast_fp16 = transpose(perm = input_41_perm_0, x = inputs_3_cast_fp16)[name = tensor("transpose_762")]; + tensor input_43_cast_fp16 = pad(constant_val = const_15_to_fp16, mode = input_43_mode_0, pad = input_43_pad_0, x = input_41_cast_fp16)[name = tensor("input_43_cast_fp16")]; + tensor x_15_pad_type_0 = const()[name = tensor("x_15_pad_type_0"), val = tensor("valid")]; + tensor x_15_groups_0 = const()[name = tensor("x_15_groups_0"), val = tensor(512)]; + tensor x_15_strides_0 = const()[name = tensor("x_15_strides_0"), val = tensor([1])]; + tensor x_15_pad_0 = const()[name = tensor("x_15_pad_0"), val = tensor([0, 0])]; + tensor x_15_dilations_0 = const()[name = tensor("x_15_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_0_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_0_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8063808)))]; + tensor x_15_cast_fp16 = conv(dilations = x_15_dilations_0, groups = x_15_groups_0, pad = x_15_pad_0, pad_type = x_15_pad_type_0, strides = x_15_strides_0, weight = encoder_encoders_0_self_attn_fsmn_block_weight_to_fp16, x = input_43_cast_fp16)[name = tensor("x_15_cast_fp16")]; + tensor x_17_perm_0 = const()[name = tensor("x_17_perm_0"), val = tensor([0, 2, 1])]; + tensor x_17_cast_fp16 = transpose(perm = x_17_perm_0, x = x_15_cast_fp16)[name = tensor("transpose_761")]; + tensor input_45_cast_fp16 = add(x = x_17_cast_fp16, y = inputs_3_cast_fp16)[name = tensor("input_45_cast_fp16")]; + tensor fsmn_memory_3_cast_fp16 = mul(x = input_45_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_3_cast_fp16")]; + tensor var_415_to_fp16 = const()[name = tensor("op_415_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_7_cast_fp16 = mul(x = var_390_cast_fp16, y = var_415_to_fp16)[name = tensor("q_h_7_cast_fp16")]; + tensor scores_5_transpose_x_0 = const()[name = tensor("scores_5_transpose_x_0"), val = tensor(false)]; + tensor scores_5_transpose_y_0 = const()[name = tensor("scores_5_transpose_y_0"), val = tensor(false)]; + tensor transpose_212_perm_0 = const()[name = tensor("transpose_212_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_213_perm_0 = const()[name = tensor("transpose_213_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_213 = transpose(perm = transpose_213_perm_0, x = var_393_cast_fp16)[name = tensor("transpose_759")]; + tensor transpose_212 = transpose(perm = transpose_212_perm_0, x = q_h_7_cast_fp16)[name = tensor("transpose_760")]; + tensor scores_5_cast_fp16 = matmul(transpose_x = scores_5_transpose_x_0, transpose_y = scores_5_transpose_y_0, x = transpose_212, y = transpose_213)[name = tensor("scores_5_cast_fp16")]; + tensor scores_7_cast_fp16 = select(a = var_48_to_fp16, b = scores_5_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_7_cast_fp16")]; + tensor var_423_cast_fp16 = softmax(axis = var_61, x = scores_7_cast_fp16)[name = tensor("op_423_cast_fp16")]; + tensor input_47_cast_fp16 = select(a = var_53_to_fp16, b = var_423_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_47_cast_fp16")]; + tensor x_21_transpose_x_0 = const()[name = tensor("x_21_transpose_x_0"), val = tensor(false)]; + tensor x_21_transpose_y_0 = const()[name = tensor("x_21_transpose_y_0"), val = tensor(false)]; + tensor value_3_cast_fp16 = transpose(perm = value_3_perm_0, x = var_396_cast_fp16)[name = tensor("transpose_763")]; + tensor x_21_cast_fp16 = matmul(transpose_x = x_21_transpose_x_0, transpose_y = x_21_transpose_y_0, x = input_47_cast_fp16, y = value_3_cast_fp16)[name = tensor("x_21_cast_fp16")]; + tensor var_427_perm_0 = const()[name = tensor("op_427_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_429 = const()[name = tensor("op_429"), val = tensor([1, -1, 512])]; + tensor var_427_cast_fp16 = transpose(perm = var_427_perm_0, x = x_21_cast_fp16)[name = tensor("transpose_758")]; + tensor input_49_cast_fp16 = reshape(shape = var_429, x = var_427_cast_fp16)[name = tensor("input_49_cast_fp16")]; + tensor encoder_encoders_0_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_0_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8075136)))]; + tensor encoder_encoders_0_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_0_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8599488)))]; + tensor linear_5_cast_fp16 = linear(bias = encoder_encoders_0_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_0_self_attn_linear_out_weight_to_fp16, x = input_49_cast_fp16)[name = tensor("linear_5_cast_fp16")]; + tensor input_51_cast_fp16 = add(x = linear_5_cast_fp16, y = fsmn_memory_3_cast_fp16)[name = tensor("input_51_cast_fp16")]; + tensor input_53_cast_fp16 = add(x = input_37_cast_fp16, y = input_51_cast_fp16)[name = tensor("input_53_cast_fp16")]; + tensor output_7_axes_0 = const()[name = tensor("output_7_axes_0"), val = tensor([-1])]; + tensor const_16_to_fp16 = const()[name = tensor("const_16_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8600576)))]; + tensor const_17_to_fp16 = const()[name = tensor("const_17_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8601664)))]; + tensor output_7_cast_fp16 = layer_norm(axes = output_7_axes_0, beta = const_17_to_fp16, epsilon = var_46_to_fp16, gamma = const_16_to_fp16, x = input_53_cast_fp16)[name = tensor("output_7_cast_fp16")]; + tensor encoder_encoders_0_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_0_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8602752)))]; + tensor encoder_encoders_0_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_0_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10699968)))]; + tensor linear_6_cast_fp16 = linear(bias = encoder_encoders_0_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_0_feed_forward_w_1_weight_to_fp16, x = output_7_cast_fp16)[name = tensor("linear_6_cast_fp16")]; + tensor input_61_cast_fp16 = relu(x = linear_6_cast_fp16)[name = tensor("input_61_cast_fp16")]; + tensor encoder_encoders_0_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_0_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10704128)))]; + tensor encoder_encoders_0_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_0_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12801344)))]; + tensor linear_7_cast_fp16 = linear(bias = encoder_encoders_0_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_0_feed_forward_w_2_weight_to_fp16, x = input_61_cast_fp16)[name = tensor("linear_7_cast_fp16")]; + tensor input_67_cast_fp16 = add(x = input_53_cast_fp16, y = linear_7_cast_fp16)[name = tensor("input_67_cast_fp16")]; + tensor output_9_axes_0 = const()[name = tensor("output_9_axes_0"), val = tensor([-1])]; + tensor const_18_to_fp16 = const()[name = tensor("const_18_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12802432)))]; + tensor const_19_to_fp16 = const()[name = tensor("const_19_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12803520)))]; + tensor output_9_cast_fp16 = layer_norm(axes = output_9_axes_0, beta = const_19_to_fp16, epsilon = var_46_to_fp16, gamma = const_18_to_fp16, x = input_67_cast_fp16)[name = tensor("output_9_cast_fp16")]; + tensor encoder_encoders_1_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_1_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12804608)))]; + tensor encoder_encoders_1_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_1_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14377536)))]; + tensor linear_8_cast_fp16 = linear(bias = encoder_encoders_1_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_1_self_attn_linear_q_k_v_weight_to_fp16, x = output_9_cast_fp16)[name = tensor("linear_8_cast_fp16")]; + tensor tile_2 = const()[name = tensor("tile_2"), val = tensor([512, 512, 512])]; + tensor var_487_axis_0 = const()[name = tensor("op_487_axis_0"), val = tensor(-1)]; + tensor var_487_cast_fp16_0, tensor var_487_cast_fp16_1, tensor var_487_cast_fp16_2 = split(axis = var_487_axis_0, split_sizes = tile_2, x = linear_8_cast_fp16)[name = tensor("op_487_cast_fp16")]; + tensor concat_6x = const()[name = tensor("concat_6x"), val = tensor([1, -1, 4, 128])]; + tensor var_492_cast_fp16 = reshape(shape = concat_6x, x = var_487_cast_fp16_0)[name = tensor("op_492_cast_fp16")]; + tensor concat_7x = const()[name = tensor("concat_7x"), val = tensor([1, -1, 4, 128])]; + tensor var_495_cast_fp16 = reshape(shape = concat_7x, x = var_487_cast_fp16_1)[name = tensor("op_495_cast_fp16")]; + tensor concat_8x = const()[name = tensor("concat_8x"), val = tensor([1, -1, 4, 128])]; + tensor var_498_cast_fp16 = reshape(shape = concat_8x, x = var_487_cast_fp16_2)[name = tensor("op_498_cast_fp16")]; + tensor value_5_perm_0 = const()[name = tensor("value_5_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_5_cast_fp16 = mul(x = var_487_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_5_cast_fp16")]; + tensor input_71_perm_0 = const()[name = tensor("input_71_perm_0"), val = tensor([0, 2, 1])]; + tensor input_73_pad_0 = const()[name = tensor("input_73_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_73_mode_0 = const()[name = tensor("input_73_mode_0"), val = tensor("constant")]; + tensor const_21_to_fp16 = const()[name = tensor("const_21_to_fp16"), val = tensor(0x0p+0)]; + tensor input_71_cast_fp16 = transpose(perm = input_71_perm_0, x = inputs_5_cast_fp16)[name = tensor("transpose_756")]; + tensor input_73_cast_fp16 = pad(constant_val = const_21_to_fp16, mode = input_73_mode_0, pad = input_73_pad_0, x = input_71_cast_fp16)[name = tensor("input_73_cast_fp16")]; + tensor x_25_pad_type_0 = const()[name = tensor("x_25_pad_type_0"), val = tensor("valid")]; + tensor x_25_groups_0 = const()[name = tensor("x_25_groups_0"), val = tensor(512)]; + tensor x_25_strides_0 = const()[name = tensor("x_25_strides_0"), val = tensor([1])]; + tensor x_25_pad_0 = const()[name = tensor("x_25_pad_0"), val = tensor([0, 0])]; + tensor x_25_dilations_0 = const()[name = tensor("x_25_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_1_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_1_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14380672)))]; + tensor x_25_cast_fp16 = conv(dilations = x_25_dilations_0, groups = x_25_groups_0, pad = x_25_pad_0, pad_type = x_25_pad_type_0, strides = x_25_strides_0, weight = encoder_encoders_1_self_attn_fsmn_block_weight_to_fp16, x = input_73_cast_fp16)[name = tensor("x_25_cast_fp16")]; + tensor x_27_perm_0 = const()[name = tensor("x_27_perm_0"), val = tensor([0, 2, 1])]; + tensor x_27_cast_fp16 = transpose(perm = x_27_perm_0, x = x_25_cast_fp16)[name = tensor("transpose_755")]; + tensor input_75_cast_fp16 = add(x = x_27_cast_fp16, y = inputs_5_cast_fp16)[name = tensor("input_75_cast_fp16")]; + tensor fsmn_memory_5_cast_fp16 = mul(x = input_75_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_5_cast_fp16")]; + tensor var_517_to_fp16 = const()[name = tensor("op_517_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_11_cast_fp16 = mul(x = var_492_cast_fp16, y = var_517_to_fp16)[name = tensor("q_h_11_cast_fp16")]; + tensor scores_9_transpose_x_0 = const()[name = tensor("scores_9_transpose_x_0"), val = tensor(false)]; + tensor scores_9_transpose_y_0 = const()[name = tensor("scores_9_transpose_y_0"), val = tensor(false)]; + tensor transpose_214_perm_0 = const()[name = tensor("transpose_214_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_215_perm_0 = const()[name = tensor("transpose_215_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_215 = transpose(perm = transpose_215_perm_0, x = var_495_cast_fp16)[name = tensor("transpose_753")]; + tensor transpose_214 = transpose(perm = transpose_214_perm_0, x = q_h_11_cast_fp16)[name = tensor("transpose_754")]; + tensor scores_9_cast_fp16 = matmul(transpose_x = scores_9_transpose_x_0, transpose_y = scores_9_transpose_y_0, x = transpose_214, y = transpose_215)[name = tensor("scores_9_cast_fp16")]; + tensor scores_11_cast_fp16 = select(a = var_48_to_fp16, b = scores_9_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_11_cast_fp16")]; + tensor var_525_cast_fp16 = softmax(axis = var_61, x = scores_11_cast_fp16)[name = tensor("op_525_cast_fp16")]; + tensor input_77_cast_fp16 = select(a = var_53_to_fp16, b = var_525_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_77_cast_fp16")]; + tensor x_31_transpose_x_0 = const()[name = tensor("x_31_transpose_x_0"), val = tensor(false)]; + tensor x_31_transpose_y_0 = const()[name = tensor("x_31_transpose_y_0"), val = tensor(false)]; + tensor value_5_cast_fp16 = transpose(perm = value_5_perm_0, x = var_498_cast_fp16)[name = tensor("transpose_757")]; + tensor x_31_cast_fp16 = matmul(transpose_x = x_31_transpose_x_0, transpose_y = x_31_transpose_y_0, x = input_77_cast_fp16, y = value_5_cast_fp16)[name = tensor("x_31_cast_fp16")]; + tensor var_529_perm_0 = const()[name = tensor("op_529_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_531 = const()[name = tensor("op_531"), val = tensor([1, -1, 512])]; + tensor var_529_cast_fp16 = transpose(perm = var_529_perm_0, x = x_31_cast_fp16)[name = tensor("transpose_752")]; + tensor input_79_cast_fp16 = reshape(shape = var_531, x = var_529_cast_fp16)[name = tensor("input_79_cast_fp16")]; + tensor encoder_encoders_1_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_1_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14392000)))]; + tensor encoder_encoders_1_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_1_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14916352)))]; + tensor linear_9_cast_fp16 = linear(bias = encoder_encoders_1_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_1_self_attn_linear_out_weight_to_fp16, x = input_79_cast_fp16)[name = tensor("linear_9_cast_fp16")]; + tensor input_81_cast_fp16 = add(x = linear_9_cast_fp16, y = fsmn_memory_5_cast_fp16)[name = tensor("input_81_cast_fp16")]; + tensor input_83_cast_fp16 = add(x = input_67_cast_fp16, y = input_81_cast_fp16)[name = tensor("input_83_cast_fp16")]; + tensor output_11_axes_0 = const()[name = tensor("output_11_axes_0"), val = tensor([-1])]; + tensor const_22_to_fp16 = const()[name = tensor("const_22_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14917440)))]; + tensor const_23_to_fp16 = const()[name = tensor("const_23_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14918528)))]; + tensor output_11_cast_fp16 = layer_norm(axes = output_11_axes_0, beta = const_23_to_fp16, epsilon = var_46_to_fp16, gamma = const_22_to_fp16, x = input_83_cast_fp16)[name = tensor("output_11_cast_fp16")]; + tensor encoder_encoders_1_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_1_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14919616)))]; + tensor encoder_encoders_1_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_1_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17016832)))]; + tensor linear_10_cast_fp16 = linear(bias = encoder_encoders_1_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_1_feed_forward_w_1_weight_to_fp16, x = output_11_cast_fp16)[name = tensor("linear_10_cast_fp16")]; + tensor input_91_cast_fp16 = relu(x = linear_10_cast_fp16)[name = tensor("input_91_cast_fp16")]; + tensor encoder_encoders_1_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_1_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17020992)))]; + tensor encoder_encoders_1_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_1_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19118208)))]; + tensor linear_11_cast_fp16 = linear(bias = encoder_encoders_1_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_1_feed_forward_w_2_weight_to_fp16, x = input_91_cast_fp16)[name = tensor("linear_11_cast_fp16")]; + tensor input_97_cast_fp16 = add(x = input_83_cast_fp16, y = linear_11_cast_fp16)[name = tensor("input_97_cast_fp16")]; + tensor output_13_axes_0 = const()[name = tensor("output_13_axes_0"), val = tensor([-1])]; + tensor const_24_to_fp16 = const()[name = tensor("const_24_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19119296)))]; + tensor const_25_to_fp16 = const()[name = tensor("const_25_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19120384)))]; + tensor output_13_cast_fp16 = layer_norm(axes = output_13_axes_0, beta = const_25_to_fp16, epsilon = var_46_to_fp16, gamma = const_24_to_fp16, x = input_97_cast_fp16)[name = tensor("output_13_cast_fp16")]; + tensor encoder_encoders_2_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_2_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19121472)))]; + tensor encoder_encoders_2_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_2_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20694400)))]; + tensor linear_12_cast_fp16 = linear(bias = encoder_encoders_2_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_2_self_attn_linear_q_k_v_weight_to_fp16, x = output_13_cast_fp16)[name = tensor("linear_12_cast_fp16")]; + tensor tile_3 = const()[name = tensor("tile_3"), val = tensor([512, 512, 512])]; + tensor var_589_axis_0 = const()[name = tensor("op_589_axis_0"), val = tensor(-1)]; + tensor var_589_cast_fp16_0, tensor var_589_cast_fp16_1, tensor var_589_cast_fp16_2 = split(axis = var_589_axis_0, split_sizes = tile_3, x = linear_12_cast_fp16)[name = tensor("op_589_cast_fp16")]; + tensor concat_9x = const()[name = tensor("concat_9x"), val = tensor([1, -1, 4, 128])]; + tensor var_594_cast_fp16 = reshape(shape = concat_9x, x = var_589_cast_fp16_0)[name = tensor("op_594_cast_fp16")]; + tensor concat_10x = const()[name = tensor("concat_10x"), val = tensor([1, -1, 4, 128])]; + tensor var_597_cast_fp16 = reshape(shape = concat_10x, x = var_589_cast_fp16_1)[name = tensor("op_597_cast_fp16")]; + tensor concat_11x = const()[name = tensor("concat_11x"), val = tensor([1, -1, 4, 128])]; + tensor var_600_cast_fp16 = reshape(shape = concat_11x, x = var_589_cast_fp16_2)[name = tensor("op_600_cast_fp16")]; + tensor value_7_perm_0 = const()[name = tensor("value_7_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_7_cast_fp16 = mul(x = var_589_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_7_cast_fp16")]; + tensor input_101_perm_0 = const()[name = tensor("input_101_perm_0"), val = tensor([0, 2, 1])]; + tensor input_103_pad_0 = const()[name = tensor("input_103_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_103_mode_0 = const()[name = tensor("input_103_mode_0"), val = tensor("constant")]; + tensor const_27_to_fp16 = const()[name = tensor("const_27_to_fp16"), val = tensor(0x0p+0)]; + tensor input_101_cast_fp16 = transpose(perm = input_101_perm_0, x = inputs_7_cast_fp16)[name = tensor("transpose_750")]; + tensor input_103_cast_fp16 = pad(constant_val = const_27_to_fp16, mode = input_103_mode_0, pad = input_103_pad_0, x = input_101_cast_fp16)[name = tensor("input_103_cast_fp16")]; + tensor x_35_pad_type_0 = const()[name = tensor("x_35_pad_type_0"), val = tensor("valid")]; + tensor x_35_groups_0 = const()[name = tensor("x_35_groups_0"), val = tensor(512)]; + tensor x_35_strides_0 = const()[name = tensor("x_35_strides_0"), val = tensor([1])]; + tensor x_35_pad_0 = const()[name = tensor("x_35_pad_0"), val = tensor([0, 0])]; + tensor x_35_dilations_0 = const()[name = tensor("x_35_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_2_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_2_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20697536)))]; + tensor x_35_cast_fp16 = conv(dilations = x_35_dilations_0, groups = x_35_groups_0, pad = x_35_pad_0, pad_type = x_35_pad_type_0, strides = x_35_strides_0, weight = encoder_encoders_2_self_attn_fsmn_block_weight_to_fp16, x = input_103_cast_fp16)[name = tensor("x_35_cast_fp16")]; + tensor x_37_perm_0 = const()[name = tensor("x_37_perm_0"), val = tensor([0, 2, 1])]; + tensor x_37_cast_fp16 = transpose(perm = x_37_perm_0, x = x_35_cast_fp16)[name = tensor("transpose_749")]; + tensor input_105_cast_fp16 = add(x = x_37_cast_fp16, y = inputs_7_cast_fp16)[name = tensor("input_105_cast_fp16")]; + tensor fsmn_memory_7_cast_fp16 = mul(x = input_105_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_7_cast_fp16")]; + tensor var_619_to_fp16 = const()[name = tensor("op_619_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_15_cast_fp16 = mul(x = var_594_cast_fp16, y = var_619_to_fp16)[name = tensor("q_h_15_cast_fp16")]; + tensor scores_13_transpose_x_0 = const()[name = tensor("scores_13_transpose_x_0"), val = tensor(false)]; + tensor scores_13_transpose_y_0 = const()[name = tensor("scores_13_transpose_y_0"), val = tensor(false)]; + tensor transpose_216_perm_0 = const()[name = tensor("transpose_216_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_217_perm_0 = const()[name = tensor("transpose_217_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_217 = transpose(perm = transpose_217_perm_0, x = var_597_cast_fp16)[name = tensor("transpose_747")]; + tensor transpose_216 = transpose(perm = transpose_216_perm_0, x = q_h_15_cast_fp16)[name = tensor("transpose_748")]; + tensor scores_13_cast_fp16 = matmul(transpose_x = scores_13_transpose_x_0, transpose_y = scores_13_transpose_y_0, x = transpose_216, y = transpose_217)[name = tensor("scores_13_cast_fp16")]; + tensor scores_15_cast_fp16 = select(a = var_48_to_fp16, b = scores_13_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_15_cast_fp16")]; + tensor var_627_cast_fp16 = softmax(axis = var_61, x = scores_15_cast_fp16)[name = tensor("op_627_cast_fp16")]; + tensor input_107_cast_fp16 = select(a = var_53_to_fp16, b = var_627_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_107_cast_fp16")]; + tensor x_41_transpose_x_0 = const()[name = tensor("x_41_transpose_x_0"), val = tensor(false)]; + tensor x_41_transpose_y_0 = const()[name = tensor("x_41_transpose_y_0"), val = tensor(false)]; + tensor value_7_cast_fp16 = transpose(perm = value_7_perm_0, x = var_600_cast_fp16)[name = tensor("transpose_751")]; + tensor x_41_cast_fp16 = matmul(transpose_x = x_41_transpose_x_0, transpose_y = x_41_transpose_y_0, x = input_107_cast_fp16, y = value_7_cast_fp16)[name = tensor("x_41_cast_fp16")]; + tensor var_631_perm_0 = const()[name = tensor("op_631_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_633 = const()[name = tensor("op_633"), val = tensor([1, -1, 512])]; + tensor var_631_cast_fp16 = transpose(perm = var_631_perm_0, x = x_41_cast_fp16)[name = tensor("transpose_746")]; + tensor input_109_cast_fp16 = reshape(shape = var_633, x = var_631_cast_fp16)[name = tensor("input_109_cast_fp16")]; + tensor encoder_encoders_2_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_2_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20708864)))]; + tensor encoder_encoders_2_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_2_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21233216)))]; + tensor linear_13_cast_fp16 = linear(bias = encoder_encoders_2_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_2_self_attn_linear_out_weight_to_fp16, x = input_109_cast_fp16)[name = tensor("linear_13_cast_fp16")]; + tensor input_111_cast_fp16 = add(x = linear_13_cast_fp16, y = fsmn_memory_7_cast_fp16)[name = tensor("input_111_cast_fp16")]; + tensor input_113_cast_fp16 = add(x = input_97_cast_fp16, y = input_111_cast_fp16)[name = tensor("input_113_cast_fp16")]; + tensor output_15_axes_0 = const()[name = tensor("output_15_axes_0"), val = tensor([-1])]; + tensor const_28_to_fp16 = const()[name = tensor("const_28_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21234304)))]; + tensor const_29_to_fp16 = const()[name = tensor("const_29_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21235392)))]; + tensor output_15_cast_fp16 = layer_norm(axes = output_15_axes_0, beta = const_29_to_fp16, epsilon = var_46_to_fp16, gamma = const_28_to_fp16, x = input_113_cast_fp16)[name = tensor("output_15_cast_fp16")]; + tensor encoder_encoders_2_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_2_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21236480)))]; + tensor encoder_encoders_2_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_2_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23333696)))]; + tensor linear_14_cast_fp16 = linear(bias = encoder_encoders_2_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_2_feed_forward_w_1_weight_to_fp16, x = output_15_cast_fp16)[name = tensor("linear_14_cast_fp16")]; + tensor input_121_cast_fp16 = relu(x = linear_14_cast_fp16)[name = tensor("input_121_cast_fp16")]; + tensor encoder_encoders_2_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_2_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23337856)))]; + tensor encoder_encoders_2_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_2_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25435072)))]; + tensor linear_15_cast_fp16 = linear(bias = encoder_encoders_2_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_2_feed_forward_w_2_weight_to_fp16, x = input_121_cast_fp16)[name = tensor("linear_15_cast_fp16")]; + tensor input_127_cast_fp16 = add(x = input_113_cast_fp16, y = linear_15_cast_fp16)[name = tensor("input_127_cast_fp16")]; + tensor output_17_axes_0 = const()[name = tensor("output_17_axes_0"), val = tensor([-1])]; + tensor const_30_to_fp16 = const()[name = tensor("const_30_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25436160)))]; + tensor const_31_to_fp16 = const()[name = tensor("const_31_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25437248)))]; + tensor output_17_cast_fp16 = layer_norm(axes = output_17_axes_0, beta = const_31_to_fp16, epsilon = var_46_to_fp16, gamma = const_30_to_fp16, x = input_127_cast_fp16)[name = tensor("output_17_cast_fp16")]; + tensor encoder_encoders_3_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_3_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25438336)))]; + tensor encoder_encoders_3_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_3_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27011264)))]; + tensor linear_16_cast_fp16 = linear(bias = encoder_encoders_3_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_3_self_attn_linear_q_k_v_weight_to_fp16, x = output_17_cast_fp16)[name = tensor("linear_16_cast_fp16")]; + tensor tile_4 = const()[name = tensor("tile_4"), val = tensor([512, 512, 512])]; + tensor var_691_axis_0 = const()[name = tensor("op_691_axis_0"), val = tensor(-1)]; + tensor var_691_cast_fp16_0, tensor var_691_cast_fp16_1, tensor var_691_cast_fp16_2 = split(axis = var_691_axis_0, split_sizes = tile_4, x = linear_16_cast_fp16)[name = tensor("op_691_cast_fp16")]; + tensor concat_12x = const()[name = tensor("concat_12x"), val = tensor([1, -1, 4, 128])]; + tensor var_696_cast_fp16 = reshape(shape = concat_12x, x = var_691_cast_fp16_0)[name = tensor("op_696_cast_fp16")]; + tensor concat_13x = const()[name = tensor("concat_13x"), val = tensor([1, -1, 4, 128])]; + tensor var_699_cast_fp16 = reshape(shape = concat_13x, x = var_691_cast_fp16_1)[name = tensor("op_699_cast_fp16")]; + tensor concat_14x = const()[name = tensor("concat_14x"), val = tensor([1, -1, 4, 128])]; + tensor var_702_cast_fp16 = reshape(shape = concat_14x, x = var_691_cast_fp16_2)[name = tensor("op_702_cast_fp16")]; + tensor value_9_perm_0 = const()[name = tensor("value_9_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_9_cast_fp16 = mul(x = var_691_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_9_cast_fp16")]; + tensor input_131_perm_0 = const()[name = tensor("input_131_perm_0"), val = tensor([0, 2, 1])]; + tensor input_133_pad_0 = const()[name = tensor("input_133_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_133_mode_0 = const()[name = tensor("input_133_mode_0"), val = tensor("constant")]; + tensor const_33_to_fp16 = const()[name = tensor("const_33_to_fp16"), val = tensor(0x0p+0)]; + tensor input_131_cast_fp16 = transpose(perm = input_131_perm_0, x = inputs_9_cast_fp16)[name = tensor("transpose_744")]; + tensor input_133_cast_fp16 = pad(constant_val = const_33_to_fp16, mode = input_133_mode_0, pad = input_133_pad_0, x = input_131_cast_fp16)[name = tensor("input_133_cast_fp16")]; + tensor x_45_pad_type_0 = const()[name = tensor("x_45_pad_type_0"), val = tensor("valid")]; + tensor x_45_groups_0 = const()[name = tensor("x_45_groups_0"), val = tensor(512)]; + tensor x_45_strides_0 = const()[name = tensor("x_45_strides_0"), val = tensor([1])]; + tensor x_45_pad_0 = const()[name = tensor("x_45_pad_0"), val = tensor([0, 0])]; + tensor x_45_dilations_0 = const()[name = tensor("x_45_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_3_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_3_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27014400)))]; + tensor x_45_cast_fp16 = conv(dilations = x_45_dilations_0, groups = x_45_groups_0, pad = x_45_pad_0, pad_type = x_45_pad_type_0, strides = x_45_strides_0, weight = encoder_encoders_3_self_attn_fsmn_block_weight_to_fp16, x = input_133_cast_fp16)[name = tensor("x_45_cast_fp16")]; + tensor x_47_perm_0 = const()[name = tensor("x_47_perm_0"), val = tensor([0, 2, 1])]; + tensor x_47_cast_fp16 = transpose(perm = x_47_perm_0, x = x_45_cast_fp16)[name = tensor("transpose_743")]; + tensor input_135_cast_fp16 = add(x = x_47_cast_fp16, y = inputs_9_cast_fp16)[name = tensor("input_135_cast_fp16")]; + tensor fsmn_memory_9_cast_fp16 = mul(x = input_135_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_9_cast_fp16")]; + tensor var_721_to_fp16 = const()[name = tensor("op_721_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_19_cast_fp16 = mul(x = var_696_cast_fp16, y = var_721_to_fp16)[name = tensor("q_h_19_cast_fp16")]; + tensor scores_17_transpose_x_0 = const()[name = tensor("scores_17_transpose_x_0"), val = tensor(false)]; + tensor scores_17_transpose_y_0 = const()[name = tensor("scores_17_transpose_y_0"), val = tensor(false)]; + tensor transpose_218_perm_0 = const()[name = tensor("transpose_218_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_219_perm_0 = const()[name = tensor("transpose_219_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_219 = transpose(perm = transpose_219_perm_0, x = var_699_cast_fp16)[name = tensor("transpose_741")]; + tensor transpose_218 = transpose(perm = transpose_218_perm_0, x = q_h_19_cast_fp16)[name = tensor("transpose_742")]; + tensor scores_17_cast_fp16 = matmul(transpose_x = scores_17_transpose_x_0, transpose_y = scores_17_transpose_y_0, x = transpose_218, y = transpose_219)[name = tensor("scores_17_cast_fp16")]; + tensor scores_19_cast_fp16 = select(a = var_48_to_fp16, b = scores_17_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_19_cast_fp16")]; + tensor var_729_cast_fp16 = softmax(axis = var_61, x = scores_19_cast_fp16)[name = tensor("op_729_cast_fp16")]; + tensor input_137_cast_fp16 = select(a = var_53_to_fp16, b = var_729_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_137_cast_fp16")]; + tensor x_51_transpose_x_0 = const()[name = tensor("x_51_transpose_x_0"), val = tensor(false)]; + tensor x_51_transpose_y_0 = const()[name = tensor("x_51_transpose_y_0"), val = tensor(false)]; + tensor value_9_cast_fp16 = transpose(perm = value_9_perm_0, x = var_702_cast_fp16)[name = tensor("transpose_745")]; + tensor x_51_cast_fp16 = matmul(transpose_x = x_51_transpose_x_0, transpose_y = x_51_transpose_y_0, x = input_137_cast_fp16, y = value_9_cast_fp16)[name = tensor("x_51_cast_fp16")]; + tensor var_733_perm_0 = const()[name = tensor("op_733_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_735 = const()[name = tensor("op_735"), val = tensor([1, -1, 512])]; + tensor var_733_cast_fp16 = transpose(perm = var_733_perm_0, x = x_51_cast_fp16)[name = tensor("transpose_740")]; + tensor input_139_cast_fp16 = reshape(shape = var_735, x = var_733_cast_fp16)[name = tensor("input_139_cast_fp16")]; + tensor encoder_encoders_3_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_3_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27025728)))]; + tensor encoder_encoders_3_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_3_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27550080)))]; + tensor linear_17_cast_fp16 = linear(bias = encoder_encoders_3_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_3_self_attn_linear_out_weight_to_fp16, x = input_139_cast_fp16)[name = tensor("linear_17_cast_fp16")]; + tensor input_141_cast_fp16 = add(x = linear_17_cast_fp16, y = fsmn_memory_9_cast_fp16)[name = tensor("input_141_cast_fp16")]; + tensor input_143_cast_fp16 = add(x = input_127_cast_fp16, y = input_141_cast_fp16)[name = tensor("input_143_cast_fp16")]; + tensor output_19_axes_0 = const()[name = tensor("output_19_axes_0"), val = tensor([-1])]; + tensor const_34_to_fp16 = const()[name = tensor("const_34_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27551168)))]; + tensor const_35_to_fp16 = const()[name = tensor("const_35_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27552256)))]; + tensor output_19_cast_fp16 = layer_norm(axes = output_19_axes_0, beta = const_35_to_fp16, epsilon = var_46_to_fp16, gamma = const_34_to_fp16, x = input_143_cast_fp16)[name = tensor("output_19_cast_fp16")]; + tensor encoder_encoders_3_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_3_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27553344)))]; + tensor encoder_encoders_3_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_3_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29650560)))]; + tensor linear_18_cast_fp16 = linear(bias = encoder_encoders_3_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_3_feed_forward_w_1_weight_to_fp16, x = output_19_cast_fp16)[name = tensor("linear_18_cast_fp16")]; + tensor input_151_cast_fp16 = relu(x = linear_18_cast_fp16)[name = tensor("input_151_cast_fp16")]; + tensor encoder_encoders_3_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_3_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29654720)))]; + tensor encoder_encoders_3_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_3_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31751936)))]; + tensor linear_19_cast_fp16 = linear(bias = encoder_encoders_3_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_3_feed_forward_w_2_weight_to_fp16, x = input_151_cast_fp16)[name = tensor("linear_19_cast_fp16")]; + tensor input_157_cast_fp16 = add(x = input_143_cast_fp16, y = linear_19_cast_fp16)[name = tensor("input_157_cast_fp16")]; + tensor output_21_axes_0 = const()[name = tensor("output_21_axes_0"), val = tensor([-1])]; + tensor const_36_to_fp16 = const()[name = tensor("const_36_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31753024)))]; + tensor const_37_to_fp16 = const()[name = tensor("const_37_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31754112)))]; + tensor output_21_cast_fp16 = layer_norm(axes = output_21_axes_0, beta = const_37_to_fp16, epsilon = var_46_to_fp16, gamma = const_36_to_fp16, x = input_157_cast_fp16)[name = tensor("output_21_cast_fp16")]; + tensor encoder_encoders_4_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_4_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31755200)))]; + tensor encoder_encoders_4_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_4_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33328128)))]; + tensor linear_20_cast_fp16 = linear(bias = encoder_encoders_4_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_4_self_attn_linear_q_k_v_weight_to_fp16, x = output_21_cast_fp16)[name = tensor("linear_20_cast_fp16")]; + tensor tile_5 = const()[name = tensor("tile_5"), val = tensor([512, 512, 512])]; + tensor var_793_axis_0 = const()[name = tensor("op_793_axis_0"), val = tensor(-1)]; + tensor var_793_cast_fp16_0, tensor var_793_cast_fp16_1, tensor var_793_cast_fp16_2 = split(axis = var_793_axis_0, split_sizes = tile_5, x = linear_20_cast_fp16)[name = tensor("op_793_cast_fp16")]; + tensor concat_15x = const()[name = tensor("concat_15x"), val = tensor([1, -1, 4, 128])]; + tensor var_798_cast_fp16 = reshape(shape = concat_15x, x = var_793_cast_fp16_0)[name = tensor("op_798_cast_fp16")]; + tensor concat_16x = const()[name = tensor("concat_16x"), val = tensor([1, -1, 4, 128])]; + tensor var_801_cast_fp16 = reshape(shape = concat_16x, x = var_793_cast_fp16_1)[name = tensor("op_801_cast_fp16")]; + tensor concat_17x = const()[name = tensor("concat_17x"), val = tensor([1, -1, 4, 128])]; + tensor var_804_cast_fp16 = reshape(shape = concat_17x, x = var_793_cast_fp16_2)[name = tensor("op_804_cast_fp16")]; + tensor value_11_perm_0 = const()[name = tensor("value_11_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_11_cast_fp16 = mul(x = var_793_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_11_cast_fp16")]; + tensor input_161_perm_0 = const()[name = tensor("input_161_perm_0"), val = tensor([0, 2, 1])]; + tensor input_163_pad_0 = const()[name = tensor("input_163_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_163_mode_0 = const()[name = tensor("input_163_mode_0"), val = tensor("constant")]; + tensor const_39_to_fp16 = const()[name = tensor("const_39_to_fp16"), val = tensor(0x0p+0)]; + tensor input_161_cast_fp16 = transpose(perm = input_161_perm_0, x = inputs_11_cast_fp16)[name = tensor("transpose_738")]; + tensor input_163_cast_fp16 = pad(constant_val = const_39_to_fp16, mode = input_163_mode_0, pad = input_163_pad_0, x = input_161_cast_fp16)[name = tensor("input_163_cast_fp16")]; + tensor x_55_pad_type_0 = const()[name = tensor("x_55_pad_type_0"), val = tensor("valid")]; + tensor x_55_groups_0 = const()[name = tensor("x_55_groups_0"), val = tensor(512)]; + tensor x_55_strides_0 = const()[name = tensor("x_55_strides_0"), val = tensor([1])]; + tensor x_55_pad_0 = const()[name = tensor("x_55_pad_0"), val = tensor([0, 0])]; + tensor x_55_dilations_0 = const()[name = tensor("x_55_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_4_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_4_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33331264)))]; + tensor x_55_cast_fp16 = conv(dilations = x_55_dilations_0, groups = x_55_groups_0, pad = x_55_pad_0, pad_type = x_55_pad_type_0, strides = x_55_strides_0, weight = encoder_encoders_4_self_attn_fsmn_block_weight_to_fp16, x = input_163_cast_fp16)[name = tensor("x_55_cast_fp16")]; + tensor x_57_perm_0 = const()[name = tensor("x_57_perm_0"), val = tensor([0, 2, 1])]; + tensor x_57_cast_fp16 = transpose(perm = x_57_perm_0, x = x_55_cast_fp16)[name = tensor("transpose_737")]; + tensor input_165_cast_fp16 = add(x = x_57_cast_fp16, y = inputs_11_cast_fp16)[name = tensor("input_165_cast_fp16")]; + tensor fsmn_memory_11_cast_fp16 = mul(x = input_165_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_11_cast_fp16")]; + tensor var_823_to_fp16 = const()[name = tensor("op_823_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_23_cast_fp16 = mul(x = var_798_cast_fp16, y = var_823_to_fp16)[name = tensor("q_h_23_cast_fp16")]; + tensor scores_21_transpose_x_0 = const()[name = tensor("scores_21_transpose_x_0"), val = tensor(false)]; + tensor scores_21_transpose_y_0 = const()[name = tensor("scores_21_transpose_y_0"), val = tensor(false)]; + tensor transpose_220_perm_0 = const()[name = tensor("transpose_220_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_221_perm_0 = const()[name = tensor("transpose_221_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_221 = transpose(perm = transpose_221_perm_0, x = var_801_cast_fp16)[name = tensor("transpose_735")]; + tensor transpose_220 = transpose(perm = transpose_220_perm_0, x = q_h_23_cast_fp16)[name = tensor("transpose_736")]; + tensor scores_21_cast_fp16 = matmul(transpose_x = scores_21_transpose_x_0, transpose_y = scores_21_transpose_y_0, x = transpose_220, y = transpose_221)[name = tensor("scores_21_cast_fp16")]; + tensor scores_23_cast_fp16 = select(a = var_48_to_fp16, b = scores_21_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_23_cast_fp16")]; + tensor var_831_cast_fp16 = softmax(axis = var_61, x = scores_23_cast_fp16)[name = tensor("op_831_cast_fp16")]; + tensor input_167_cast_fp16 = select(a = var_53_to_fp16, b = var_831_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_167_cast_fp16")]; + tensor x_61_transpose_x_0 = const()[name = tensor("x_61_transpose_x_0"), val = tensor(false)]; + tensor x_61_transpose_y_0 = const()[name = tensor("x_61_transpose_y_0"), val = tensor(false)]; + tensor value_11_cast_fp16 = transpose(perm = value_11_perm_0, x = var_804_cast_fp16)[name = tensor("transpose_739")]; + tensor x_61_cast_fp16 = matmul(transpose_x = x_61_transpose_x_0, transpose_y = x_61_transpose_y_0, x = input_167_cast_fp16, y = value_11_cast_fp16)[name = tensor("x_61_cast_fp16")]; + tensor var_835_perm_0 = const()[name = tensor("op_835_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_837 = const()[name = tensor("op_837"), val = tensor([1, -1, 512])]; + tensor var_835_cast_fp16 = transpose(perm = var_835_perm_0, x = x_61_cast_fp16)[name = tensor("transpose_734")]; + tensor input_169_cast_fp16 = reshape(shape = var_837, x = var_835_cast_fp16)[name = tensor("input_169_cast_fp16")]; + tensor encoder_encoders_4_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_4_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33342592)))]; + tensor encoder_encoders_4_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_4_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33866944)))]; + tensor linear_21_cast_fp16 = linear(bias = encoder_encoders_4_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_4_self_attn_linear_out_weight_to_fp16, x = input_169_cast_fp16)[name = tensor("linear_21_cast_fp16")]; + tensor input_171_cast_fp16 = add(x = linear_21_cast_fp16, y = fsmn_memory_11_cast_fp16)[name = tensor("input_171_cast_fp16")]; + tensor input_173_cast_fp16 = add(x = input_157_cast_fp16, y = input_171_cast_fp16)[name = tensor("input_173_cast_fp16")]; + tensor output_23_axes_0 = const()[name = tensor("output_23_axes_0"), val = tensor([-1])]; + tensor const_40_to_fp16 = const()[name = tensor("const_40_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33868032)))]; + tensor const_41_to_fp16 = const()[name = tensor("const_41_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33869120)))]; + tensor output_23_cast_fp16 = layer_norm(axes = output_23_axes_0, beta = const_41_to_fp16, epsilon = var_46_to_fp16, gamma = const_40_to_fp16, x = input_173_cast_fp16)[name = tensor("output_23_cast_fp16")]; + tensor encoder_encoders_4_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_4_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33870208)))]; + tensor encoder_encoders_4_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_4_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35967424)))]; + tensor linear_22_cast_fp16 = linear(bias = encoder_encoders_4_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_4_feed_forward_w_1_weight_to_fp16, x = output_23_cast_fp16)[name = tensor("linear_22_cast_fp16")]; + tensor input_181_cast_fp16 = relu(x = linear_22_cast_fp16)[name = tensor("input_181_cast_fp16")]; + tensor encoder_encoders_4_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_4_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35971584)))]; + tensor encoder_encoders_4_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_4_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38068800)))]; + tensor linear_23_cast_fp16 = linear(bias = encoder_encoders_4_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_4_feed_forward_w_2_weight_to_fp16, x = input_181_cast_fp16)[name = tensor("linear_23_cast_fp16")]; + tensor input_187_cast_fp16 = add(x = input_173_cast_fp16, y = linear_23_cast_fp16)[name = tensor("input_187_cast_fp16")]; + tensor output_25_axes_0 = const()[name = tensor("output_25_axes_0"), val = tensor([-1])]; + tensor const_42_to_fp16 = const()[name = tensor("const_42_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38069888)))]; + tensor const_43_to_fp16 = const()[name = tensor("const_43_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38070976)))]; + tensor output_25_cast_fp16 = layer_norm(axes = output_25_axes_0, beta = const_43_to_fp16, epsilon = var_46_to_fp16, gamma = const_42_to_fp16, x = input_187_cast_fp16)[name = tensor("output_25_cast_fp16")]; + tensor encoder_encoders_5_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_5_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38072064)))]; + tensor encoder_encoders_5_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_5_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39644992)))]; + tensor linear_24_cast_fp16 = linear(bias = encoder_encoders_5_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_5_self_attn_linear_q_k_v_weight_to_fp16, x = output_25_cast_fp16)[name = tensor("linear_24_cast_fp16")]; + tensor tile_6 = const()[name = tensor("tile_6"), val = tensor([512, 512, 512])]; + tensor var_895_axis_0 = const()[name = tensor("op_895_axis_0"), val = tensor(-1)]; + tensor var_895_cast_fp16_0, tensor var_895_cast_fp16_1, tensor var_895_cast_fp16_2 = split(axis = var_895_axis_0, split_sizes = tile_6, x = linear_24_cast_fp16)[name = tensor("op_895_cast_fp16")]; + tensor concat_18x = const()[name = tensor("concat_18x"), val = tensor([1, -1, 4, 128])]; + tensor var_900_cast_fp16 = reshape(shape = concat_18x, x = var_895_cast_fp16_0)[name = tensor("op_900_cast_fp16")]; + tensor concat_19x = const()[name = tensor("concat_19x"), val = tensor([1, -1, 4, 128])]; + tensor var_903_cast_fp16 = reshape(shape = concat_19x, x = var_895_cast_fp16_1)[name = tensor("op_903_cast_fp16")]; + tensor concat_20x = const()[name = tensor("concat_20x"), val = tensor([1, -1, 4, 128])]; + tensor var_906_cast_fp16 = reshape(shape = concat_20x, x = var_895_cast_fp16_2)[name = tensor("op_906_cast_fp16")]; + tensor value_13_perm_0 = const()[name = tensor("value_13_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_13_cast_fp16 = mul(x = var_895_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_13_cast_fp16")]; + tensor input_191_perm_0 = const()[name = tensor("input_191_perm_0"), val = tensor([0, 2, 1])]; + tensor input_193_pad_0 = const()[name = tensor("input_193_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_193_mode_0 = const()[name = tensor("input_193_mode_0"), val = tensor("constant")]; + tensor const_45_to_fp16 = const()[name = tensor("const_45_to_fp16"), val = tensor(0x0p+0)]; + tensor input_191_cast_fp16 = transpose(perm = input_191_perm_0, x = inputs_13_cast_fp16)[name = tensor("transpose_732")]; + tensor input_193_cast_fp16 = pad(constant_val = const_45_to_fp16, mode = input_193_mode_0, pad = input_193_pad_0, x = input_191_cast_fp16)[name = tensor("input_193_cast_fp16")]; + tensor x_65_pad_type_0 = const()[name = tensor("x_65_pad_type_0"), val = tensor("valid")]; + tensor x_65_groups_0 = const()[name = tensor("x_65_groups_0"), val = tensor(512)]; + tensor x_65_strides_0 = const()[name = tensor("x_65_strides_0"), val = tensor([1])]; + tensor x_65_pad_0 = const()[name = tensor("x_65_pad_0"), val = tensor([0, 0])]; + tensor x_65_dilations_0 = const()[name = tensor("x_65_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_5_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_5_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39648128)))]; + tensor x_65_cast_fp16 = conv(dilations = x_65_dilations_0, groups = x_65_groups_0, pad = x_65_pad_0, pad_type = x_65_pad_type_0, strides = x_65_strides_0, weight = encoder_encoders_5_self_attn_fsmn_block_weight_to_fp16, x = input_193_cast_fp16)[name = tensor("x_65_cast_fp16")]; + tensor x_67_perm_0 = const()[name = tensor("x_67_perm_0"), val = tensor([0, 2, 1])]; + tensor x_67_cast_fp16 = transpose(perm = x_67_perm_0, x = x_65_cast_fp16)[name = tensor("transpose_731")]; + tensor input_195_cast_fp16 = add(x = x_67_cast_fp16, y = inputs_13_cast_fp16)[name = tensor("input_195_cast_fp16")]; + tensor fsmn_memory_13_cast_fp16 = mul(x = input_195_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_13_cast_fp16")]; + tensor var_925_to_fp16 = const()[name = tensor("op_925_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_27_cast_fp16 = mul(x = var_900_cast_fp16, y = var_925_to_fp16)[name = tensor("q_h_27_cast_fp16")]; + tensor scores_25_transpose_x_0 = const()[name = tensor("scores_25_transpose_x_0"), val = tensor(false)]; + tensor scores_25_transpose_y_0 = const()[name = tensor("scores_25_transpose_y_0"), val = tensor(false)]; + tensor transpose_222_perm_0 = const()[name = tensor("transpose_222_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_223_perm_0 = const()[name = tensor("transpose_223_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_223 = transpose(perm = transpose_223_perm_0, x = var_903_cast_fp16)[name = tensor("transpose_729")]; + tensor transpose_222 = transpose(perm = transpose_222_perm_0, x = q_h_27_cast_fp16)[name = tensor("transpose_730")]; + tensor scores_25_cast_fp16 = matmul(transpose_x = scores_25_transpose_x_0, transpose_y = scores_25_transpose_y_0, x = transpose_222, y = transpose_223)[name = tensor("scores_25_cast_fp16")]; + tensor scores_27_cast_fp16 = select(a = var_48_to_fp16, b = scores_25_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_27_cast_fp16")]; + tensor var_933_cast_fp16 = softmax(axis = var_61, x = scores_27_cast_fp16)[name = tensor("op_933_cast_fp16")]; + tensor input_197_cast_fp16 = select(a = var_53_to_fp16, b = var_933_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_197_cast_fp16")]; + tensor x_71_transpose_x_0 = const()[name = tensor("x_71_transpose_x_0"), val = tensor(false)]; + tensor x_71_transpose_y_0 = const()[name = tensor("x_71_transpose_y_0"), val = tensor(false)]; + tensor value_13_cast_fp16 = transpose(perm = value_13_perm_0, x = var_906_cast_fp16)[name = tensor("transpose_733")]; + tensor x_71_cast_fp16 = matmul(transpose_x = x_71_transpose_x_0, transpose_y = x_71_transpose_y_0, x = input_197_cast_fp16, y = value_13_cast_fp16)[name = tensor("x_71_cast_fp16")]; + tensor var_937_perm_0 = const()[name = tensor("op_937_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_939 = const()[name = tensor("op_939"), val = tensor([1, -1, 512])]; + tensor var_937_cast_fp16 = transpose(perm = var_937_perm_0, x = x_71_cast_fp16)[name = tensor("transpose_728")]; + tensor input_199_cast_fp16 = reshape(shape = var_939, x = var_937_cast_fp16)[name = tensor("input_199_cast_fp16")]; + tensor encoder_encoders_5_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_5_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39659456)))]; + tensor encoder_encoders_5_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_5_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40183808)))]; + tensor linear_25_cast_fp16 = linear(bias = encoder_encoders_5_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_5_self_attn_linear_out_weight_to_fp16, x = input_199_cast_fp16)[name = tensor("linear_25_cast_fp16")]; + tensor input_201_cast_fp16 = add(x = linear_25_cast_fp16, y = fsmn_memory_13_cast_fp16)[name = tensor("input_201_cast_fp16")]; + tensor input_203_cast_fp16 = add(x = input_187_cast_fp16, y = input_201_cast_fp16)[name = tensor("input_203_cast_fp16")]; + tensor output_27_axes_0 = const()[name = tensor("output_27_axes_0"), val = tensor([-1])]; + tensor const_46_to_fp16 = const()[name = tensor("const_46_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40184896)))]; + tensor const_47_to_fp16 = const()[name = tensor("const_47_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40185984)))]; + tensor output_27_cast_fp16 = layer_norm(axes = output_27_axes_0, beta = const_47_to_fp16, epsilon = var_46_to_fp16, gamma = const_46_to_fp16, x = input_203_cast_fp16)[name = tensor("output_27_cast_fp16")]; + tensor encoder_encoders_5_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_5_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40187072)))]; + tensor encoder_encoders_5_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_5_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42284288)))]; + tensor linear_26_cast_fp16 = linear(bias = encoder_encoders_5_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_5_feed_forward_w_1_weight_to_fp16, x = output_27_cast_fp16)[name = tensor("linear_26_cast_fp16")]; + tensor input_211_cast_fp16 = relu(x = linear_26_cast_fp16)[name = tensor("input_211_cast_fp16")]; + tensor encoder_encoders_5_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_5_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42288448)))]; + tensor encoder_encoders_5_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_5_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44385664)))]; + tensor linear_27_cast_fp16 = linear(bias = encoder_encoders_5_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_5_feed_forward_w_2_weight_to_fp16, x = input_211_cast_fp16)[name = tensor("linear_27_cast_fp16")]; + tensor input_217_cast_fp16 = add(x = input_203_cast_fp16, y = linear_27_cast_fp16)[name = tensor("input_217_cast_fp16")]; + tensor output_29_axes_0 = const()[name = tensor("output_29_axes_0"), val = tensor([-1])]; + tensor const_48_to_fp16 = const()[name = tensor("const_48_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44386752)))]; + tensor const_49_to_fp16 = const()[name = tensor("const_49_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44387840)))]; + tensor output_29_cast_fp16 = layer_norm(axes = output_29_axes_0, beta = const_49_to_fp16, epsilon = var_46_to_fp16, gamma = const_48_to_fp16, x = input_217_cast_fp16)[name = tensor("output_29_cast_fp16")]; + tensor encoder_encoders_6_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_6_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44388928)))]; + tensor encoder_encoders_6_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_6_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45961856)))]; + tensor linear_28_cast_fp16 = linear(bias = encoder_encoders_6_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_6_self_attn_linear_q_k_v_weight_to_fp16, x = output_29_cast_fp16)[name = tensor("linear_28_cast_fp16")]; + tensor tile_7 = const()[name = tensor("tile_7"), val = tensor([512, 512, 512])]; + tensor var_997_axis_0 = const()[name = tensor("op_997_axis_0"), val = tensor(-1)]; + tensor var_997_cast_fp16_0, tensor var_997_cast_fp16_1, tensor var_997_cast_fp16_2 = split(axis = var_997_axis_0, split_sizes = tile_7, x = linear_28_cast_fp16)[name = tensor("op_997_cast_fp16")]; + tensor concat_21x = const()[name = tensor("concat_21x"), val = tensor([1, -1, 4, 128])]; + tensor var_1002_cast_fp16 = reshape(shape = concat_21x, x = var_997_cast_fp16_0)[name = tensor("op_1002_cast_fp16")]; + tensor concat_22x = const()[name = tensor("concat_22x"), val = tensor([1, -1, 4, 128])]; + tensor var_1005_cast_fp16 = reshape(shape = concat_22x, x = var_997_cast_fp16_1)[name = tensor("op_1005_cast_fp16")]; + tensor concat_23x = const()[name = tensor("concat_23x"), val = tensor([1, -1, 4, 128])]; + tensor var_1008_cast_fp16 = reshape(shape = concat_23x, x = var_997_cast_fp16_2)[name = tensor("op_1008_cast_fp16")]; + tensor value_15_perm_0 = const()[name = tensor("value_15_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_15_cast_fp16 = mul(x = var_997_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_15_cast_fp16")]; + tensor input_221_perm_0 = const()[name = tensor("input_221_perm_0"), val = tensor([0, 2, 1])]; + tensor input_223_pad_0 = const()[name = tensor("input_223_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_223_mode_0 = const()[name = tensor("input_223_mode_0"), val = tensor("constant")]; + tensor const_51_to_fp16 = const()[name = tensor("const_51_to_fp16"), val = tensor(0x0p+0)]; + tensor input_221_cast_fp16 = transpose(perm = input_221_perm_0, x = inputs_15_cast_fp16)[name = tensor("transpose_726")]; + tensor input_223_cast_fp16 = pad(constant_val = const_51_to_fp16, mode = input_223_mode_0, pad = input_223_pad_0, x = input_221_cast_fp16)[name = tensor("input_223_cast_fp16")]; + tensor x_75_pad_type_0 = const()[name = tensor("x_75_pad_type_0"), val = tensor("valid")]; + tensor x_75_groups_0 = const()[name = tensor("x_75_groups_0"), val = tensor(512)]; + tensor x_75_strides_0 = const()[name = tensor("x_75_strides_0"), val = tensor([1])]; + tensor x_75_pad_0 = const()[name = tensor("x_75_pad_0"), val = tensor([0, 0])]; + tensor x_75_dilations_0 = const()[name = tensor("x_75_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_6_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_6_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45964992)))]; + tensor x_75_cast_fp16 = conv(dilations = x_75_dilations_0, groups = x_75_groups_0, pad = x_75_pad_0, pad_type = x_75_pad_type_0, strides = x_75_strides_0, weight = encoder_encoders_6_self_attn_fsmn_block_weight_to_fp16, x = input_223_cast_fp16)[name = tensor("x_75_cast_fp16")]; + tensor x_77_perm_0 = const()[name = tensor("x_77_perm_0"), val = tensor([0, 2, 1])]; + tensor x_77_cast_fp16 = transpose(perm = x_77_perm_0, x = x_75_cast_fp16)[name = tensor("transpose_725")]; + tensor input_225_cast_fp16 = add(x = x_77_cast_fp16, y = inputs_15_cast_fp16)[name = tensor("input_225_cast_fp16")]; + tensor fsmn_memory_15_cast_fp16 = mul(x = input_225_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_15_cast_fp16")]; + tensor var_1027_to_fp16 = const()[name = tensor("op_1027_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_31_cast_fp16 = mul(x = var_1002_cast_fp16, y = var_1027_to_fp16)[name = tensor("q_h_31_cast_fp16")]; + tensor scores_29_transpose_x_0 = const()[name = tensor("scores_29_transpose_x_0"), val = tensor(false)]; + tensor scores_29_transpose_y_0 = const()[name = tensor("scores_29_transpose_y_0"), val = tensor(false)]; + tensor transpose_224_perm_0 = const()[name = tensor("transpose_224_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_225_perm_0 = const()[name = tensor("transpose_225_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_225 = transpose(perm = transpose_225_perm_0, x = var_1005_cast_fp16)[name = tensor("transpose_723")]; + tensor transpose_224 = transpose(perm = transpose_224_perm_0, x = q_h_31_cast_fp16)[name = tensor("transpose_724")]; + tensor scores_29_cast_fp16 = matmul(transpose_x = scores_29_transpose_x_0, transpose_y = scores_29_transpose_y_0, x = transpose_224, y = transpose_225)[name = tensor("scores_29_cast_fp16")]; + tensor scores_31_cast_fp16 = select(a = var_48_to_fp16, b = scores_29_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_31_cast_fp16")]; + tensor var_1035_cast_fp16 = softmax(axis = var_61, x = scores_31_cast_fp16)[name = tensor("op_1035_cast_fp16")]; + tensor input_227_cast_fp16 = select(a = var_53_to_fp16, b = var_1035_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_227_cast_fp16")]; + tensor x_81_transpose_x_0 = const()[name = tensor("x_81_transpose_x_0"), val = tensor(false)]; + tensor x_81_transpose_y_0 = const()[name = tensor("x_81_transpose_y_0"), val = tensor(false)]; + tensor value_15_cast_fp16 = transpose(perm = value_15_perm_0, x = var_1008_cast_fp16)[name = tensor("transpose_727")]; + tensor x_81_cast_fp16 = matmul(transpose_x = x_81_transpose_x_0, transpose_y = x_81_transpose_y_0, x = input_227_cast_fp16, y = value_15_cast_fp16)[name = tensor("x_81_cast_fp16")]; + tensor var_1039_perm_0 = const()[name = tensor("op_1039_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1041 = const()[name = tensor("op_1041"), val = tensor([1, -1, 512])]; + tensor var_1039_cast_fp16 = transpose(perm = var_1039_perm_0, x = x_81_cast_fp16)[name = tensor("transpose_722")]; + tensor input_229_cast_fp16 = reshape(shape = var_1041, x = var_1039_cast_fp16)[name = tensor("input_229_cast_fp16")]; + tensor encoder_encoders_6_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_6_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45976320)))]; + tensor encoder_encoders_6_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_6_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46500672)))]; + tensor linear_29_cast_fp16 = linear(bias = encoder_encoders_6_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_6_self_attn_linear_out_weight_to_fp16, x = input_229_cast_fp16)[name = tensor("linear_29_cast_fp16")]; + tensor input_231_cast_fp16 = add(x = linear_29_cast_fp16, y = fsmn_memory_15_cast_fp16)[name = tensor("input_231_cast_fp16")]; + tensor input_233_cast_fp16 = add(x = input_217_cast_fp16, y = input_231_cast_fp16)[name = tensor("input_233_cast_fp16")]; + tensor output_31_axes_0 = const()[name = tensor("output_31_axes_0"), val = tensor([-1])]; + tensor const_52_to_fp16 = const()[name = tensor("const_52_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46501760)))]; + tensor const_53_to_fp16 = const()[name = tensor("const_53_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46502848)))]; + tensor output_31_cast_fp16 = layer_norm(axes = output_31_axes_0, beta = const_53_to_fp16, epsilon = var_46_to_fp16, gamma = const_52_to_fp16, x = input_233_cast_fp16)[name = tensor("output_31_cast_fp16")]; + tensor encoder_encoders_6_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_6_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46503936)))]; + tensor encoder_encoders_6_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_6_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48601152)))]; + tensor linear_30_cast_fp16 = linear(bias = encoder_encoders_6_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_6_feed_forward_w_1_weight_to_fp16, x = output_31_cast_fp16)[name = tensor("linear_30_cast_fp16")]; + tensor input_241_cast_fp16 = relu(x = linear_30_cast_fp16)[name = tensor("input_241_cast_fp16")]; + tensor encoder_encoders_6_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_6_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48605312)))]; + tensor encoder_encoders_6_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_6_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50702528)))]; + tensor linear_31_cast_fp16 = linear(bias = encoder_encoders_6_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_6_feed_forward_w_2_weight_to_fp16, x = input_241_cast_fp16)[name = tensor("linear_31_cast_fp16")]; + tensor input_247_cast_fp16 = add(x = input_233_cast_fp16, y = linear_31_cast_fp16)[name = tensor("input_247_cast_fp16")]; + tensor output_33_axes_0 = const()[name = tensor("output_33_axes_0"), val = tensor([-1])]; + tensor const_54_to_fp16 = const()[name = tensor("const_54_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50703616)))]; + tensor const_55_to_fp16 = const()[name = tensor("const_55_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50704704)))]; + tensor output_33_cast_fp16 = layer_norm(axes = output_33_axes_0, beta = const_55_to_fp16, epsilon = var_46_to_fp16, gamma = const_54_to_fp16, x = input_247_cast_fp16)[name = tensor("output_33_cast_fp16")]; + tensor encoder_encoders_7_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_7_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50705792)))]; + tensor encoder_encoders_7_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_7_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52278720)))]; + tensor linear_32_cast_fp16 = linear(bias = encoder_encoders_7_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_7_self_attn_linear_q_k_v_weight_to_fp16, x = output_33_cast_fp16)[name = tensor("linear_32_cast_fp16")]; + tensor tile_8 = const()[name = tensor("tile_8"), val = tensor([512, 512, 512])]; + tensor var_1099_axis_0 = const()[name = tensor("op_1099_axis_0"), val = tensor(-1)]; + tensor var_1099_cast_fp16_0, tensor var_1099_cast_fp16_1, tensor var_1099_cast_fp16_2 = split(axis = var_1099_axis_0, split_sizes = tile_8, x = linear_32_cast_fp16)[name = tensor("op_1099_cast_fp16")]; + tensor concat_24x = const()[name = tensor("concat_24x"), val = tensor([1, -1, 4, 128])]; + tensor var_1104_cast_fp16 = reshape(shape = concat_24x, x = var_1099_cast_fp16_0)[name = tensor("op_1104_cast_fp16")]; + tensor concat_25x = const()[name = tensor("concat_25x"), val = tensor([1, -1, 4, 128])]; + tensor var_1107_cast_fp16 = reshape(shape = concat_25x, x = var_1099_cast_fp16_1)[name = tensor("op_1107_cast_fp16")]; + tensor concat_26x = const()[name = tensor("concat_26x"), val = tensor([1, -1, 4, 128])]; + tensor var_1110_cast_fp16 = reshape(shape = concat_26x, x = var_1099_cast_fp16_2)[name = tensor("op_1110_cast_fp16")]; + tensor value_17_perm_0 = const()[name = tensor("value_17_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_17_cast_fp16 = mul(x = var_1099_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_17_cast_fp16")]; + tensor input_251_perm_0 = const()[name = tensor("input_251_perm_0"), val = tensor([0, 2, 1])]; + tensor input_253_pad_0 = const()[name = tensor("input_253_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_253_mode_0 = const()[name = tensor("input_253_mode_0"), val = tensor("constant")]; + tensor const_57_to_fp16 = const()[name = tensor("const_57_to_fp16"), val = tensor(0x0p+0)]; + tensor input_251_cast_fp16 = transpose(perm = input_251_perm_0, x = inputs_17_cast_fp16)[name = tensor("transpose_720")]; + tensor input_253_cast_fp16 = pad(constant_val = const_57_to_fp16, mode = input_253_mode_0, pad = input_253_pad_0, x = input_251_cast_fp16)[name = tensor("input_253_cast_fp16")]; + tensor x_85_pad_type_0 = const()[name = tensor("x_85_pad_type_0"), val = tensor("valid")]; + tensor x_85_groups_0 = const()[name = tensor("x_85_groups_0"), val = tensor(512)]; + tensor x_85_strides_0 = const()[name = tensor("x_85_strides_0"), val = tensor([1])]; + tensor x_85_pad_0 = const()[name = tensor("x_85_pad_0"), val = tensor([0, 0])]; + tensor x_85_dilations_0 = const()[name = tensor("x_85_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_7_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_7_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52281856)))]; + tensor x_85_cast_fp16 = conv(dilations = x_85_dilations_0, groups = x_85_groups_0, pad = x_85_pad_0, pad_type = x_85_pad_type_0, strides = x_85_strides_0, weight = encoder_encoders_7_self_attn_fsmn_block_weight_to_fp16, x = input_253_cast_fp16)[name = tensor("x_85_cast_fp16")]; + tensor x_87_perm_0 = const()[name = tensor("x_87_perm_0"), val = tensor([0, 2, 1])]; + tensor x_87_cast_fp16 = transpose(perm = x_87_perm_0, x = x_85_cast_fp16)[name = tensor("transpose_719")]; + tensor input_255_cast_fp16 = add(x = x_87_cast_fp16, y = inputs_17_cast_fp16)[name = tensor("input_255_cast_fp16")]; + tensor fsmn_memory_17_cast_fp16 = mul(x = input_255_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_17_cast_fp16")]; + tensor var_1129_to_fp16 = const()[name = tensor("op_1129_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_35_cast_fp16 = mul(x = var_1104_cast_fp16, y = var_1129_to_fp16)[name = tensor("q_h_35_cast_fp16")]; + tensor scores_33_transpose_x_0 = const()[name = tensor("scores_33_transpose_x_0"), val = tensor(false)]; + tensor scores_33_transpose_y_0 = const()[name = tensor("scores_33_transpose_y_0"), val = tensor(false)]; + tensor transpose_226_perm_0 = const()[name = tensor("transpose_226_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_227_perm_0 = const()[name = tensor("transpose_227_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_227 = transpose(perm = transpose_227_perm_0, x = var_1107_cast_fp16)[name = tensor("transpose_717")]; + tensor transpose_226 = transpose(perm = transpose_226_perm_0, x = q_h_35_cast_fp16)[name = tensor("transpose_718")]; + tensor scores_33_cast_fp16 = matmul(transpose_x = scores_33_transpose_x_0, transpose_y = scores_33_transpose_y_0, x = transpose_226, y = transpose_227)[name = tensor("scores_33_cast_fp16")]; + tensor scores_35_cast_fp16 = select(a = var_48_to_fp16, b = scores_33_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_35_cast_fp16")]; + tensor var_1137_cast_fp16 = softmax(axis = var_61, x = scores_35_cast_fp16)[name = tensor("op_1137_cast_fp16")]; + tensor input_257_cast_fp16 = select(a = var_53_to_fp16, b = var_1137_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_257_cast_fp16")]; + tensor x_91_transpose_x_0 = const()[name = tensor("x_91_transpose_x_0"), val = tensor(false)]; + tensor x_91_transpose_y_0 = const()[name = tensor("x_91_transpose_y_0"), val = tensor(false)]; + tensor value_17_cast_fp16 = transpose(perm = value_17_perm_0, x = var_1110_cast_fp16)[name = tensor("transpose_721")]; + tensor x_91_cast_fp16 = matmul(transpose_x = x_91_transpose_x_0, transpose_y = x_91_transpose_y_0, x = input_257_cast_fp16, y = value_17_cast_fp16)[name = tensor("x_91_cast_fp16")]; + tensor var_1141_perm_0 = const()[name = tensor("op_1141_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1143 = const()[name = tensor("op_1143"), val = tensor([1, -1, 512])]; + tensor var_1141_cast_fp16 = transpose(perm = var_1141_perm_0, x = x_91_cast_fp16)[name = tensor("transpose_716")]; + tensor input_259_cast_fp16 = reshape(shape = var_1143, x = var_1141_cast_fp16)[name = tensor("input_259_cast_fp16")]; + tensor encoder_encoders_7_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_7_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52293184)))]; + tensor encoder_encoders_7_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_7_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52817536)))]; + tensor linear_33_cast_fp16 = linear(bias = encoder_encoders_7_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_7_self_attn_linear_out_weight_to_fp16, x = input_259_cast_fp16)[name = tensor("linear_33_cast_fp16")]; + tensor input_261_cast_fp16 = add(x = linear_33_cast_fp16, y = fsmn_memory_17_cast_fp16)[name = tensor("input_261_cast_fp16")]; + tensor input_263_cast_fp16 = add(x = input_247_cast_fp16, y = input_261_cast_fp16)[name = tensor("input_263_cast_fp16")]; + tensor output_35_axes_0 = const()[name = tensor("output_35_axes_0"), val = tensor([-1])]; + tensor const_58_to_fp16 = const()[name = tensor("const_58_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52818624)))]; + tensor const_59_to_fp16 = const()[name = tensor("const_59_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52819712)))]; + tensor output_35_cast_fp16 = layer_norm(axes = output_35_axes_0, beta = const_59_to_fp16, epsilon = var_46_to_fp16, gamma = const_58_to_fp16, x = input_263_cast_fp16)[name = tensor("output_35_cast_fp16")]; + tensor encoder_encoders_7_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_7_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52820800)))]; + tensor encoder_encoders_7_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_7_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54918016)))]; + tensor linear_34_cast_fp16 = linear(bias = encoder_encoders_7_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_7_feed_forward_w_1_weight_to_fp16, x = output_35_cast_fp16)[name = tensor("linear_34_cast_fp16")]; + tensor input_271_cast_fp16 = relu(x = linear_34_cast_fp16)[name = tensor("input_271_cast_fp16")]; + tensor encoder_encoders_7_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_7_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54922176)))]; + tensor encoder_encoders_7_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_7_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57019392)))]; + tensor linear_35_cast_fp16 = linear(bias = encoder_encoders_7_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_7_feed_forward_w_2_weight_to_fp16, x = input_271_cast_fp16)[name = tensor("linear_35_cast_fp16")]; + tensor input_277_cast_fp16 = add(x = input_263_cast_fp16, y = linear_35_cast_fp16)[name = tensor("input_277_cast_fp16")]; + tensor output_37_axes_0 = const()[name = tensor("output_37_axes_0"), val = tensor([-1])]; + tensor const_60_to_fp16 = const()[name = tensor("const_60_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57020480)))]; + tensor const_61_to_fp16 = const()[name = tensor("const_61_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57021568)))]; + tensor output_37_cast_fp16 = layer_norm(axes = output_37_axes_0, beta = const_61_to_fp16, epsilon = var_46_to_fp16, gamma = const_60_to_fp16, x = input_277_cast_fp16)[name = tensor("output_37_cast_fp16")]; + tensor encoder_encoders_8_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_8_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57022656)))]; + tensor encoder_encoders_8_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_8_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(58595584)))]; + tensor linear_36_cast_fp16 = linear(bias = encoder_encoders_8_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_8_self_attn_linear_q_k_v_weight_to_fp16, x = output_37_cast_fp16)[name = tensor("linear_36_cast_fp16")]; + tensor tile_9 = const()[name = tensor("tile_9"), val = tensor([512, 512, 512])]; + tensor var_1201_axis_0 = const()[name = tensor("op_1201_axis_0"), val = tensor(-1)]; + tensor var_1201_cast_fp16_0, tensor var_1201_cast_fp16_1, tensor var_1201_cast_fp16_2 = split(axis = var_1201_axis_0, split_sizes = tile_9, x = linear_36_cast_fp16)[name = tensor("op_1201_cast_fp16")]; + tensor concat_27x = const()[name = tensor("concat_27x"), val = tensor([1, -1, 4, 128])]; + tensor var_1206_cast_fp16 = reshape(shape = concat_27x, x = var_1201_cast_fp16_0)[name = tensor("op_1206_cast_fp16")]; + tensor concat_28x = const()[name = tensor("concat_28x"), val = tensor([1, -1, 4, 128])]; + tensor var_1209_cast_fp16 = reshape(shape = concat_28x, x = var_1201_cast_fp16_1)[name = tensor("op_1209_cast_fp16")]; + tensor concat_29x = const()[name = tensor("concat_29x"), val = tensor([1, -1, 4, 128])]; + tensor var_1212_cast_fp16 = reshape(shape = concat_29x, x = var_1201_cast_fp16_2)[name = tensor("op_1212_cast_fp16")]; + tensor value_19_perm_0 = const()[name = tensor("value_19_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_19_cast_fp16 = mul(x = var_1201_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_19_cast_fp16")]; + tensor input_281_perm_0 = const()[name = tensor("input_281_perm_0"), val = tensor([0, 2, 1])]; + tensor input_283_pad_0 = const()[name = tensor("input_283_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_283_mode_0 = const()[name = tensor("input_283_mode_0"), val = tensor("constant")]; + tensor const_63_to_fp16 = const()[name = tensor("const_63_to_fp16"), val = tensor(0x0p+0)]; + tensor input_281_cast_fp16 = transpose(perm = input_281_perm_0, x = inputs_19_cast_fp16)[name = tensor("transpose_714")]; + tensor input_283_cast_fp16 = pad(constant_val = const_63_to_fp16, mode = input_283_mode_0, pad = input_283_pad_0, x = input_281_cast_fp16)[name = tensor("input_283_cast_fp16")]; + tensor x_95_pad_type_0 = const()[name = tensor("x_95_pad_type_0"), val = tensor("valid")]; + tensor x_95_groups_0 = const()[name = tensor("x_95_groups_0"), val = tensor(512)]; + tensor x_95_strides_0 = const()[name = tensor("x_95_strides_0"), val = tensor([1])]; + tensor x_95_pad_0 = const()[name = tensor("x_95_pad_0"), val = tensor([0, 0])]; + tensor x_95_dilations_0 = const()[name = tensor("x_95_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_8_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_8_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(58598720)))]; + tensor x_95_cast_fp16 = conv(dilations = x_95_dilations_0, groups = x_95_groups_0, pad = x_95_pad_0, pad_type = x_95_pad_type_0, strides = x_95_strides_0, weight = encoder_encoders_8_self_attn_fsmn_block_weight_to_fp16, x = input_283_cast_fp16)[name = tensor("x_95_cast_fp16")]; + tensor x_97_perm_0 = const()[name = tensor("x_97_perm_0"), val = tensor([0, 2, 1])]; + tensor x_97_cast_fp16 = transpose(perm = x_97_perm_0, x = x_95_cast_fp16)[name = tensor("transpose_713")]; + tensor input_285_cast_fp16 = add(x = x_97_cast_fp16, y = inputs_19_cast_fp16)[name = tensor("input_285_cast_fp16")]; + tensor fsmn_memory_19_cast_fp16 = mul(x = input_285_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_19_cast_fp16")]; + tensor var_1231_to_fp16 = const()[name = tensor("op_1231_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_39_cast_fp16 = mul(x = var_1206_cast_fp16, y = var_1231_to_fp16)[name = tensor("q_h_39_cast_fp16")]; + tensor scores_37_transpose_x_0 = const()[name = tensor("scores_37_transpose_x_0"), val = tensor(false)]; + tensor scores_37_transpose_y_0 = const()[name = tensor("scores_37_transpose_y_0"), val = tensor(false)]; + tensor transpose_228_perm_0 = const()[name = tensor("transpose_228_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_229_perm_0 = const()[name = tensor("transpose_229_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_229 = transpose(perm = transpose_229_perm_0, x = var_1209_cast_fp16)[name = tensor("transpose_711")]; + tensor transpose_228 = transpose(perm = transpose_228_perm_0, x = q_h_39_cast_fp16)[name = tensor("transpose_712")]; + tensor scores_37_cast_fp16 = matmul(transpose_x = scores_37_transpose_x_0, transpose_y = scores_37_transpose_y_0, x = transpose_228, y = transpose_229)[name = tensor("scores_37_cast_fp16")]; + tensor scores_39_cast_fp16 = select(a = var_48_to_fp16, b = scores_37_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_39_cast_fp16")]; + tensor var_1239_cast_fp16 = softmax(axis = var_61, x = scores_39_cast_fp16)[name = tensor("op_1239_cast_fp16")]; + tensor input_287_cast_fp16 = select(a = var_53_to_fp16, b = var_1239_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_287_cast_fp16")]; + tensor x_101_transpose_x_0 = const()[name = tensor("x_101_transpose_x_0"), val = tensor(false)]; + tensor x_101_transpose_y_0 = const()[name = tensor("x_101_transpose_y_0"), val = tensor(false)]; + tensor value_19_cast_fp16 = transpose(perm = value_19_perm_0, x = var_1212_cast_fp16)[name = tensor("transpose_715")]; + tensor x_101_cast_fp16 = matmul(transpose_x = x_101_transpose_x_0, transpose_y = x_101_transpose_y_0, x = input_287_cast_fp16, y = value_19_cast_fp16)[name = tensor("x_101_cast_fp16")]; + tensor var_1243_perm_0 = const()[name = tensor("op_1243_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1245 = const()[name = tensor("op_1245"), val = tensor([1, -1, 512])]; + tensor var_1243_cast_fp16 = transpose(perm = var_1243_perm_0, x = x_101_cast_fp16)[name = tensor("transpose_710")]; + tensor input_289_cast_fp16 = reshape(shape = var_1245, x = var_1243_cast_fp16)[name = tensor("input_289_cast_fp16")]; + tensor encoder_encoders_8_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_8_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(58610048)))]; + tensor encoder_encoders_8_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_8_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59134400)))]; + tensor linear_37_cast_fp16 = linear(bias = encoder_encoders_8_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_8_self_attn_linear_out_weight_to_fp16, x = input_289_cast_fp16)[name = tensor("linear_37_cast_fp16")]; + tensor input_291_cast_fp16 = add(x = linear_37_cast_fp16, y = fsmn_memory_19_cast_fp16)[name = tensor("input_291_cast_fp16")]; + tensor input_293_cast_fp16 = add(x = input_277_cast_fp16, y = input_291_cast_fp16)[name = tensor("input_293_cast_fp16")]; + tensor output_39_axes_0 = const()[name = tensor("output_39_axes_0"), val = tensor([-1])]; + tensor const_64_to_fp16 = const()[name = tensor("const_64_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59135488)))]; + tensor const_65_to_fp16 = const()[name = tensor("const_65_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59136576)))]; + tensor output_39_cast_fp16 = layer_norm(axes = output_39_axes_0, beta = const_65_to_fp16, epsilon = var_46_to_fp16, gamma = const_64_to_fp16, x = input_293_cast_fp16)[name = tensor("output_39_cast_fp16")]; + tensor encoder_encoders_8_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_8_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59137664)))]; + tensor encoder_encoders_8_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_8_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61234880)))]; + tensor linear_38_cast_fp16 = linear(bias = encoder_encoders_8_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_8_feed_forward_w_1_weight_to_fp16, x = output_39_cast_fp16)[name = tensor("linear_38_cast_fp16")]; + tensor input_301_cast_fp16 = relu(x = linear_38_cast_fp16)[name = tensor("input_301_cast_fp16")]; + tensor encoder_encoders_8_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_8_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61239040)))]; + tensor encoder_encoders_8_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_8_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63336256)))]; + tensor linear_39_cast_fp16 = linear(bias = encoder_encoders_8_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_8_feed_forward_w_2_weight_to_fp16, x = input_301_cast_fp16)[name = tensor("linear_39_cast_fp16")]; + tensor input_307_cast_fp16 = add(x = input_293_cast_fp16, y = linear_39_cast_fp16)[name = tensor("input_307_cast_fp16")]; + tensor output_41_axes_0 = const()[name = tensor("output_41_axes_0"), val = tensor([-1])]; + tensor const_66_to_fp16 = const()[name = tensor("const_66_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63337344)))]; + tensor const_67_to_fp16 = const()[name = tensor("const_67_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63338432)))]; + tensor output_41_cast_fp16 = layer_norm(axes = output_41_axes_0, beta = const_67_to_fp16, epsilon = var_46_to_fp16, gamma = const_66_to_fp16, x = input_307_cast_fp16)[name = tensor("output_41_cast_fp16")]; + tensor encoder_encoders_9_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_9_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63339520)))]; + tensor encoder_encoders_9_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_9_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64912448)))]; + tensor linear_40_cast_fp16 = linear(bias = encoder_encoders_9_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_9_self_attn_linear_q_k_v_weight_to_fp16, x = output_41_cast_fp16)[name = tensor("linear_40_cast_fp16")]; + tensor tile_10 = const()[name = tensor("tile_10"), val = tensor([512, 512, 512])]; + tensor var_1303_axis_0 = const()[name = tensor("op_1303_axis_0"), val = tensor(-1)]; + tensor var_1303_cast_fp16_0, tensor var_1303_cast_fp16_1, tensor var_1303_cast_fp16_2 = split(axis = var_1303_axis_0, split_sizes = tile_10, x = linear_40_cast_fp16)[name = tensor("op_1303_cast_fp16")]; + tensor concat_30x = const()[name = tensor("concat_30x"), val = tensor([1, -1, 4, 128])]; + tensor var_1308_cast_fp16 = reshape(shape = concat_30x, x = var_1303_cast_fp16_0)[name = tensor("op_1308_cast_fp16")]; + tensor concat_31x = const()[name = tensor("concat_31x"), val = tensor([1, -1, 4, 128])]; + tensor var_1311_cast_fp16 = reshape(shape = concat_31x, x = var_1303_cast_fp16_1)[name = tensor("op_1311_cast_fp16")]; + tensor concat_32x = const()[name = tensor("concat_32x"), val = tensor([1, -1, 4, 128])]; + tensor var_1314_cast_fp16 = reshape(shape = concat_32x, x = var_1303_cast_fp16_2)[name = tensor("op_1314_cast_fp16")]; + tensor value_21_perm_0 = const()[name = tensor("value_21_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_21_cast_fp16 = mul(x = var_1303_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_21_cast_fp16")]; + tensor input_311_perm_0 = const()[name = tensor("input_311_perm_0"), val = tensor([0, 2, 1])]; + tensor input_313_pad_0 = const()[name = tensor("input_313_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_313_mode_0 = const()[name = tensor("input_313_mode_0"), val = tensor("constant")]; + tensor const_69_to_fp16 = const()[name = tensor("const_69_to_fp16"), val = tensor(0x0p+0)]; + tensor input_311_cast_fp16 = transpose(perm = input_311_perm_0, x = inputs_21_cast_fp16)[name = tensor("transpose_708")]; + tensor input_313_cast_fp16 = pad(constant_val = const_69_to_fp16, mode = input_313_mode_0, pad = input_313_pad_0, x = input_311_cast_fp16)[name = tensor("input_313_cast_fp16")]; + tensor x_105_pad_type_0 = const()[name = tensor("x_105_pad_type_0"), val = tensor("valid")]; + tensor x_105_groups_0 = const()[name = tensor("x_105_groups_0"), val = tensor(512)]; + tensor x_105_strides_0 = const()[name = tensor("x_105_strides_0"), val = tensor([1])]; + tensor x_105_pad_0 = const()[name = tensor("x_105_pad_0"), val = tensor([0, 0])]; + tensor x_105_dilations_0 = const()[name = tensor("x_105_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_9_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_9_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64915584)))]; + tensor x_105_cast_fp16 = conv(dilations = x_105_dilations_0, groups = x_105_groups_0, pad = x_105_pad_0, pad_type = x_105_pad_type_0, strides = x_105_strides_0, weight = encoder_encoders_9_self_attn_fsmn_block_weight_to_fp16, x = input_313_cast_fp16)[name = tensor("x_105_cast_fp16")]; + tensor x_107_perm_0 = const()[name = tensor("x_107_perm_0"), val = tensor([0, 2, 1])]; + tensor x_107_cast_fp16 = transpose(perm = x_107_perm_0, x = x_105_cast_fp16)[name = tensor("transpose_707")]; + tensor input_315_cast_fp16 = add(x = x_107_cast_fp16, y = inputs_21_cast_fp16)[name = tensor("input_315_cast_fp16")]; + tensor fsmn_memory_21_cast_fp16 = mul(x = input_315_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_21_cast_fp16")]; + tensor var_1333_to_fp16 = const()[name = tensor("op_1333_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_43_cast_fp16 = mul(x = var_1308_cast_fp16, y = var_1333_to_fp16)[name = tensor("q_h_43_cast_fp16")]; + tensor scores_41_transpose_x_0 = const()[name = tensor("scores_41_transpose_x_0"), val = tensor(false)]; + tensor scores_41_transpose_y_0 = const()[name = tensor("scores_41_transpose_y_0"), val = tensor(false)]; + tensor transpose_230_perm_0 = const()[name = tensor("transpose_230_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_231_perm_0 = const()[name = tensor("transpose_231_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_231 = transpose(perm = transpose_231_perm_0, x = var_1311_cast_fp16)[name = tensor("transpose_705")]; + tensor transpose_230 = transpose(perm = transpose_230_perm_0, x = q_h_43_cast_fp16)[name = tensor("transpose_706")]; + tensor scores_41_cast_fp16 = matmul(transpose_x = scores_41_transpose_x_0, transpose_y = scores_41_transpose_y_0, x = transpose_230, y = transpose_231)[name = tensor("scores_41_cast_fp16")]; + tensor scores_43_cast_fp16 = select(a = var_48_to_fp16, b = scores_41_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_43_cast_fp16")]; + tensor var_1341_cast_fp16 = softmax(axis = var_61, x = scores_43_cast_fp16)[name = tensor("op_1341_cast_fp16")]; + tensor input_317_cast_fp16 = select(a = var_53_to_fp16, b = var_1341_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_317_cast_fp16")]; + tensor x_111_transpose_x_0 = const()[name = tensor("x_111_transpose_x_0"), val = tensor(false)]; + tensor x_111_transpose_y_0 = const()[name = tensor("x_111_transpose_y_0"), val = tensor(false)]; + tensor value_21_cast_fp16 = transpose(perm = value_21_perm_0, x = var_1314_cast_fp16)[name = tensor("transpose_709")]; + tensor x_111_cast_fp16 = matmul(transpose_x = x_111_transpose_x_0, transpose_y = x_111_transpose_y_0, x = input_317_cast_fp16, y = value_21_cast_fp16)[name = tensor("x_111_cast_fp16")]; + tensor var_1345_perm_0 = const()[name = tensor("op_1345_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1347 = const()[name = tensor("op_1347"), val = tensor([1, -1, 512])]; + tensor var_1345_cast_fp16 = transpose(perm = var_1345_perm_0, x = x_111_cast_fp16)[name = tensor("transpose_704")]; + tensor input_319_cast_fp16 = reshape(shape = var_1347, x = var_1345_cast_fp16)[name = tensor("input_319_cast_fp16")]; + tensor encoder_encoders_9_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_9_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64926912)))]; + tensor encoder_encoders_9_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_9_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65451264)))]; + tensor linear_41_cast_fp16 = linear(bias = encoder_encoders_9_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_9_self_attn_linear_out_weight_to_fp16, x = input_319_cast_fp16)[name = tensor("linear_41_cast_fp16")]; + tensor input_321_cast_fp16 = add(x = linear_41_cast_fp16, y = fsmn_memory_21_cast_fp16)[name = tensor("input_321_cast_fp16")]; + tensor input_323_cast_fp16 = add(x = input_307_cast_fp16, y = input_321_cast_fp16)[name = tensor("input_323_cast_fp16")]; + tensor output_43_axes_0 = const()[name = tensor("output_43_axes_0"), val = tensor([-1])]; + tensor const_70_to_fp16 = const()[name = tensor("const_70_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65452352)))]; + tensor const_71_to_fp16 = const()[name = tensor("const_71_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65453440)))]; + tensor output_43_cast_fp16 = layer_norm(axes = output_43_axes_0, beta = const_71_to_fp16, epsilon = var_46_to_fp16, gamma = const_70_to_fp16, x = input_323_cast_fp16)[name = tensor("output_43_cast_fp16")]; + tensor encoder_encoders_9_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_9_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65454528)))]; + tensor encoder_encoders_9_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_9_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67551744)))]; + tensor linear_42_cast_fp16 = linear(bias = encoder_encoders_9_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_9_feed_forward_w_1_weight_to_fp16, x = output_43_cast_fp16)[name = tensor("linear_42_cast_fp16")]; + tensor input_331_cast_fp16 = relu(x = linear_42_cast_fp16)[name = tensor("input_331_cast_fp16")]; + tensor encoder_encoders_9_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_9_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67555904)))]; + tensor encoder_encoders_9_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_9_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69653120)))]; + tensor linear_43_cast_fp16 = linear(bias = encoder_encoders_9_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_9_feed_forward_w_2_weight_to_fp16, x = input_331_cast_fp16)[name = tensor("linear_43_cast_fp16")]; + tensor input_337_cast_fp16 = add(x = input_323_cast_fp16, y = linear_43_cast_fp16)[name = tensor("input_337_cast_fp16")]; + tensor output_45_axes_0 = const()[name = tensor("output_45_axes_0"), val = tensor([-1])]; + tensor const_72_to_fp16 = const()[name = tensor("const_72_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69654208)))]; + tensor const_73_to_fp16 = const()[name = tensor("const_73_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69655296)))]; + tensor output_45_cast_fp16 = layer_norm(axes = output_45_axes_0, beta = const_73_to_fp16, epsilon = var_46_to_fp16, gamma = const_72_to_fp16, x = input_337_cast_fp16)[name = tensor("output_45_cast_fp16")]; + tensor encoder_encoders_10_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_10_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69656384)))]; + tensor encoder_encoders_10_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_10_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71229312)))]; + tensor linear_44_cast_fp16 = linear(bias = encoder_encoders_10_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_10_self_attn_linear_q_k_v_weight_to_fp16, x = output_45_cast_fp16)[name = tensor("linear_44_cast_fp16")]; + tensor tile_11 = const()[name = tensor("tile_11"), val = tensor([512, 512, 512])]; + tensor var_1405_axis_0 = const()[name = tensor("op_1405_axis_0"), val = tensor(-1)]; + tensor var_1405_cast_fp16_0, tensor var_1405_cast_fp16_1, tensor var_1405_cast_fp16_2 = split(axis = var_1405_axis_0, split_sizes = tile_11, x = linear_44_cast_fp16)[name = tensor("op_1405_cast_fp16")]; + tensor concat_33x = const()[name = tensor("concat_33x"), val = tensor([1, -1, 4, 128])]; + tensor var_1410_cast_fp16 = reshape(shape = concat_33x, x = var_1405_cast_fp16_0)[name = tensor("op_1410_cast_fp16")]; + tensor concat_34x = const()[name = tensor("concat_34x"), val = tensor([1, -1, 4, 128])]; + tensor var_1413_cast_fp16 = reshape(shape = concat_34x, x = var_1405_cast_fp16_1)[name = tensor("op_1413_cast_fp16")]; + tensor concat_35x = const()[name = tensor("concat_35x"), val = tensor([1, -1, 4, 128])]; + tensor var_1416_cast_fp16 = reshape(shape = concat_35x, x = var_1405_cast_fp16_2)[name = tensor("op_1416_cast_fp16")]; + tensor value_23_perm_0 = const()[name = tensor("value_23_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_23_cast_fp16 = mul(x = var_1405_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_23_cast_fp16")]; + tensor input_341_perm_0 = const()[name = tensor("input_341_perm_0"), val = tensor([0, 2, 1])]; + tensor input_343_pad_0 = const()[name = tensor("input_343_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_343_mode_0 = const()[name = tensor("input_343_mode_0"), val = tensor("constant")]; + tensor const_75_to_fp16 = const()[name = tensor("const_75_to_fp16"), val = tensor(0x0p+0)]; + tensor input_341_cast_fp16 = transpose(perm = input_341_perm_0, x = inputs_23_cast_fp16)[name = tensor("transpose_702")]; + tensor input_343_cast_fp16 = pad(constant_val = const_75_to_fp16, mode = input_343_mode_0, pad = input_343_pad_0, x = input_341_cast_fp16)[name = tensor("input_343_cast_fp16")]; + tensor x_115_pad_type_0 = const()[name = tensor("x_115_pad_type_0"), val = tensor("valid")]; + tensor x_115_groups_0 = const()[name = tensor("x_115_groups_0"), val = tensor(512)]; + tensor x_115_strides_0 = const()[name = tensor("x_115_strides_0"), val = tensor([1])]; + tensor x_115_pad_0 = const()[name = tensor("x_115_pad_0"), val = tensor([0, 0])]; + tensor x_115_dilations_0 = const()[name = tensor("x_115_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_10_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_10_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71232448)))]; + tensor x_115_cast_fp16 = conv(dilations = x_115_dilations_0, groups = x_115_groups_0, pad = x_115_pad_0, pad_type = x_115_pad_type_0, strides = x_115_strides_0, weight = encoder_encoders_10_self_attn_fsmn_block_weight_to_fp16, x = input_343_cast_fp16)[name = tensor("x_115_cast_fp16")]; + tensor x_117_perm_0 = const()[name = tensor("x_117_perm_0"), val = tensor([0, 2, 1])]; + tensor x_117_cast_fp16 = transpose(perm = x_117_perm_0, x = x_115_cast_fp16)[name = tensor("transpose_701")]; + tensor input_345_cast_fp16 = add(x = x_117_cast_fp16, y = inputs_23_cast_fp16)[name = tensor("input_345_cast_fp16")]; + tensor fsmn_memory_23_cast_fp16 = mul(x = input_345_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_23_cast_fp16")]; + tensor var_1435_to_fp16 = const()[name = tensor("op_1435_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_47_cast_fp16 = mul(x = var_1410_cast_fp16, y = var_1435_to_fp16)[name = tensor("q_h_47_cast_fp16")]; + tensor scores_45_transpose_x_0 = const()[name = tensor("scores_45_transpose_x_0"), val = tensor(false)]; + tensor scores_45_transpose_y_0 = const()[name = tensor("scores_45_transpose_y_0"), val = tensor(false)]; + tensor transpose_232_perm_0 = const()[name = tensor("transpose_232_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_233_perm_0 = const()[name = tensor("transpose_233_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_233 = transpose(perm = transpose_233_perm_0, x = var_1413_cast_fp16)[name = tensor("transpose_699")]; + tensor transpose_232 = transpose(perm = transpose_232_perm_0, x = q_h_47_cast_fp16)[name = tensor("transpose_700")]; + tensor scores_45_cast_fp16 = matmul(transpose_x = scores_45_transpose_x_0, transpose_y = scores_45_transpose_y_0, x = transpose_232, y = transpose_233)[name = tensor("scores_45_cast_fp16")]; + tensor scores_47_cast_fp16 = select(a = var_48_to_fp16, b = scores_45_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_47_cast_fp16")]; + tensor var_1443_cast_fp16 = softmax(axis = var_61, x = scores_47_cast_fp16)[name = tensor("op_1443_cast_fp16")]; + tensor input_347_cast_fp16 = select(a = var_53_to_fp16, b = var_1443_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_347_cast_fp16")]; + tensor x_121_transpose_x_0 = const()[name = tensor("x_121_transpose_x_0"), val = tensor(false)]; + tensor x_121_transpose_y_0 = const()[name = tensor("x_121_transpose_y_0"), val = tensor(false)]; + tensor value_23_cast_fp16 = transpose(perm = value_23_perm_0, x = var_1416_cast_fp16)[name = tensor("transpose_703")]; + tensor x_121_cast_fp16 = matmul(transpose_x = x_121_transpose_x_0, transpose_y = x_121_transpose_y_0, x = input_347_cast_fp16, y = value_23_cast_fp16)[name = tensor("x_121_cast_fp16")]; + tensor var_1447_perm_0 = const()[name = tensor("op_1447_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1449 = const()[name = tensor("op_1449"), val = tensor([1, -1, 512])]; + tensor var_1447_cast_fp16 = transpose(perm = var_1447_perm_0, x = x_121_cast_fp16)[name = tensor("transpose_698")]; + tensor input_349_cast_fp16 = reshape(shape = var_1449, x = var_1447_cast_fp16)[name = tensor("input_349_cast_fp16")]; + tensor encoder_encoders_10_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_10_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71243776)))]; + tensor encoder_encoders_10_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_10_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71768128)))]; + tensor linear_45_cast_fp16 = linear(bias = encoder_encoders_10_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_10_self_attn_linear_out_weight_to_fp16, x = input_349_cast_fp16)[name = tensor("linear_45_cast_fp16")]; + tensor input_351_cast_fp16 = add(x = linear_45_cast_fp16, y = fsmn_memory_23_cast_fp16)[name = tensor("input_351_cast_fp16")]; + tensor input_353_cast_fp16 = add(x = input_337_cast_fp16, y = input_351_cast_fp16)[name = tensor("input_353_cast_fp16")]; + tensor output_47_axes_0 = const()[name = tensor("output_47_axes_0"), val = tensor([-1])]; + tensor const_76_to_fp16 = const()[name = tensor("const_76_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71769216)))]; + tensor const_77_to_fp16 = const()[name = tensor("const_77_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71770304)))]; + tensor output_47_cast_fp16 = layer_norm(axes = output_47_axes_0, beta = const_77_to_fp16, epsilon = var_46_to_fp16, gamma = const_76_to_fp16, x = input_353_cast_fp16)[name = tensor("output_47_cast_fp16")]; + tensor encoder_encoders_10_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_10_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71771392)))]; + tensor encoder_encoders_10_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_10_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73868608)))]; + tensor linear_46_cast_fp16 = linear(bias = encoder_encoders_10_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_10_feed_forward_w_1_weight_to_fp16, x = output_47_cast_fp16)[name = tensor("linear_46_cast_fp16")]; + tensor input_361_cast_fp16 = relu(x = linear_46_cast_fp16)[name = tensor("input_361_cast_fp16")]; + tensor encoder_encoders_10_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_10_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73872768)))]; + tensor encoder_encoders_10_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_10_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75969984)))]; + tensor linear_47_cast_fp16 = linear(bias = encoder_encoders_10_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_10_feed_forward_w_2_weight_to_fp16, x = input_361_cast_fp16)[name = tensor("linear_47_cast_fp16")]; + tensor input_367_cast_fp16 = add(x = input_353_cast_fp16, y = linear_47_cast_fp16)[name = tensor("input_367_cast_fp16")]; + tensor output_49_axes_0 = const()[name = tensor("output_49_axes_0"), val = tensor([-1])]; + tensor const_78_to_fp16 = const()[name = tensor("const_78_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75971072)))]; + tensor const_79_to_fp16 = const()[name = tensor("const_79_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75972160)))]; + tensor output_49_cast_fp16 = layer_norm(axes = output_49_axes_0, beta = const_79_to_fp16, epsilon = var_46_to_fp16, gamma = const_78_to_fp16, x = input_367_cast_fp16)[name = tensor("output_49_cast_fp16")]; + tensor encoder_encoders_11_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_11_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75973248)))]; + tensor encoder_encoders_11_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_11_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77546176)))]; + tensor linear_48_cast_fp16 = linear(bias = encoder_encoders_11_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_11_self_attn_linear_q_k_v_weight_to_fp16, x = output_49_cast_fp16)[name = tensor("linear_48_cast_fp16")]; + tensor tile_12 = const()[name = tensor("tile_12"), val = tensor([512, 512, 512])]; + tensor var_1507_axis_0 = const()[name = tensor("op_1507_axis_0"), val = tensor(-1)]; + tensor var_1507_cast_fp16_0, tensor var_1507_cast_fp16_1, tensor var_1507_cast_fp16_2 = split(axis = var_1507_axis_0, split_sizes = tile_12, x = linear_48_cast_fp16)[name = tensor("op_1507_cast_fp16")]; + tensor concat_36x = const()[name = tensor("concat_36x"), val = tensor([1, -1, 4, 128])]; + tensor var_1512_cast_fp16 = reshape(shape = concat_36x, x = var_1507_cast_fp16_0)[name = tensor("op_1512_cast_fp16")]; + tensor concat_37x = const()[name = tensor("concat_37x"), val = tensor([1, -1, 4, 128])]; + tensor var_1515_cast_fp16 = reshape(shape = concat_37x, x = var_1507_cast_fp16_1)[name = tensor("op_1515_cast_fp16")]; + tensor concat_38x = const()[name = tensor("concat_38x"), val = tensor([1, -1, 4, 128])]; + tensor var_1518_cast_fp16 = reshape(shape = concat_38x, x = var_1507_cast_fp16_2)[name = tensor("op_1518_cast_fp16")]; + tensor value_25_perm_0 = const()[name = tensor("value_25_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_25_cast_fp16 = mul(x = var_1507_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_25_cast_fp16")]; + tensor input_371_perm_0 = const()[name = tensor("input_371_perm_0"), val = tensor([0, 2, 1])]; + tensor input_373_pad_0 = const()[name = tensor("input_373_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_373_mode_0 = const()[name = tensor("input_373_mode_0"), val = tensor("constant")]; + tensor const_81_to_fp16 = const()[name = tensor("const_81_to_fp16"), val = tensor(0x0p+0)]; + tensor input_371_cast_fp16 = transpose(perm = input_371_perm_0, x = inputs_25_cast_fp16)[name = tensor("transpose_696")]; + tensor input_373_cast_fp16 = pad(constant_val = const_81_to_fp16, mode = input_373_mode_0, pad = input_373_pad_0, x = input_371_cast_fp16)[name = tensor("input_373_cast_fp16")]; + tensor x_125_pad_type_0 = const()[name = tensor("x_125_pad_type_0"), val = tensor("valid")]; + tensor x_125_groups_0 = const()[name = tensor("x_125_groups_0"), val = tensor(512)]; + tensor x_125_strides_0 = const()[name = tensor("x_125_strides_0"), val = tensor([1])]; + tensor x_125_pad_0 = const()[name = tensor("x_125_pad_0"), val = tensor([0, 0])]; + tensor x_125_dilations_0 = const()[name = tensor("x_125_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_11_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_11_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77549312)))]; + tensor x_125_cast_fp16 = conv(dilations = x_125_dilations_0, groups = x_125_groups_0, pad = x_125_pad_0, pad_type = x_125_pad_type_0, strides = x_125_strides_0, weight = encoder_encoders_11_self_attn_fsmn_block_weight_to_fp16, x = input_373_cast_fp16)[name = tensor("x_125_cast_fp16")]; + tensor x_127_perm_0 = const()[name = tensor("x_127_perm_0"), val = tensor([0, 2, 1])]; + tensor x_127_cast_fp16 = transpose(perm = x_127_perm_0, x = x_125_cast_fp16)[name = tensor("transpose_695")]; + tensor input_375_cast_fp16 = add(x = x_127_cast_fp16, y = inputs_25_cast_fp16)[name = tensor("input_375_cast_fp16")]; + tensor fsmn_memory_25_cast_fp16 = mul(x = input_375_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_25_cast_fp16")]; + tensor var_1537_to_fp16 = const()[name = tensor("op_1537_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_51_cast_fp16 = mul(x = var_1512_cast_fp16, y = var_1537_to_fp16)[name = tensor("q_h_51_cast_fp16")]; + tensor scores_49_transpose_x_0 = const()[name = tensor("scores_49_transpose_x_0"), val = tensor(false)]; + tensor scores_49_transpose_y_0 = const()[name = tensor("scores_49_transpose_y_0"), val = tensor(false)]; + tensor transpose_234_perm_0 = const()[name = tensor("transpose_234_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_235_perm_0 = const()[name = tensor("transpose_235_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_235 = transpose(perm = transpose_235_perm_0, x = var_1515_cast_fp16)[name = tensor("transpose_693")]; + tensor transpose_234 = transpose(perm = transpose_234_perm_0, x = q_h_51_cast_fp16)[name = tensor("transpose_694")]; + tensor scores_49_cast_fp16 = matmul(transpose_x = scores_49_transpose_x_0, transpose_y = scores_49_transpose_y_0, x = transpose_234, y = transpose_235)[name = tensor("scores_49_cast_fp16")]; + tensor scores_51_cast_fp16 = select(a = var_48_to_fp16, b = scores_49_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_51_cast_fp16")]; + tensor var_1545_cast_fp16 = softmax(axis = var_61, x = scores_51_cast_fp16)[name = tensor("op_1545_cast_fp16")]; + tensor input_377_cast_fp16 = select(a = var_53_to_fp16, b = var_1545_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_377_cast_fp16")]; + tensor x_131_transpose_x_0 = const()[name = tensor("x_131_transpose_x_0"), val = tensor(false)]; + tensor x_131_transpose_y_0 = const()[name = tensor("x_131_transpose_y_0"), val = tensor(false)]; + tensor value_25_cast_fp16 = transpose(perm = value_25_perm_0, x = var_1518_cast_fp16)[name = tensor("transpose_697")]; + tensor x_131_cast_fp16 = matmul(transpose_x = x_131_transpose_x_0, transpose_y = x_131_transpose_y_0, x = input_377_cast_fp16, y = value_25_cast_fp16)[name = tensor("x_131_cast_fp16")]; + tensor var_1549_perm_0 = const()[name = tensor("op_1549_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1551 = const()[name = tensor("op_1551"), val = tensor([1, -1, 512])]; + tensor var_1549_cast_fp16 = transpose(perm = var_1549_perm_0, x = x_131_cast_fp16)[name = tensor("transpose_692")]; + tensor input_379_cast_fp16 = reshape(shape = var_1551, x = var_1549_cast_fp16)[name = tensor("input_379_cast_fp16")]; + tensor encoder_encoders_11_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_11_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77560640)))]; + tensor encoder_encoders_11_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_11_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78084992)))]; + tensor linear_49_cast_fp16 = linear(bias = encoder_encoders_11_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_11_self_attn_linear_out_weight_to_fp16, x = input_379_cast_fp16)[name = tensor("linear_49_cast_fp16")]; + tensor input_381_cast_fp16 = add(x = linear_49_cast_fp16, y = fsmn_memory_25_cast_fp16)[name = tensor("input_381_cast_fp16")]; + tensor input_383_cast_fp16 = add(x = input_367_cast_fp16, y = input_381_cast_fp16)[name = tensor("input_383_cast_fp16")]; + tensor output_51_axes_0 = const()[name = tensor("output_51_axes_0"), val = tensor([-1])]; + tensor const_82_to_fp16 = const()[name = tensor("const_82_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78086080)))]; + tensor const_83_to_fp16 = const()[name = tensor("const_83_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78087168)))]; + tensor output_51_cast_fp16 = layer_norm(axes = output_51_axes_0, beta = const_83_to_fp16, epsilon = var_46_to_fp16, gamma = const_82_to_fp16, x = input_383_cast_fp16)[name = tensor("output_51_cast_fp16")]; + tensor encoder_encoders_11_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_11_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78088256)))]; + tensor encoder_encoders_11_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_11_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80185472)))]; + tensor linear_50_cast_fp16 = linear(bias = encoder_encoders_11_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_11_feed_forward_w_1_weight_to_fp16, x = output_51_cast_fp16)[name = tensor("linear_50_cast_fp16")]; + tensor input_391_cast_fp16 = relu(x = linear_50_cast_fp16)[name = tensor("input_391_cast_fp16")]; + tensor encoder_encoders_11_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_11_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80189632)))]; + tensor encoder_encoders_11_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_11_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82286848)))]; + tensor linear_51_cast_fp16 = linear(bias = encoder_encoders_11_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_11_feed_forward_w_2_weight_to_fp16, x = input_391_cast_fp16)[name = tensor("linear_51_cast_fp16")]; + tensor input_397_cast_fp16 = add(x = input_383_cast_fp16, y = linear_51_cast_fp16)[name = tensor("input_397_cast_fp16")]; + tensor output_53_axes_0 = const()[name = tensor("output_53_axes_0"), val = tensor([-1])]; + tensor const_84_to_fp16 = const()[name = tensor("const_84_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82287936)))]; + tensor const_85_to_fp16 = const()[name = tensor("const_85_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82289024)))]; + tensor output_53_cast_fp16 = layer_norm(axes = output_53_axes_0, beta = const_85_to_fp16, epsilon = var_46_to_fp16, gamma = const_84_to_fp16, x = input_397_cast_fp16)[name = tensor("output_53_cast_fp16")]; + tensor encoder_encoders_12_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_12_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82290112)))]; + tensor encoder_encoders_12_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_12_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83863040)))]; + tensor linear_52_cast_fp16 = linear(bias = encoder_encoders_12_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_12_self_attn_linear_q_k_v_weight_to_fp16, x = output_53_cast_fp16)[name = tensor("linear_52_cast_fp16")]; + tensor tile_13 = const()[name = tensor("tile_13"), val = tensor([512, 512, 512])]; + tensor var_1609_axis_0 = const()[name = tensor("op_1609_axis_0"), val = tensor(-1)]; + tensor var_1609_cast_fp16_0, tensor var_1609_cast_fp16_1, tensor var_1609_cast_fp16_2 = split(axis = var_1609_axis_0, split_sizes = tile_13, x = linear_52_cast_fp16)[name = tensor("op_1609_cast_fp16")]; + tensor concat_39x = const()[name = tensor("concat_39x"), val = tensor([1, -1, 4, 128])]; + tensor var_1614_cast_fp16 = reshape(shape = concat_39x, x = var_1609_cast_fp16_0)[name = tensor("op_1614_cast_fp16")]; + tensor concat_40x = const()[name = tensor("concat_40x"), val = tensor([1, -1, 4, 128])]; + tensor var_1617_cast_fp16 = reshape(shape = concat_40x, x = var_1609_cast_fp16_1)[name = tensor("op_1617_cast_fp16")]; + tensor concat_41x = const()[name = tensor("concat_41x"), val = tensor([1, -1, 4, 128])]; + tensor var_1620_cast_fp16 = reshape(shape = concat_41x, x = var_1609_cast_fp16_2)[name = tensor("op_1620_cast_fp16")]; + tensor value_27_perm_0 = const()[name = tensor("value_27_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_27_cast_fp16 = mul(x = var_1609_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_27_cast_fp16")]; + tensor input_401_perm_0 = const()[name = tensor("input_401_perm_0"), val = tensor([0, 2, 1])]; + tensor input_403_pad_0 = const()[name = tensor("input_403_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_403_mode_0 = const()[name = tensor("input_403_mode_0"), val = tensor("constant")]; + tensor const_87_to_fp16 = const()[name = tensor("const_87_to_fp16"), val = tensor(0x0p+0)]; + tensor input_401_cast_fp16 = transpose(perm = input_401_perm_0, x = inputs_27_cast_fp16)[name = tensor("transpose_690")]; + tensor input_403_cast_fp16 = pad(constant_val = const_87_to_fp16, mode = input_403_mode_0, pad = input_403_pad_0, x = input_401_cast_fp16)[name = tensor("input_403_cast_fp16")]; + tensor x_135_pad_type_0 = const()[name = tensor("x_135_pad_type_0"), val = tensor("valid")]; + tensor x_135_groups_0 = const()[name = tensor("x_135_groups_0"), val = tensor(512)]; + tensor x_135_strides_0 = const()[name = tensor("x_135_strides_0"), val = tensor([1])]; + tensor x_135_pad_0 = const()[name = tensor("x_135_pad_0"), val = tensor([0, 0])]; + tensor x_135_dilations_0 = const()[name = tensor("x_135_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_12_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_12_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83866176)))]; + tensor x_135_cast_fp16 = conv(dilations = x_135_dilations_0, groups = x_135_groups_0, pad = x_135_pad_0, pad_type = x_135_pad_type_0, strides = x_135_strides_0, weight = encoder_encoders_12_self_attn_fsmn_block_weight_to_fp16, x = input_403_cast_fp16)[name = tensor("x_135_cast_fp16")]; + tensor x_137_perm_0 = const()[name = tensor("x_137_perm_0"), val = tensor([0, 2, 1])]; + tensor x_137_cast_fp16 = transpose(perm = x_137_perm_0, x = x_135_cast_fp16)[name = tensor("transpose_689")]; + tensor input_405_cast_fp16 = add(x = x_137_cast_fp16, y = inputs_27_cast_fp16)[name = tensor("input_405_cast_fp16")]; + tensor fsmn_memory_27_cast_fp16 = mul(x = input_405_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_27_cast_fp16")]; + tensor var_1639_to_fp16 = const()[name = tensor("op_1639_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_55_cast_fp16 = mul(x = var_1614_cast_fp16, y = var_1639_to_fp16)[name = tensor("q_h_55_cast_fp16")]; + tensor scores_53_transpose_x_0 = const()[name = tensor("scores_53_transpose_x_0"), val = tensor(false)]; + tensor scores_53_transpose_y_0 = const()[name = tensor("scores_53_transpose_y_0"), val = tensor(false)]; + tensor transpose_236_perm_0 = const()[name = tensor("transpose_236_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_237_perm_0 = const()[name = tensor("transpose_237_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_237 = transpose(perm = transpose_237_perm_0, x = var_1617_cast_fp16)[name = tensor("transpose_687")]; + tensor transpose_236 = transpose(perm = transpose_236_perm_0, x = q_h_55_cast_fp16)[name = tensor("transpose_688")]; + tensor scores_53_cast_fp16 = matmul(transpose_x = scores_53_transpose_x_0, transpose_y = scores_53_transpose_y_0, x = transpose_236, y = transpose_237)[name = tensor("scores_53_cast_fp16")]; + tensor scores_55_cast_fp16 = select(a = var_48_to_fp16, b = scores_53_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_55_cast_fp16")]; + tensor var_1647_cast_fp16 = softmax(axis = var_61, x = scores_55_cast_fp16)[name = tensor("op_1647_cast_fp16")]; + tensor input_407_cast_fp16 = select(a = var_53_to_fp16, b = var_1647_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_407_cast_fp16")]; + tensor x_141_transpose_x_0 = const()[name = tensor("x_141_transpose_x_0"), val = tensor(false)]; + tensor x_141_transpose_y_0 = const()[name = tensor("x_141_transpose_y_0"), val = tensor(false)]; + tensor value_27_cast_fp16 = transpose(perm = value_27_perm_0, x = var_1620_cast_fp16)[name = tensor("transpose_691")]; + tensor x_141_cast_fp16 = matmul(transpose_x = x_141_transpose_x_0, transpose_y = x_141_transpose_y_0, x = input_407_cast_fp16, y = value_27_cast_fp16)[name = tensor("x_141_cast_fp16")]; + tensor var_1651_perm_0 = const()[name = tensor("op_1651_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1653 = const()[name = tensor("op_1653"), val = tensor([1, -1, 512])]; + tensor var_1651_cast_fp16 = transpose(perm = var_1651_perm_0, x = x_141_cast_fp16)[name = tensor("transpose_686")]; + tensor input_409_cast_fp16 = reshape(shape = var_1653, x = var_1651_cast_fp16)[name = tensor("input_409_cast_fp16")]; + tensor encoder_encoders_12_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_12_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83877504)))]; + tensor encoder_encoders_12_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_12_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84401856)))]; + tensor linear_53_cast_fp16 = linear(bias = encoder_encoders_12_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_12_self_attn_linear_out_weight_to_fp16, x = input_409_cast_fp16)[name = tensor("linear_53_cast_fp16")]; + tensor input_411_cast_fp16 = add(x = linear_53_cast_fp16, y = fsmn_memory_27_cast_fp16)[name = tensor("input_411_cast_fp16")]; + tensor input_413_cast_fp16 = add(x = input_397_cast_fp16, y = input_411_cast_fp16)[name = tensor("input_413_cast_fp16")]; + tensor output_55_axes_0 = const()[name = tensor("output_55_axes_0"), val = tensor([-1])]; + tensor const_88_to_fp16 = const()[name = tensor("const_88_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84402944)))]; + tensor const_89_to_fp16 = const()[name = tensor("const_89_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84404032)))]; + tensor output_55_cast_fp16 = layer_norm(axes = output_55_axes_0, beta = const_89_to_fp16, epsilon = var_46_to_fp16, gamma = const_88_to_fp16, x = input_413_cast_fp16)[name = tensor("output_55_cast_fp16")]; + tensor encoder_encoders_12_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_12_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84405120)))]; + tensor encoder_encoders_12_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_12_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86502336)))]; + tensor linear_54_cast_fp16 = linear(bias = encoder_encoders_12_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_12_feed_forward_w_1_weight_to_fp16, x = output_55_cast_fp16)[name = tensor("linear_54_cast_fp16")]; + tensor input_421_cast_fp16 = relu(x = linear_54_cast_fp16)[name = tensor("input_421_cast_fp16")]; + tensor encoder_encoders_12_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_12_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86506496)))]; + tensor encoder_encoders_12_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_12_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88603712)))]; + tensor linear_55_cast_fp16 = linear(bias = encoder_encoders_12_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_12_feed_forward_w_2_weight_to_fp16, x = input_421_cast_fp16)[name = tensor("linear_55_cast_fp16")]; + tensor input_427_cast_fp16 = add(x = input_413_cast_fp16, y = linear_55_cast_fp16)[name = tensor("input_427_cast_fp16")]; + tensor output_57_axes_0 = const()[name = tensor("output_57_axes_0"), val = tensor([-1])]; + tensor const_90_to_fp16 = const()[name = tensor("const_90_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88604800)))]; + tensor const_91_to_fp16 = const()[name = tensor("const_91_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88605888)))]; + tensor output_57_cast_fp16 = layer_norm(axes = output_57_axes_0, beta = const_91_to_fp16, epsilon = var_46_to_fp16, gamma = const_90_to_fp16, x = input_427_cast_fp16)[name = tensor("output_57_cast_fp16")]; + tensor encoder_encoders_13_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_13_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88606976)))]; + tensor encoder_encoders_13_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_13_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90179904)))]; + tensor linear_56_cast_fp16 = linear(bias = encoder_encoders_13_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_13_self_attn_linear_q_k_v_weight_to_fp16, x = output_57_cast_fp16)[name = tensor("linear_56_cast_fp16")]; + tensor tile_14 = const()[name = tensor("tile_14"), val = tensor([512, 512, 512])]; + tensor var_1711_axis_0 = const()[name = tensor("op_1711_axis_0"), val = tensor(-1)]; + tensor var_1711_cast_fp16_0, tensor var_1711_cast_fp16_1, tensor var_1711_cast_fp16_2 = split(axis = var_1711_axis_0, split_sizes = tile_14, x = linear_56_cast_fp16)[name = tensor("op_1711_cast_fp16")]; + tensor concat_42x = const()[name = tensor("concat_42x"), val = tensor([1, -1, 4, 128])]; + tensor var_1716_cast_fp16 = reshape(shape = concat_42x, x = var_1711_cast_fp16_0)[name = tensor("op_1716_cast_fp16")]; + tensor concat_43x = const()[name = tensor("concat_43x"), val = tensor([1, -1, 4, 128])]; + tensor var_1719_cast_fp16 = reshape(shape = concat_43x, x = var_1711_cast_fp16_1)[name = tensor("op_1719_cast_fp16")]; + tensor concat_44x = const()[name = tensor("concat_44x"), val = tensor([1, -1, 4, 128])]; + tensor var_1722_cast_fp16 = reshape(shape = concat_44x, x = var_1711_cast_fp16_2)[name = tensor("op_1722_cast_fp16")]; + tensor value_29_perm_0 = const()[name = tensor("value_29_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_29_cast_fp16 = mul(x = var_1711_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_29_cast_fp16")]; + tensor input_431_perm_0 = const()[name = tensor("input_431_perm_0"), val = tensor([0, 2, 1])]; + tensor input_433_pad_0 = const()[name = tensor("input_433_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_433_mode_0 = const()[name = tensor("input_433_mode_0"), val = tensor("constant")]; + tensor const_93_to_fp16 = const()[name = tensor("const_93_to_fp16"), val = tensor(0x0p+0)]; + tensor input_431_cast_fp16 = transpose(perm = input_431_perm_0, x = inputs_29_cast_fp16)[name = tensor("transpose_684")]; + tensor input_433_cast_fp16 = pad(constant_val = const_93_to_fp16, mode = input_433_mode_0, pad = input_433_pad_0, x = input_431_cast_fp16)[name = tensor("input_433_cast_fp16")]; + tensor x_145_pad_type_0 = const()[name = tensor("x_145_pad_type_0"), val = tensor("valid")]; + tensor x_145_groups_0 = const()[name = tensor("x_145_groups_0"), val = tensor(512)]; + tensor x_145_strides_0 = const()[name = tensor("x_145_strides_0"), val = tensor([1])]; + tensor x_145_pad_0 = const()[name = tensor("x_145_pad_0"), val = tensor([0, 0])]; + tensor x_145_dilations_0 = const()[name = tensor("x_145_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_13_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_13_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90183040)))]; + tensor x_145_cast_fp16 = conv(dilations = x_145_dilations_0, groups = x_145_groups_0, pad = x_145_pad_0, pad_type = x_145_pad_type_0, strides = x_145_strides_0, weight = encoder_encoders_13_self_attn_fsmn_block_weight_to_fp16, x = input_433_cast_fp16)[name = tensor("x_145_cast_fp16")]; + tensor x_147_perm_0 = const()[name = tensor("x_147_perm_0"), val = tensor([0, 2, 1])]; + tensor x_147_cast_fp16 = transpose(perm = x_147_perm_0, x = x_145_cast_fp16)[name = tensor("transpose_683")]; + tensor input_435_cast_fp16 = add(x = x_147_cast_fp16, y = inputs_29_cast_fp16)[name = tensor("input_435_cast_fp16")]; + tensor fsmn_memory_29_cast_fp16 = mul(x = input_435_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_29_cast_fp16")]; + tensor var_1741_to_fp16 = const()[name = tensor("op_1741_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_59_cast_fp16 = mul(x = var_1716_cast_fp16, y = var_1741_to_fp16)[name = tensor("q_h_59_cast_fp16")]; + tensor scores_57_transpose_x_0 = const()[name = tensor("scores_57_transpose_x_0"), val = tensor(false)]; + tensor scores_57_transpose_y_0 = const()[name = tensor("scores_57_transpose_y_0"), val = tensor(false)]; + tensor transpose_238_perm_0 = const()[name = tensor("transpose_238_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_239_perm_0 = const()[name = tensor("transpose_239_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_239 = transpose(perm = transpose_239_perm_0, x = var_1719_cast_fp16)[name = tensor("transpose_681")]; + tensor transpose_238 = transpose(perm = transpose_238_perm_0, x = q_h_59_cast_fp16)[name = tensor("transpose_682")]; + tensor scores_57_cast_fp16 = matmul(transpose_x = scores_57_transpose_x_0, transpose_y = scores_57_transpose_y_0, x = transpose_238, y = transpose_239)[name = tensor("scores_57_cast_fp16")]; + tensor scores_59_cast_fp16 = select(a = var_48_to_fp16, b = scores_57_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_59_cast_fp16")]; + tensor var_1749_cast_fp16 = softmax(axis = var_61, x = scores_59_cast_fp16)[name = tensor("op_1749_cast_fp16")]; + tensor input_437_cast_fp16 = select(a = var_53_to_fp16, b = var_1749_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_437_cast_fp16")]; + tensor x_151_transpose_x_0 = const()[name = tensor("x_151_transpose_x_0"), val = tensor(false)]; + tensor x_151_transpose_y_0 = const()[name = tensor("x_151_transpose_y_0"), val = tensor(false)]; + tensor value_29_cast_fp16 = transpose(perm = value_29_perm_0, x = var_1722_cast_fp16)[name = tensor("transpose_685")]; + tensor x_151_cast_fp16 = matmul(transpose_x = x_151_transpose_x_0, transpose_y = x_151_transpose_y_0, x = input_437_cast_fp16, y = value_29_cast_fp16)[name = tensor("x_151_cast_fp16")]; + tensor var_1753_perm_0 = const()[name = tensor("op_1753_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1755 = const()[name = tensor("op_1755"), val = tensor([1, -1, 512])]; + tensor var_1753_cast_fp16 = transpose(perm = var_1753_perm_0, x = x_151_cast_fp16)[name = tensor("transpose_680")]; + tensor input_439_cast_fp16 = reshape(shape = var_1755, x = var_1753_cast_fp16)[name = tensor("input_439_cast_fp16")]; + tensor encoder_encoders_13_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_13_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90194368)))]; + tensor encoder_encoders_13_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_13_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90718720)))]; + tensor linear_57_cast_fp16 = linear(bias = encoder_encoders_13_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_13_self_attn_linear_out_weight_to_fp16, x = input_439_cast_fp16)[name = tensor("linear_57_cast_fp16")]; + tensor input_441_cast_fp16 = add(x = linear_57_cast_fp16, y = fsmn_memory_29_cast_fp16)[name = tensor("input_441_cast_fp16")]; + tensor input_443_cast_fp16 = add(x = input_427_cast_fp16, y = input_441_cast_fp16)[name = tensor("input_443_cast_fp16")]; + tensor output_59_axes_0 = const()[name = tensor("output_59_axes_0"), val = tensor([-1])]; + tensor const_94_to_fp16 = const()[name = tensor("const_94_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90719808)))]; + tensor const_95_to_fp16 = const()[name = tensor("const_95_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90720896)))]; + tensor output_59_cast_fp16 = layer_norm(axes = output_59_axes_0, beta = const_95_to_fp16, epsilon = var_46_to_fp16, gamma = const_94_to_fp16, x = input_443_cast_fp16)[name = tensor("output_59_cast_fp16")]; + tensor encoder_encoders_13_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_13_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90721984)))]; + tensor encoder_encoders_13_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_13_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92819200)))]; + tensor linear_58_cast_fp16 = linear(bias = encoder_encoders_13_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_13_feed_forward_w_1_weight_to_fp16, x = output_59_cast_fp16)[name = tensor("linear_58_cast_fp16")]; + tensor input_451_cast_fp16 = relu(x = linear_58_cast_fp16)[name = tensor("input_451_cast_fp16")]; + tensor encoder_encoders_13_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_13_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92823360)))]; + tensor encoder_encoders_13_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_13_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94920576)))]; + tensor linear_59_cast_fp16 = linear(bias = encoder_encoders_13_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_13_feed_forward_w_2_weight_to_fp16, x = input_451_cast_fp16)[name = tensor("linear_59_cast_fp16")]; + tensor input_457_cast_fp16 = add(x = input_443_cast_fp16, y = linear_59_cast_fp16)[name = tensor("input_457_cast_fp16")]; + tensor output_61_axes_0 = const()[name = tensor("output_61_axes_0"), val = tensor([-1])]; + tensor const_96_to_fp16 = const()[name = tensor("const_96_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94921664)))]; + tensor const_97_to_fp16 = const()[name = tensor("const_97_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94922752)))]; + tensor output_61_cast_fp16 = layer_norm(axes = output_61_axes_0, beta = const_97_to_fp16, epsilon = var_46_to_fp16, gamma = const_96_to_fp16, x = input_457_cast_fp16)[name = tensor("output_61_cast_fp16")]; + tensor encoder_encoders_14_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_14_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94923840)))]; + tensor encoder_encoders_14_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_14_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(96496768)))]; + tensor linear_60_cast_fp16 = linear(bias = encoder_encoders_14_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_14_self_attn_linear_q_k_v_weight_to_fp16, x = output_61_cast_fp16)[name = tensor("linear_60_cast_fp16")]; + tensor tile_15 = const()[name = tensor("tile_15"), val = tensor([512, 512, 512])]; + tensor var_1813_axis_0 = const()[name = tensor("op_1813_axis_0"), val = tensor(-1)]; + tensor var_1813_cast_fp16_0, tensor var_1813_cast_fp16_1, tensor var_1813_cast_fp16_2 = split(axis = var_1813_axis_0, split_sizes = tile_15, x = linear_60_cast_fp16)[name = tensor("op_1813_cast_fp16")]; + tensor concat_45x = const()[name = tensor("concat_45x"), val = tensor([1, -1, 4, 128])]; + tensor var_1818_cast_fp16 = reshape(shape = concat_45x, x = var_1813_cast_fp16_0)[name = tensor("op_1818_cast_fp16")]; + tensor concat_46x = const()[name = tensor("concat_46x"), val = tensor([1, -1, 4, 128])]; + tensor var_1821_cast_fp16 = reshape(shape = concat_46x, x = var_1813_cast_fp16_1)[name = tensor("op_1821_cast_fp16")]; + tensor concat_47x = const()[name = tensor("concat_47x"), val = tensor([1, -1, 4, 128])]; + tensor var_1824_cast_fp16 = reshape(shape = concat_47x, x = var_1813_cast_fp16_2)[name = tensor("op_1824_cast_fp16")]; + tensor value_31_perm_0 = const()[name = tensor("value_31_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_31_cast_fp16 = mul(x = var_1813_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_31_cast_fp16")]; + tensor input_461_perm_0 = const()[name = tensor("input_461_perm_0"), val = tensor([0, 2, 1])]; + tensor input_463_pad_0 = const()[name = tensor("input_463_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_463_mode_0 = const()[name = tensor("input_463_mode_0"), val = tensor("constant")]; + tensor const_99_to_fp16 = const()[name = tensor("const_99_to_fp16"), val = tensor(0x0p+0)]; + tensor input_461_cast_fp16 = transpose(perm = input_461_perm_0, x = inputs_31_cast_fp16)[name = tensor("transpose_678")]; + tensor input_463_cast_fp16 = pad(constant_val = const_99_to_fp16, mode = input_463_mode_0, pad = input_463_pad_0, x = input_461_cast_fp16)[name = tensor("input_463_cast_fp16")]; + tensor x_155_pad_type_0 = const()[name = tensor("x_155_pad_type_0"), val = tensor("valid")]; + tensor x_155_groups_0 = const()[name = tensor("x_155_groups_0"), val = tensor(512)]; + tensor x_155_strides_0 = const()[name = tensor("x_155_strides_0"), val = tensor([1])]; + tensor x_155_pad_0 = const()[name = tensor("x_155_pad_0"), val = tensor([0, 0])]; + tensor x_155_dilations_0 = const()[name = tensor("x_155_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_14_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_14_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(96499904)))]; + tensor x_155_cast_fp16 = conv(dilations = x_155_dilations_0, groups = x_155_groups_0, pad = x_155_pad_0, pad_type = x_155_pad_type_0, strides = x_155_strides_0, weight = encoder_encoders_14_self_attn_fsmn_block_weight_to_fp16, x = input_463_cast_fp16)[name = tensor("x_155_cast_fp16")]; + tensor x_157_perm_0 = const()[name = tensor("x_157_perm_0"), val = tensor([0, 2, 1])]; + tensor x_157_cast_fp16 = transpose(perm = x_157_perm_0, x = x_155_cast_fp16)[name = tensor("transpose_677")]; + tensor input_465_cast_fp16 = add(x = x_157_cast_fp16, y = inputs_31_cast_fp16)[name = tensor("input_465_cast_fp16")]; + tensor fsmn_memory_31_cast_fp16 = mul(x = input_465_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_31_cast_fp16")]; + tensor var_1843_to_fp16 = const()[name = tensor("op_1843_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_63_cast_fp16 = mul(x = var_1818_cast_fp16, y = var_1843_to_fp16)[name = tensor("q_h_63_cast_fp16")]; + tensor scores_61_transpose_x_0 = const()[name = tensor("scores_61_transpose_x_0"), val = tensor(false)]; + tensor scores_61_transpose_y_0 = const()[name = tensor("scores_61_transpose_y_0"), val = tensor(false)]; + tensor transpose_240_perm_0 = const()[name = tensor("transpose_240_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_241_perm_0 = const()[name = tensor("transpose_241_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_241 = transpose(perm = transpose_241_perm_0, x = var_1821_cast_fp16)[name = tensor("transpose_675")]; + tensor transpose_240 = transpose(perm = transpose_240_perm_0, x = q_h_63_cast_fp16)[name = tensor("transpose_676")]; + tensor scores_61_cast_fp16 = matmul(transpose_x = scores_61_transpose_x_0, transpose_y = scores_61_transpose_y_0, x = transpose_240, y = transpose_241)[name = tensor("scores_61_cast_fp16")]; + tensor scores_63_cast_fp16 = select(a = var_48_to_fp16, b = scores_61_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_63_cast_fp16")]; + tensor var_1851_cast_fp16 = softmax(axis = var_61, x = scores_63_cast_fp16)[name = tensor("op_1851_cast_fp16")]; + tensor input_467_cast_fp16 = select(a = var_53_to_fp16, b = var_1851_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_467_cast_fp16")]; + tensor x_161_transpose_x_0 = const()[name = tensor("x_161_transpose_x_0"), val = tensor(false)]; + tensor x_161_transpose_y_0 = const()[name = tensor("x_161_transpose_y_0"), val = tensor(false)]; + tensor value_31_cast_fp16 = transpose(perm = value_31_perm_0, x = var_1824_cast_fp16)[name = tensor("transpose_679")]; + tensor x_161_cast_fp16 = matmul(transpose_x = x_161_transpose_x_0, transpose_y = x_161_transpose_y_0, x = input_467_cast_fp16, y = value_31_cast_fp16)[name = tensor("x_161_cast_fp16")]; + tensor var_1855_perm_0 = const()[name = tensor("op_1855_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1857 = const()[name = tensor("op_1857"), val = tensor([1, -1, 512])]; + tensor var_1855_cast_fp16 = transpose(perm = var_1855_perm_0, x = x_161_cast_fp16)[name = tensor("transpose_674")]; + tensor input_469_cast_fp16 = reshape(shape = var_1857, x = var_1855_cast_fp16)[name = tensor("input_469_cast_fp16")]; + tensor encoder_encoders_14_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_14_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(96511232)))]; + tensor encoder_encoders_14_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_14_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97035584)))]; + tensor linear_61_cast_fp16 = linear(bias = encoder_encoders_14_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_14_self_attn_linear_out_weight_to_fp16, x = input_469_cast_fp16)[name = tensor("linear_61_cast_fp16")]; + tensor input_471_cast_fp16 = add(x = linear_61_cast_fp16, y = fsmn_memory_31_cast_fp16)[name = tensor("input_471_cast_fp16")]; + tensor input_473_cast_fp16 = add(x = input_457_cast_fp16, y = input_471_cast_fp16)[name = tensor("input_473_cast_fp16")]; + tensor output_63_axes_0 = const()[name = tensor("output_63_axes_0"), val = tensor([-1])]; + tensor const_100_to_fp16 = const()[name = tensor("const_100_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97036672)))]; + tensor const_101_to_fp16 = const()[name = tensor("const_101_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97037760)))]; + tensor output_63_cast_fp16 = layer_norm(axes = output_63_axes_0, beta = const_101_to_fp16, epsilon = var_46_to_fp16, gamma = const_100_to_fp16, x = input_473_cast_fp16)[name = tensor("output_63_cast_fp16")]; + tensor encoder_encoders_14_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_14_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97038848)))]; + tensor encoder_encoders_14_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_14_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99136064)))]; + tensor linear_62_cast_fp16 = linear(bias = encoder_encoders_14_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_14_feed_forward_w_1_weight_to_fp16, x = output_63_cast_fp16)[name = tensor("linear_62_cast_fp16")]; + tensor input_481_cast_fp16 = relu(x = linear_62_cast_fp16)[name = tensor("input_481_cast_fp16")]; + tensor encoder_encoders_14_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_14_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99140224)))]; + tensor encoder_encoders_14_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_14_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101237440)))]; + tensor linear_63_cast_fp16 = linear(bias = encoder_encoders_14_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_14_feed_forward_w_2_weight_to_fp16, x = input_481_cast_fp16)[name = tensor("linear_63_cast_fp16")]; + tensor input_487_cast_fp16 = add(x = input_473_cast_fp16, y = linear_63_cast_fp16)[name = tensor("input_487_cast_fp16")]; + tensor output_65_axes_0 = const()[name = tensor("output_65_axes_0"), val = tensor([-1])]; + tensor const_102_to_fp16 = const()[name = tensor("const_102_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101238528)))]; + tensor const_103_to_fp16 = const()[name = tensor("const_103_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101239616)))]; + tensor output_65_cast_fp16 = layer_norm(axes = output_65_axes_0, beta = const_103_to_fp16, epsilon = var_46_to_fp16, gamma = const_102_to_fp16, x = input_487_cast_fp16)[name = tensor("output_65_cast_fp16")]; + tensor encoder_encoders_15_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_15_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101240704)))]; + tensor encoder_encoders_15_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_15_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102813632)))]; + tensor linear_64_cast_fp16 = linear(bias = encoder_encoders_15_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_15_self_attn_linear_q_k_v_weight_to_fp16, x = output_65_cast_fp16)[name = tensor("linear_64_cast_fp16")]; + tensor tile_16 = const()[name = tensor("tile_16"), val = tensor([512, 512, 512])]; + tensor var_1915_axis_0 = const()[name = tensor("op_1915_axis_0"), val = tensor(-1)]; + tensor var_1915_cast_fp16_0, tensor var_1915_cast_fp16_1, tensor var_1915_cast_fp16_2 = split(axis = var_1915_axis_0, split_sizes = tile_16, x = linear_64_cast_fp16)[name = tensor("op_1915_cast_fp16")]; + tensor concat_48x = const()[name = tensor("concat_48x"), val = tensor([1, -1, 4, 128])]; + tensor var_1920_cast_fp16 = reshape(shape = concat_48x, x = var_1915_cast_fp16_0)[name = tensor("op_1920_cast_fp16")]; + tensor concat_49x = const()[name = tensor("concat_49x"), val = tensor([1, -1, 4, 128])]; + tensor var_1923_cast_fp16 = reshape(shape = concat_49x, x = var_1915_cast_fp16_1)[name = tensor("op_1923_cast_fp16")]; + tensor concat_50x = const()[name = tensor("concat_50x"), val = tensor([1, -1, 4, 128])]; + tensor var_1926_cast_fp16 = reshape(shape = concat_50x, x = var_1915_cast_fp16_2)[name = tensor("op_1926_cast_fp16")]; + tensor value_33_perm_0 = const()[name = tensor("value_33_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_33_cast_fp16 = mul(x = var_1915_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_33_cast_fp16")]; + tensor input_491_perm_0 = const()[name = tensor("input_491_perm_0"), val = tensor([0, 2, 1])]; + tensor input_493_pad_0 = const()[name = tensor("input_493_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_493_mode_0 = const()[name = tensor("input_493_mode_0"), val = tensor("constant")]; + tensor const_105_to_fp16 = const()[name = tensor("const_105_to_fp16"), val = tensor(0x0p+0)]; + tensor input_491_cast_fp16 = transpose(perm = input_491_perm_0, x = inputs_33_cast_fp16)[name = tensor("transpose_672")]; + tensor input_493_cast_fp16 = pad(constant_val = const_105_to_fp16, mode = input_493_mode_0, pad = input_493_pad_0, x = input_491_cast_fp16)[name = tensor("input_493_cast_fp16")]; + tensor x_165_pad_type_0 = const()[name = tensor("x_165_pad_type_0"), val = tensor("valid")]; + tensor x_165_groups_0 = const()[name = tensor("x_165_groups_0"), val = tensor(512)]; + tensor x_165_strides_0 = const()[name = tensor("x_165_strides_0"), val = tensor([1])]; + tensor x_165_pad_0 = const()[name = tensor("x_165_pad_0"), val = tensor([0, 0])]; + tensor x_165_dilations_0 = const()[name = tensor("x_165_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_15_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_15_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102816768)))]; + tensor x_165_cast_fp16 = conv(dilations = x_165_dilations_0, groups = x_165_groups_0, pad = x_165_pad_0, pad_type = x_165_pad_type_0, strides = x_165_strides_0, weight = encoder_encoders_15_self_attn_fsmn_block_weight_to_fp16, x = input_493_cast_fp16)[name = tensor("x_165_cast_fp16")]; + tensor x_167_perm_0 = const()[name = tensor("x_167_perm_0"), val = tensor([0, 2, 1])]; + tensor x_167_cast_fp16 = transpose(perm = x_167_perm_0, x = x_165_cast_fp16)[name = tensor("transpose_671")]; + tensor input_495_cast_fp16 = add(x = x_167_cast_fp16, y = inputs_33_cast_fp16)[name = tensor("input_495_cast_fp16")]; + tensor fsmn_memory_33_cast_fp16 = mul(x = input_495_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_33_cast_fp16")]; + tensor var_1945_to_fp16 = const()[name = tensor("op_1945_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_67_cast_fp16 = mul(x = var_1920_cast_fp16, y = var_1945_to_fp16)[name = tensor("q_h_67_cast_fp16")]; + tensor scores_65_transpose_x_0 = const()[name = tensor("scores_65_transpose_x_0"), val = tensor(false)]; + tensor scores_65_transpose_y_0 = const()[name = tensor("scores_65_transpose_y_0"), val = tensor(false)]; + tensor transpose_242_perm_0 = const()[name = tensor("transpose_242_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_243_perm_0 = const()[name = tensor("transpose_243_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_243 = transpose(perm = transpose_243_perm_0, x = var_1923_cast_fp16)[name = tensor("transpose_669")]; + tensor transpose_242 = transpose(perm = transpose_242_perm_0, x = q_h_67_cast_fp16)[name = tensor("transpose_670")]; + tensor scores_65_cast_fp16 = matmul(transpose_x = scores_65_transpose_x_0, transpose_y = scores_65_transpose_y_0, x = transpose_242, y = transpose_243)[name = tensor("scores_65_cast_fp16")]; + tensor scores_67_cast_fp16 = select(a = var_48_to_fp16, b = scores_65_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_67_cast_fp16")]; + tensor var_1953_cast_fp16 = softmax(axis = var_61, x = scores_67_cast_fp16)[name = tensor("op_1953_cast_fp16")]; + tensor input_497_cast_fp16 = select(a = var_53_to_fp16, b = var_1953_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_497_cast_fp16")]; + tensor x_171_transpose_x_0 = const()[name = tensor("x_171_transpose_x_0"), val = tensor(false)]; + tensor x_171_transpose_y_0 = const()[name = tensor("x_171_transpose_y_0"), val = tensor(false)]; + tensor value_33_cast_fp16 = transpose(perm = value_33_perm_0, x = var_1926_cast_fp16)[name = tensor("transpose_673")]; + tensor x_171_cast_fp16 = matmul(transpose_x = x_171_transpose_x_0, transpose_y = x_171_transpose_y_0, x = input_497_cast_fp16, y = value_33_cast_fp16)[name = tensor("x_171_cast_fp16")]; + tensor var_1957_perm_0 = const()[name = tensor("op_1957_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1959 = const()[name = tensor("op_1959"), val = tensor([1, -1, 512])]; + tensor var_1957_cast_fp16 = transpose(perm = var_1957_perm_0, x = x_171_cast_fp16)[name = tensor("transpose_668")]; + tensor input_499_cast_fp16 = reshape(shape = var_1959, x = var_1957_cast_fp16)[name = tensor("input_499_cast_fp16")]; + tensor encoder_encoders_15_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_15_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102828096)))]; + tensor encoder_encoders_15_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_15_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103352448)))]; + tensor linear_65_cast_fp16 = linear(bias = encoder_encoders_15_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_15_self_attn_linear_out_weight_to_fp16, x = input_499_cast_fp16)[name = tensor("linear_65_cast_fp16")]; + tensor input_501_cast_fp16 = add(x = linear_65_cast_fp16, y = fsmn_memory_33_cast_fp16)[name = tensor("input_501_cast_fp16")]; + tensor input_503_cast_fp16 = add(x = input_487_cast_fp16, y = input_501_cast_fp16)[name = tensor("input_503_cast_fp16")]; + tensor output_67_axes_0 = const()[name = tensor("output_67_axes_0"), val = tensor([-1])]; + tensor const_106_to_fp16 = const()[name = tensor("const_106_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103353536)))]; + tensor const_107_to_fp16 = const()[name = tensor("const_107_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103354624)))]; + tensor output_67_cast_fp16 = layer_norm(axes = output_67_axes_0, beta = const_107_to_fp16, epsilon = var_46_to_fp16, gamma = const_106_to_fp16, x = input_503_cast_fp16)[name = tensor("output_67_cast_fp16")]; + tensor encoder_encoders_15_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_15_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103355712)))]; + tensor encoder_encoders_15_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_15_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(105452928)))]; + tensor linear_66_cast_fp16 = linear(bias = encoder_encoders_15_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_15_feed_forward_w_1_weight_to_fp16, x = output_67_cast_fp16)[name = tensor("linear_66_cast_fp16")]; + tensor input_511_cast_fp16 = relu(x = linear_66_cast_fp16)[name = tensor("input_511_cast_fp16")]; + tensor encoder_encoders_15_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_15_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(105457088)))]; + tensor encoder_encoders_15_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_15_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107554304)))]; + tensor linear_67_cast_fp16 = linear(bias = encoder_encoders_15_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_15_feed_forward_w_2_weight_to_fp16, x = input_511_cast_fp16)[name = tensor("linear_67_cast_fp16")]; + tensor input_517_cast_fp16 = add(x = input_503_cast_fp16, y = linear_67_cast_fp16)[name = tensor("input_517_cast_fp16")]; + tensor output_69_axes_0 = const()[name = tensor("output_69_axes_0"), val = tensor([-1])]; + tensor const_108_to_fp16 = const()[name = tensor("const_108_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107555392)))]; + tensor const_109_to_fp16 = const()[name = tensor("const_109_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107556480)))]; + tensor output_69_cast_fp16 = layer_norm(axes = output_69_axes_0, beta = const_109_to_fp16, epsilon = var_46_to_fp16, gamma = const_108_to_fp16, x = input_517_cast_fp16)[name = tensor("output_69_cast_fp16")]; + tensor encoder_encoders_16_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_16_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107557568)))]; + tensor encoder_encoders_16_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_16_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109130496)))]; + tensor linear_68_cast_fp16 = linear(bias = encoder_encoders_16_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_16_self_attn_linear_q_k_v_weight_to_fp16, x = output_69_cast_fp16)[name = tensor("linear_68_cast_fp16")]; + tensor tile_17 = const()[name = tensor("tile_17"), val = tensor([512, 512, 512])]; + tensor var_2017_axis_0 = const()[name = tensor("op_2017_axis_0"), val = tensor(-1)]; + tensor var_2017_cast_fp16_0, tensor var_2017_cast_fp16_1, tensor var_2017_cast_fp16_2 = split(axis = var_2017_axis_0, split_sizes = tile_17, x = linear_68_cast_fp16)[name = tensor("op_2017_cast_fp16")]; + tensor concat_51x = const()[name = tensor("concat_51x"), val = tensor([1, -1, 4, 128])]; + tensor var_2022_cast_fp16 = reshape(shape = concat_51x, x = var_2017_cast_fp16_0)[name = tensor("op_2022_cast_fp16")]; + tensor concat_52x = const()[name = tensor("concat_52x"), val = tensor([1, -1, 4, 128])]; + tensor var_2025_cast_fp16 = reshape(shape = concat_52x, x = var_2017_cast_fp16_1)[name = tensor("op_2025_cast_fp16")]; + tensor concat_53x = const()[name = tensor("concat_53x"), val = tensor([1, -1, 4, 128])]; + tensor var_2028_cast_fp16 = reshape(shape = concat_53x, x = var_2017_cast_fp16_2)[name = tensor("op_2028_cast_fp16")]; + tensor value_35_perm_0 = const()[name = tensor("value_35_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_35_cast_fp16 = mul(x = var_2017_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_35_cast_fp16")]; + tensor input_521_perm_0 = const()[name = tensor("input_521_perm_0"), val = tensor([0, 2, 1])]; + tensor input_523_pad_0 = const()[name = tensor("input_523_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_523_mode_0 = const()[name = tensor("input_523_mode_0"), val = tensor("constant")]; + tensor const_111_to_fp16 = const()[name = tensor("const_111_to_fp16"), val = tensor(0x0p+0)]; + tensor input_521_cast_fp16 = transpose(perm = input_521_perm_0, x = inputs_35_cast_fp16)[name = tensor("transpose_666")]; + tensor input_523_cast_fp16 = pad(constant_val = const_111_to_fp16, mode = input_523_mode_0, pad = input_523_pad_0, x = input_521_cast_fp16)[name = tensor("input_523_cast_fp16")]; + tensor x_175_pad_type_0 = const()[name = tensor("x_175_pad_type_0"), val = tensor("valid")]; + tensor x_175_groups_0 = const()[name = tensor("x_175_groups_0"), val = tensor(512)]; + tensor x_175_strides_0 = const()[name = tensor("x_175_strides_0"), val = tensor([1])]; + tensor x_175_pad_0 = const()[name = tensor("x_175_pad_0"), val = tensor([0, 0])]; + tensor x_175_dilations_0 = const()[name = tensor("x_175_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_16_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_16_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109133632)))]; + tensor x_175_cast_fp16 = conv(dilations = x_175_dilations_0, groups = x_175_groups_0, pad = x_175_pad_0, pad_type = x_175_pad_type_0, strides = x_175_strides_0, weight = encoder_encoders_16_self_attn_fsmn_block_weight_to_fp16, x = input_523_cast_fp16)[name = tensor("x_175_cast_fp16")]; + tensor x_177_perm_0 = const()[name = tensor("x_177_perm_0"), val = tensor([0, 2, 1])]; + tensor x_177_cast_fp16 = transpose(perm = x_177_perm_0, x = x_175_cast_fp16)[name = tensor("transpose_665")]; + tensor input_525_cast_fp16 = add(x = x_177_cast_fp16, y = inputs_35_cast_fp16)[name = tensor("input_525_cast_fp16")]; + tensor fsmn_memory_35_cast_fp16 = mul(x = input_525_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_35_cast_fp16")]; + tensor var_2047_to_fp16 = const()[name = tensor("op_2047_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_71_cast_fp16 = mul(x = var_2022_cast_fp16, y = var_2047_to_fp16)[name = tensor("q_h_71_cast_fp16")]; + tensor scores_69_transpose_x_0 = const()[name = tensor("scores_69_transpose_x_0"), val = tensor(false)]; + tensor scores_69_transpose_y_0 = const()[name = tensor("scores_69_transpose_y_0"), val = tensor(false)]; + tensor transpose_244_perm_0 = const()[name = tensor("transpose_244_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_245_perm_0 = const()[name = tensor("transpose_245_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_245 = transpose(perm = transpose_245_perm_0, x = var_2025_cast_fp16)[name = tensor("transpose_663")]; + tensor transpose_244 = transpose(perm = transpose_244_perm_0, x = q_h_71_cast_fp16)[name = tensor("transpose_664")]; + tensor scores_69_cast_fp16 = matmul(transpose_x = scores_69_transpose_x_0, transpose_y = scores_69_transpose_y_0, x = transpose_244, y = transpose_245)[name = tensor("scores_69_cast_fp16")]; + tensor scores_71_cast_fp16 = select(a = var_48_to_fp16, b = scores_69_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_71_cast_fp16")]; + tensor var_2055_cast_fp16 = softmax(axis = var_61, x = scores_71_cast_fp16)[name = tensor("op_2055_cast_fp16")]; + tensor input_527_cast_fp16 = select(a = var_53_to_fp16, b = var_2055_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_527_cast_fp16")]; + tensor x_181_transpose_x_0 = const()[name = tensor("x_181_transpose_x_0"), val = tensor(false)]; + tensor x_181_transpose_y_0 = const()[name = tensor("x_181_transpose_y_0"), val = tensor(false)]; + tensor value_35_cast_fp16 = transpose(perm = value_35_perm_0, x = var_2028_cast_fp16)[name = tensor("transpose_667")]; + tensor x_181_cast_fp16 = matmul(transpose_x = x_181_transpose_x_0, transpose_y = x_181_transpose_y_0, x = input_527_cast_fp16, y = value_35_cast_fp16)[name = tensor("x_181_cast_fp16")]; + tensor var_2059_perm_0 = const()[name = tensor("op_2059_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2061 = const()[name = tensor("op_2061"), val = tensor([1, -1, 512])]; + tensor var_2059_cast_fp16 = transpose(perm = var_2059_perm_0, x = x_181_cast_fp16)[name = tensor("transpose_662")]; + tensor input_529_cast_fp16 = reshape(shape = var_2061, x = var_2059_cast_fp16)[name = tensor("input_529_cast_fp16")]; + tensor encoder_encoders_16_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_16_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109144960)))]; + tensor encoder_encoders_16_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_16_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109669312)))]; + tensor linear_69_cast_fp16 = linear(bias = encoder_encoders_16_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_16_self_attn_linear_out_weight_to_fp16, x = input_529_cast_fp16)[name = tensor("linear_69_cast_fp16")]; + tensor input_531_cast_fp16 = add(x = linear_69_cast_fp16, y = fsmn_memory_35_cast_fp16)[name = tensor("input_531_cast_fp16")]; + tensor input_533_cast_fp16 = add(x = input_517_cast_fp16, y = input_531_cast_fp16)[name = tensor("input_533_cast_fp16")]; + tensor output_71_axes_0 = const()[name = tensor("output_71_axes_0"), val = tensor([-1])]; + tensor const_112_to_fp16 = const()[name = tensor("const_112_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109670400)))]; + tensor const_113_to_fp16 = const()[name = tensor("const_113_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109671488)))]; + tensor output_71_cast_fp16 = layer_norm(axes = output_71_axes_0, beta = const_113_to_fp16, epsilon = var_46_to_fp16, gamma = const_112_to_fp16, x = input_533_cast_fp16)[name = tensor("output_71_cast_fp16")]; + tensor encoder_encoders_16_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_16_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109672576)))]; + tensor encoder_encoders_16_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_16_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111769792)))]; + tensor linear_70_cast_fp16 = linear(bias = encoder_encoders_16_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_16_feed_forward_w_1_weight_to_fp16, x = output_71_cast_fp16)[name = tensor("linear_70_cast_fp16")]; + tensor input_541_cast_fp16 = relu(x = linear_70_cast_fp16)[name = tensor("input_541_cast_fp16")]; + tensor encoder_encoders_16_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_16_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111773952)))]; + tensor encoder_encoders_16_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_16_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113871168)))]; + tensor linear_71_cast_fp16 = linear(bias = encoder_encoders_16_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_16_feed_forward_w_2_weight_to_fp16, x = input_541_cast_fp16)[name = tensor("linear_71_cast_fp16")]; + tensor input_547_cast_fp16 = add(x = input_533_cast_fp16, y = linear_71_cast_fp16)[name = tensor("input_547_cast_fp16")]; + tensor output_73_axes_0 = const()[name = tensor("output_73_axes_0"), val = tensor([-1])]; + tensor const_114_to_fp16 = const()[name = tensor("const_114_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113872256)))]; + tensor const_115_to_fp16 = const()[name = tensor("const_115_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113873344)))]; + tensor output_73_cast_fp16 = layer_norm(axes = output_73_axes_0, beta = const_115_to_fp16, epsilon = var_46_to_fp16, gamma = const_114_to_fp16, x = input_547_cast_fp16)[name = tensor("output_73_cast_fp16")]; + tensor encoder_encoders_17_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_17_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113874432)))]; + tensor encoder_encoders_17_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_17_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115447360)))]; + tensor linear_72_cast_fp16 = linear(bias = encoder_encoders_17_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_17_self_attn_linear_q_k_v_weight_to_fp16, x = output_73_cast_fp16)[name = tensor("linear_72_cast_fp16")]; + tensor tile_18 = const()[name = tensor("tile_18"), val = tensor([512, 512, 512])]; + tensor var_2119_axis_0 = const()[name = tensor("op_2119_axis_0"), val = tensor(-1)]; + tensor var_2119_cast_fp16_0, tensor var_2119_cast_fp16_1, tensor var_2119_cast_fp16_2 = split(axis = var_2119_axis_0, split_sizes = tile_18, x = linear_72_cast_fp16)[name = tensor("op_2119_cast_fp16")]; + tensor concat_54x = const()[name = tensor("concat_54x"), val = tensor([1, -1, 4, 128])]; + tensor var_2124_cast_fp16 = reshape(shape = concat_54x, x = var_2119_cast_fp16_0)[name = tensor("op_2124_cast_fp16")]; + tensor concat_55x = const()[name = tensor("concat_55x"), val = tensor([1, -1, 4, 128])]; + tensor var_2127_cast_fp16 = reshape(shape = concat_55x, x = var_2119_cast_fp16_1)[name = tensor("op_2127_cast_fp16")]; + tensor concat_56x = const()[name = tensor("concat_56x"), val = tensor([1, -1, 4, 128])]; + tensor var_2130_cast_fp16 = reshape(shape = concat_56x, x = var_2119_cast_fp16_2)[name = tensor("op_2130_cast_fp16")]; + tensor value_37_perm_0 = const()[name = tensor("value_37_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_37_cast_fp16 = mul(x = var_2119_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_37_cast_fp16")]; + tensor input_551_perm_0 = const()[name = tensor("input_551_perm_0"), val = tensor([0, 2, 1])]; + tensor input_553_pad_0 = const()[name = tensor("input_553_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_553_mode_0 = const()[name = tensor("input_553_mode_0"), val = tensor("constant")]; + tensor const_117_to_fp16 = const()[name = tensor("const_117_to_fp16"), val = tensor(0x0p+0)]; + tensor input_551_cast_fp16 = transpose(perm = input_551_perm_0, x = inputs_37_cast_fp16)[name = tensor("transpose_660")]; + tensor input_553_cast_fp16 = pad(constant_val = const_117_to_fp16, mode = input_553_mode_0, pad = input_553_pad_0, x = input_551_cast_fp16)[name = tensor("input_553_cast_fp16")]; + tensor x_185_pad_type_0 = const()[name = tensor("x_185_pad_type_0"), val = tensor("valid")]; + tensor x_185_groups_0 = const()[name = tensor("x_185_groups_0"), val = tensor(512)]; + tensor x_185_strides_0 = const()[name = tensor("x_185_strides_0"), val = tensor([1])]; + tensor x_185_pad_0 = const()[name = tensor("x_185_pad_0"), val = tensor([0, 0])]; + tensor x_185_dilations_0 = const()[name = tensor("x_185_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_17_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_17_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115450496)))]; + tensor x_185_cast_fp16 = conv(dilations = x_185_dilations_0, groups = x_185_groups_0, pad = x_185_pad_0, pad_type = x_185_pad_type_0, strides = x_185_strides_0, weight = encoder_encoders_17_self_attn_fsmn_block_weight_to_fp16, x = input_553_cast_fp16)[name = tensor("x_185_cast_fp16")]; + tensor x_187_perm_0 = const()[name = tensor("x_187_perm_0"), val = tensor([0, 2, 1])]; + tensor x_187_cast_fp16 = transpose(perm = x_187_perm_0, x = x_185_cast_fp16)[name = tensor("transpose_659")]; + tensor input_555_cast_fp16 = add(x = x_187_cast_fp16, y = inputs_37_cast_fp16)[name = tensor("input_555_cast_fp16")]; + tensor fsmn_memory_37_cast_fp16 = mul(x = input_555_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_37_cast_fp16")]; + tensor var_2149_to_fp16 = const()[name = tensor("op_2149_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_75_cast_fp16 = mul(x = var_2124_cast_fp16, y = var_2149_to_fp16)[name = tensor("q_h_75_cast_fp16")]; + tensor scores_73_transpose_x_0 = const()[name = tensor("scores_73_transpose_x_0"), val = tensor(false)]; + tensor scores_73_transpose_y_0 = const()[name = tensor("scores_73_transpose_y_0"), val = tensor(false)]; + tensor transpose_246_perm_0 = const()[name = tensor("transpose_246_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_247_perm_0 = const()[name = tensor("transpose_247_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_247 = transpose(perm = transpose_247_perm_0, x = var_2127_cast_fp16)[name = tensor("transpose_657")]; + tensor transpose_246 = transpose(perm = transpose_246_perm_0, x = q_h_75_cast_fp16)[name = tensor("transpose_658")]; + tensor scores_73_cast_fp16 = matmul(transpose_x = scores_73_transpose_x_0, transpose_y = scores_73_transpose_y_0, x = transpose_246, y = transpose_247)[name = tensor("scores_73_cast_fp16")]; + tensor scores_75_cast_fp16 = select(a = var_48_to_fp16, b = scores_73_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_75_cast_fp16")]; + tensor var_2157_cast_fp16 = softmax(axis = var_61, x = scores_75_cast_fp16)[name = tensor("op_2157_cast_fp16")]; + tensor input_557_cast_fp16 = select(a = var_53_to_fp16, b = var_2157_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_557_cast_fp16")]; + tensor x_191_transpose_x_0 = const()[name = tensor("x_191_transpose_x_0"), val = tensor(false)]; + tensor x_191_transpose_y_0 = const()[name = tensor("x_191_transpose_y_0"), val = tensor(false)]; + tensor value_37_cast_fp16 = transpose(perm = value_37_perm_0, x = var_2130_cast_fp16)[name = tensor("transpose_661")]; + tensor x_191_cast_fp16 = matmul(transpose_x = x_191_transpose_x_0, transpose_y = x_191_transpose_y_0, x = input_557_cast_fp16, y = value_37_cast_fp16)[name = tensor("x_191_cast_fp16")]; + tensor var_2161_perm_0 = const()[name = tensor("op_2161_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2163 = const()[name = tensor("op_2163"), val = tensor([1, -1, 512])]; + tensor var_2161_cast_fp16 = transpose(perm = var_2161_perm_0, x = x_191_cast_fp16)[name = tensor("transpose_656")]; + tensor input_559_cast_fp16 = reshape(shape = var_2163, x = var_2161_cast_fp16)[name = tensor("input_559_cast_fp16")]; + tensor encoder_encoders_17_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_17_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115461824)))]; + tensor encoder_encoders_17_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_17_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115986176)))]; + tensor linear_73_cast_fp16 = linear(bias = encoder_encoders_17_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_17_self_attn_linear_out_weight_to_fp16, x = input_559_cast_fp16)[name = tensor("linear_73_cast_fp16")]; + tensor input_561_cast_fp16 = add(x = linear_73_cast_fp16, y = fsmn_memory_37_cast_fp16)[name = tensor("input_561_cast_fp16")]; + tensor input_563_cast_fp16 = add(x = input_547_cast_fp16, y = input_561_cast_fp16)[name = tensor("input_563_cast_fp16")]; + tensor output_75_axes_0 = const()[name = tensor("output_75_axes_0"), val = tensor([-1])]; + tensor const_118_to_fp16 = const()[name = tensor("const_118_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115987264)))]; + tensor const_119_to_fp16 = const()[name = tensor("const_119_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115988352)))]; + tensor output_75_cast_fp16 = layer_norm(axes = output_75_axes_0, beta = const_119_to_fp16, epsilon = var_46_to_fp16, gamma = const_118_to_fp16, x = input_563_cast_fp16)[name = tensor("output_75_cast_fp16")]; + tensor encoder_encoders_17_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_17_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115989440)))]; + tensor encoder_encoders_17_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_17_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118086656)))]; + tensor linear_74_cast_fp16 = linear(bias = encoder_encoders_17_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_17_feed_forward_w_1_weight_to_fp16, x = output_75_cast_fp16)[name = tensor("linear_74_cast_fp16")]; + tensor input_571_cast_fp16 = relu(x = linear_74_cast_fp16)[name = tensor("input_571_cast_fp16")]; + tensor encoder_encoders_17_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_17_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118090816)))]; + tensor encoder_encoders_17_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_17_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120188032)))]; + tensor linear_75_cast_fp16 = linear(bias = encoder_encoders_17_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_17_feed_forward_w_2_weight_to_fp16, x = input_571_cast_fp16)[name = tensor("linear_75_cast_fp16")]; + tensor input_577_cast_fp16 = add(x = input_563_cast_fp16, y = linear_75_cast_fp16)[name = tensor("input_577_cast_fp16")]; + tensor output_77_axes_0 = const()[name = tensor("output_77_axes_0"), val = tensor([-1])]; + tensor const_120_to_fp16 = const()[name = tensor("const_120_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120189120)))]; + tensor const_121_to_fp16 = const()[name = tensor("const_121_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120190208)))]; + tensor output_77_cast_fp16 = layer_norm(axes = output_77_axes_0, beta = const_121_to_fp16, epsilon = var_46_to_fp16, gamma = const_120_to_fp16, x = input_577_cast_fp16)[name = tensor("output_77_cast_fp16")]; + tensor encoder_encoders_18_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_18_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120191296)))]; + tensor encoder_encoders_18_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_18_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121764224)))]; + tensor linear_76_cast_fp16 = linear(bias = encoder_encoders_18_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_18_self_attn_linear_q_k_v_weight_to_fp16, x = output_77_cast_fp16)[name = tensor("linear_76_cast_fp16")]; + tensor tile_19 = const()[name = tensor("tile_19"), val = tensor([512, 512, 512])]; + tensor var_2221_axis_0 = const()[name = tensor("op_2221_axis_0"), val = tensor(-1)]; + tensor var_2221_cast_fp16_0, tensor var_2221_cast_fp16_1, tensor var_2221_cast_fp16_2 = split(axis = var_2221_axis_0, split_sizes = tile_19, x = linear_76_cast_fp16)[name = tensor("op_2221_cast_fp16")]; + tensor concat_57x = const()[name = tensor("concat_57x"), val = tensor([1, -1, 4, 128])]; + tensor var_2226_cast_fp16 = reshape(shape = concat_57x, x = var_2221_cast_fp16_0)[name = tensor("op_2226_cast_fp16")]; + tensor concat_58x = const()[name = tensor("concat_58x"), val = tensor([1, -1, 4, 128])]; + tensor var_2229_cast_fp16 = reshape(shape = concat_58x, x = var_2221_cast_fp16_1)[name = tensor("op_2229_cast_fp16")]; + tensor concat_59x = const()[name = tensor("concat_59x"), val = tensor([1, -1, 4, 128])]; + tensor var_2232_cast_fp16 = reshape(shape = concat_59x, x = var_2221_cast_fp16_2)[name = tensor("op_2232_cast_fp16")]; + tensor value_39_perm_0 = const()[name = tensor("value_39_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_39_cast_fp16 = mul(x = var_2221_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_39_cast_fp16")]; + tensor input_581_perm_0 = const()[name = tensor("input_581_perm_0"), val = tensor([0, 2, 1])]; + tensor input_583_pad_0 = const()[name = tensor("input_583_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_583_mode_0 = const()[name = tensor("input_583_mode_0"), val = tensor("constant")]; + tensor const_123_to_fp16 = const()[name = tensor("const_123_to_fp16"), val = tensor(0x0p+0)]; + tensor input_581_cast_fp16 = transpose(perm = input_581_perm_0, x = inputs_39_cast_fp16)[name = tensor("transpose_654")]; + tensor input_583_cast_fp16 = pad(constant_val = const_123_to_fp16, mode = input_583_mode_0, pad = input_583_pad_0, x = input_581_cast_fp16)[name = tensor("input_583_cast_fp16")]; + tensor x_195_pad_type_0 = const()[name = tensor("x_195_pad_type_0"), val = tensor("valid")]; + tensor x_195_groups_0 = const()[name = tensor("x_195_groups_0"), val = tensor(512)]; + tensor x_195_strides_0 = const()[name = tensor("x_195_strides_0"), val = tensor([1])]; + tensor x_195_pad_0 = const()[name = tensor("x_195_pad_0"), val = tensor([0, 0])]; + tensor x_195_dilations_0 = const()[name = tensor("x_195_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_18_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_18_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121767360)))]; + tensor x_195_cast_fp16 = conv(dilations = x_195_dilations_0, groups = x_195_groups_0, pad = x_195_pad_0, pad_type = x_195_pad_type_0, strides = x_195_strides_0, weight = encoder_encoders_18_self_attn_fsmn_block_weight_to_fp16, x = input_583_cast_fp16)[name = tensor("x_195_cast_fp16")]; + tensor x_197_perm_0 = const()[name = tensor("x_197_perm_0"), val = tensor([0, 2, 1])]; + tensor x_197_cast_fp16 = transpose(perm = x_197_perm_0, x = x_195_cast_fp16)[name = tensor("transpose_653")]; + tensor input_585_cast_fp16 = add(x = x_197_cast_fp16, y = inputs_39_cast_fp16)[name = tensor("input_585_cast_fp16")]; + tensor fsmn_memory_39_cast_fp16 = mul(x = input_585_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_39_cast_fp16")]; + tensor var_2251_to_fp16 = const()[name = tensor("op_2251_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_79_cast_fp16 = mul(x = var_2226_cast_fp16, y = var_2251_to_fp16)[name = tensor("q_h_79_cast_fp16")]; + tensor scores_77_transpose_x_0 = const()[name = tensor("scores_77_transpose_x_0"), val = tensor(false)]; + tensor scores_77_transpose_y_0 = const()[name = tensor("scores_77_transpose_y_0"), val = tensor(false)]; + tensor transpose_248_perm_0 = const()[name = tensor("transpose_248_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_249_perm_0 = const()[name = tensor("transpose_249_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_249 = transpose(perm = transpose_249_perm_0, x = var_2229_cast_fp16)[name = tensor("transpose_651")]; + tensor transpose_248 = transpose(perm = transpose_248_perm_0, x = q_h_79_cast_fp16)[name = tensor("transpose_652")]; + tensor scores_77_cast_fp16 = matmul(transpose_x = scores_77_transpose_x_0, transpose_y = scores_77_transpose_y_0, x = transpose_248, y = transpose_249)[name = tensor("scores_77_cast_fp16")]; + tensor scores_79_cast_fp16 = select(a = var_48_to_fp16, b = scores_77_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_79_cast_fp16")]; + tensor var_2259_cast_fp16 = softmax(axis = var_61, x = scores_79_cast_fp16)[name = tensor("op_2259_cast_fp16")]; + tensor input_587_cast_fp16 = select(a = var_53_to_fp16, b = var_2259_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_587_cast_fp16")]; + tensor x_201_transpose_x_0 = const()[name = tensor("x_201_transpose_x_0"), val = tensor(false)]; + tensor x_201_transpose_y_0 = const()[name = tensor("x_201_transpose_y_0"), val = tensor(false)]; + tensor value_39_cast_fp16 = transpose(perm = value_39_perm_0, x = var_2232_cast_fp16)[name = tensor("transpose_655")]; + tensor x_201_cast_fp16 = matmul(transpose_x = x_201_transpose_x_0, transpose_y = x_201_transpose_y_0, x = input_587_cast_fp16, y = value_39_cast_fp16)[name = tensor("x_201_cast_fp16")]; + tensor var_2263_perm_0 = const()[name = tensor("op_2263_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2265 = const()[name = tensor("op_2265"), val = tensor([1, -1, 512])]; + tensor var_2263_cast_fp16 = transpose(perm = var_2263_perm_0, x = x_201_cast_fp16)[name = tensor("transpose_650")]; + tensor input_589_cast_fp16 = reshape(shape = var_2265, x = var_2263_cast_fp16)[name = tensor("input_589_cast_fp16")]; + tensor encoder_encoders_18_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_18_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121778688)))]; + tensor encoder_encoders_18_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_18_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122303040)))]; + tensor linear_77_cast_fp16 = linear(bias = encoder_encoders_18_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_18_self_attn_linear_out_weight_to_fp16, x = input_589_cast_fp16)[name = tensor("linear_77_cast_fp16")]; + tensor input_591_cast_fp16 = add(x = linear_77_cast_fp16, y = fsmn_memory_39_cast_fp16)[name = tensor("input_591_cast_fp16")]; + tensor input_593_cast_fp16 = add(x = input_577_cast_fp16, y = input_591_cast_fp16)[name = tensor("input_593_cast_fp16")]; + tensor output_79_axes_0 = const()[name = tensor("output_79_axes_0"), val = tensor([-1])]; + tensor const_124_to_fp16 = const()[name = tensor("const_124_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122304128)))]; + tensor const_125_to_fp16 = const()[name = tensor("const_125_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122305216)))]; + tensor output_79_cast_fp16 = layer_norm(axes = output_79_axes_0, beta = const_125_to_fp16, epsilon = var_46_to_fp16, gamma = const_124_to_fp16, x = input_593_cast_fp16)[name = tensor("output_79_cast_fp16")]; + tensor encoder_encoders_18_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_18_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122306304)))]; + tensor encoder_encoders_18_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_18_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124403520)))]; + tensor linear_78_cast_fp16 = linear(bias = encoder_encoders_18_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_18_feed_forward_w_1_weight_to_fp16, x = output_79_cast_fp16)[name = tensor("linear_78_cast_fp16")]; + tensor input_601_cast_fp16 = relu(x = linear_78_cast_fp16)[name = tensor("input_601_cast_fp16")]; + tensor encoder_encoders_18_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_18_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124407680)))]; + tensor encoder_encoders_18_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_18_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126504896)))]; + tensor linear_79_cast_fp16 = linear(bias = encoder_encoders_18_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_18_feed_forward_w_2_weight_to_fp16, x = input_601_cast_fp16)[name = tensor("linear_79_cast_fp16")]; + tensor input_607_cast_fp16 = add(x = input_593_cast_fp16, y = linear_79_cast_fp16)[name = tensor("input_607_cast_fp16")]; + tensor output_81_axes_0 = const()[name = tensor("output_81_axes_0"), val = tensor([-1])]; + tensor const_126_to_fp16 = const()[name = tensor("const_126_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126505984)))]; + tensor const_127_to_fp16 = const()[name = tensor("const_127_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126507072)))]; + tensor output_81_cast_fp16 = layer_norm(axes = output_81_axes_0, beta = const_127_to_fp16, epsilon = var_46_to_fp16, gamma = const_126_to_fp16, x = input_607_cast_fp16)[name = tensor("output_81_cast_fp16")]; + tensor encoder_encoders_19_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_19_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126508160)))]; + tensor encoder_encoders_19_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_19_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128081088)))]; + tensor linear_80_cast_fp16 = linear(bias = encoder_encoders_19_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_19_self_attn_linear_q_k_v_weight_to_fp16, x = output_81_cast_fp16)[name = tensor("linear_80_cast_fp16")]; + tensor tile_20 = const()[name = tensor("tile_20"), val = tensor([512, 512, 512])]; + tensor var_2323_axis_0 = const()[name = tensor("op_2323_axis_0"), val = tensor(-1)]; + tensor var_2323_cast_fp16_0, tensor var_2323_cast_fp16_1, tensor var_2323_cast_fp16_2 = split(axis = var_2323_axis_0, split_sizes = tile_20, x = linear_80_cast_fp16)[name = tensor("op_2323_cast_fp16")]; + tensor concat_60x = const()[name = tensor("concat_60x"), val = tensor([1, -1, 4, 128])]; + tensor var_2328_cast_fp16 = reshape(shape = concat_60x, x = var_2323_cast_fp16_0)[name = tensor("op_2328_cast_fp16")]; + tensor concat_61x = const()[name = tensor("concat_61x"), val = tensor([1, -1, 4, 128])]; + tensor var_2331_cast_fp16 = reshape(shape = concat_61x, x = var_2323_cast_fp16_1)[name = tensor("op_2331_cast_fp16")]; + tensor concat_62x = const()[name = tensor("concat_62x"), val = tensor([1, -1, 4, 128])]; + tensor var_2334_cast_fp16 = reshape(shape = concat_62x, x = var_2323_cast_fp16_2)[name = tensor("op_2334_cast_fp16")]; + tensor value_41_perm_0 = const()[name = tensor("value_41_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_41_cast_fp16 = mul(x = var_2323_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_41_cast_fp16")]; + tensor input_611_perm_0 = const()[name = tensor("input_611_perm_0"), val = tensor([0, 2, 1])]; + tensor input_613_pad_0 = const()[name = tensor("input_613_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_613_mode_0 = const()[name = tensor("input_613_mode_0"), val = tensor("constant")]; + tensor const_129_to_fp16 = const()[name = tensor("const_129_to_fp16"), val = tensor(0x0p+0)]; + tensor input_611_cast_fp16 = transpose(perm = input_611_perm_0, x = inputs_41_cast_fp16)[name = tensor("transpose_648")]; + tensor input_613_cast_fp16 = pad(constant_val = const_129_to_fp16, mode = input_613_mode_0, pad = input_613_pad_0, x = input_611_cast_fp16)[name = tensor("input_613_cast_fp16")]; + tensor x_205_pad_type_0 = const()[name = tensor("x_205_pad_type_0"), val = tensor("valid")]; + tensor x_205_groups_0 = const()[name = tensor("x_205_groups_0"), val = tensor(512)]; + tensor x_205_strides_0 = const()[name = tensor("x_205_strides_0"), val = tensor([1])]; + tensor x_205_pad_0 = const()[name = tensor("x_205_pad_0"), val = tensor([0, 0])]; + tensor x_205_dilations_0 = const()[name = tensor("x_205_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_19_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_19_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128084224)))]; + tensor x_205_cast_fp16 = conv(dilations = x_205_dilations_0, groups = x_205_groups_0, pad = x_205_pad_0, pad_type = x_205_pad_type_0, strides = x_205_strides_0, weight = encoder_encoders_19_self_attn_fsmn_block_weight_to_fp16, x = input_613_cast_fp16)[name = tensor("x_205_cast_fp16")]; + tensor x_207_perm_0 = const()[name = tensor("x_207_perm_0"), val = tensor([0, 2, 1])]; + tensor x_207_cast_fp16 = transpose(perm = x_207_perm_0, x = x_205_cast_fp16)[name = tensor("transpose_647")]; + tensor input_615_cast_fp16 = add(x = x_207_cast_fp16, y = inputs_41_cast_fp16)[name = tensor("input_615_cast_fp16")]; + tensor fsmn_memory_41_cast_fp16 = mul(x = input_615_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_41_cast_fp16")]; + tensor var_2353_to_fp16 = const()[name = tensor("op_2353_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_83_cast_fp16 = mul(x = var_2328_cast_fp16, y = var_2353_to_fp16)[name = tensor("q_h_83_cast_fp16")]; + tensor scores_81_transpose_x_0 = const()[name = tensor("scores_81_transpose_x_0"), val = tensor(false)]; + tensor scores_81_transpose_y_0 = const()[name = tensor("scores_81_transpose_y_0"), val = tensor(false)]; + tensor transpose_250_perm_0 = const()[name = tensor("transpose_250_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_251_perm_0 = const()[name = tensor("transpose_251_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_251 = transpose(perm = transpose_251_perm_0, x = var_2331_cast_fp16)[name = tensor("transpose_645")]; + tensor transpose_250 = transpose(perm = transpose_250_perm_0, x = q_h_83_cast_fp16)[name = tensor("transpose_646")]; + tensor scores_81_cast_fp16 = matmul(transpose_x = scores_81_transpose_x_0, transpose_y = scores_81_transpose_y_0, x = transpose_250, y = transpose_251)[name = tensor("scores_81_cast_fp16")]; + tensor scores_83_cast_fp16 = select(a = var_48_to_fp16, b = scores_81_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_83_cast_fp16")]; + tensor var_2361_cast_fp16 = softmax(axis = var_61, x = scores_83_cast_fp16)[name = tensor("op_2361_cast_fp16")]; + tensor input_617_cast_fp16 = select(a = var_53_to_fp16, b = var_2361_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_617_cast_fp16")]; + tensor x_211_transpose_x_0 = const()[name = tensor("x_211_transpose_x_0"), val = tensor(false)]; + tensor x_211_transpose_y_0 = const()[name = tensor("x_211_transpose_y_0"), val = tensor(false)]; + tensor value_41_cast_fp16 = transpose(perm = value_41_perm_0, x = var_2334_cast_fp16)[name = tensor("transpose_649")]; + tensor x_211_cast_fp16 = matmul(transpose_x = x_211_transpose_x_0, transpose_y = x_211_transpose_y_0, x = input_617_cast_fp16, y = value_41_cast_fp16)[name = tensor("x_211_cast_fp16")]; + tensor var_2365_perm_0 = const()[name = tensor("op_2365_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2367 = const()[name = tensor("op_2367"), val = tensor([1, -1, 512])]; + tensor var_2365_cast_fp16 = transpose(perm = var_2365_perm_0, x = x_211_cast_fp16)[name = tensor("transpose_644")]; + tensor input_619_cast_fp16 = reshape(shape = var_2367, x = var_2365_cast_fp16)[name = tensor("input_619_cast_fp16")]; + tensor encoder_encoders_19_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_19_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128095552)))]; + tensor encoder_encoders_19_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_19_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128619904)))]; + tensor linear_81_cast_fp16 = linear(bias = encoder_encoders_19_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_19_self_attn_linear_out_weight_to_fp16, x = input_619_cast_fp16)[name = tensor("linear_81_cast_fp16")]; + tensor input_621_cast_fp16 = add(x = linear_81_cast_fp16, y = fsmn_memory_41_cast_fp16)[name = tensor("input_621_cast_fp16")]; + tensor input_623_cast_fp16 = add(x = input_607_cast_fp16, y = input_621_cast_fp16)[name = tensor("input_623_cast_fp16")]; + tensor output_83_axes_0 = const()[name = tensor("output_83_axes_0"), val = tensor([-1])]; + tensor const_130_to_fp16 = const()[name = tensor("const_130_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128620992)))]; + tensor const_131_to_fp16 = const()[name = tensor("const_131_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128622080)))]; + tensor output_83_cast_fp16 = layer_norm(axes = output_83_axes_0, beta = const_131_to_fp16, epsilon = var_46_to_fp16, gamma = const_130_to_fp16, x = input_623_cast_fp16)[name = tensor("output_83_cast_fp16")]; + tensor encoder_encoders_19_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_19_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128623168)))]; + tensor encoder_encoders_19_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_19_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130720384)))]; + tensor linear_82_cast_fp16 = linear(bias = encoder_encoders_19_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_19_feed_forward_w_1_weight_to_fp16, x = output_83_cast_fp16)[name = tensor("linear_82_cast_fp16")]; + tensor input_631_cast_fp16 = relu(x = linear_82_cast_fp16)[name = tensor("input_631_cast_fp16")]; + tensor encoder_encoders_19_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_19_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130724544)))]; + tensor encoder_encoders_19_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_19_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132821760)))]; + tensor linear_83_cast_fp16 = linear(bias = encoder_encoders_19_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_19_feed_forward_w_2_weight_to_fp16, x = input_631_cast_fp16)[name = tensor("linear_83_cast_fp16")]; + tensor input_637_cast_fp16 = add(x = input_623_cast_fp16, y = linear_83_cast_fp16)[name = tensor("input_637_cast_fp16")]; + tensor output_85_axes_0 = const()[name = tensor("output_85_axes_0"), val = tensor([-1])]; + tensor const_132_to_fp16 = const()[name = tensor("const_132_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132822848)))]; + tensor const_133_to_fp16 = const()[name = tensor("const_133_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132823936)))]; + tensor output_85_cast_fp16 = layer_norm(axes = output_85_axes_0, beta = const_133_to_fp16, epsilon = var_46_to_fp16, gamma = const_132_to_fp16, x = input_637_cast_fp16)[name = tensor("output_85_cast_fp16")]; + tensor encoder_encoders_20_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_20_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132825024)))]; + tensor encoder_encoders_20_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_20_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134397952)))]; + tensor linear_84_cast_fp16 = linear(bias = encoder_encoders_20_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_20_self_attn_linear_q_k_v_weight_to_fp16, x = output_85_cast_fp16)[name = tensor("linear_84_cast_fp16")]; + tensor tile_21 = const()[name = tensor("tile_21"), val = tensor([512, 512, 512])]; + tensor var_2425_axis_0 = const()[name = tensor("op_2425_axis_0"), val = tensor(-1)]; + tensor var_2425_cast_fp16_0, tensor var_2425_cast_fp16_1, tensor var_2425_cast_fp16_2 = split(axis = var_2425_axis_0, split_sizes = tile_21, x = linear_84_cast_fp16)[name = tensor("op_2425_cast_fp16")]; + tensor concat_63x = const()[name = tensor("concat_63x"), val = tensor([1, -1, 4, 128])]; + tensor var_2430_cast_fp16 = reshape(shape = concat_63x, x = var_2425_cast_fp16_0)[name = tensor("op_2430_cast_fp16")]; + tensor concat_64x = const()[name = tensor("concat_64x"), val = tensor([1, -1, 4, 128])]; + tensor var_2433_cast_fp16 = reshape(shape = concat_64x, x = var_2425_cast_fp16_1)[name = tensor("op_2433_cast_fp16")]; + tensor concat_65x = const()[name = tensor("concat_65x"), val = tensor([1, -1, 4, 128])]; + tensor var_2436_cast_fp16 = reshape(shape = concat_65x, x = var_2425_cast_fp16_2)[name = tensor("op_2436_cast_fp16")]; + tensor value_43_perm_0 = const()[name = tensor("value_43_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_43_cast_fp16 = mul(x = var_2425_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_43_cast_fp16")]; + tensor input_641_perm_0 = const()[name = tensor("input_641_perm_0"), val = tensor([0, 2, 1])]; + tensor input_643_pad_0 = const()[name = tensor("input_643_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_643_mode_0 = const()[name = tensor("input_643_mode_0"), val = tensor("constant")]; + tensor const_135_to_fp16 = const()[name = tensor("const_135_to_fp16"), val = tensor(0x0p+0)]; + tensor input_641_cast_fp16 = transpose(perm = input_641_perm_0, x = inputs_43_cast_fp16)[name = tensor("transpose_642")]; + tensor input_643_cast_fp16 = pad(constant_val = const_135_to_fp16, mode = input_643_mode_0, pad = input_643_pad_0, x = input_641_cast_fp16)[name = tensor("input_643_cast_fp16")]; + tensor x_215_pad_type_0 = const()[name = tensor("x_215_pad_type_0"), val = tensor("valid")]; + tensor x_215_groups_0 = const()[name = tensor("x_215_groups_0"), val = tensor(512)]; + tensor x_215_strides_0 = const()[name = tensor("x_215_strides_0"), val = tensor([1])]; + tensor x_215_pad_0 = const()[name = tensor("x_215_pad_0"), val = tensor([0, 0])]; + tensor x_215_dilations_0 = const()[name = tensor("x_215_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_20_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_20_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134401088)))]; + tensor x_215_cast_fp16 = conv(dilations = x_215_dilations_0, groups = x_215_groups_0, pad = x_215_pad_0, pad_type = x_215_pad_type_0, strides = x_215_strides_0, weight = encoder_encoders_20_self_attn_fsmn_block_weight_to_fp16, x = input_643_cast_fp16)[name = tensor("x_215_cast_fp16")]; + tensor x_217_perm_0 = const()[name = tensor("x_217_perm_0"), val = tensor([0, 2, 1])]; + tensor x_217_cast_fp16 = transpose(perm = x_217_perm_0, x = x_215_cast_fp16)[name = tensor("transpose_641")]; + tensor input_645_cast_fp16 = add(x = x_217_cast_fp16, y = inputs_43_cast_fp16)[name = tensor("input_645_cast_fp16")]; + tensor fsmn_memory_43_cast_fp16 = mul(x = input_645_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_43_cast_fp16")]; + tensor var_2455_to_fp16 = const()[name = tensor("op_2455_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_87_cast_fp16 = mul(x = var_2430_cast_fp16, y = var_2455_to_fp16)[name = tensor("q_h_87_cast_fp16")]; + tensor scores_85_transpose_x_0 = const()[name = tensor("scores_85_transpose_x_0"), val = tensor(false)]; + tensor scores_85_transpose_y_0 = const()[name = tensor("scores_85_transpose_y_0"), val = tensor(false)]; + tensor transpose_252_perm_0 = const()[name = tensor("transpose_252_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_253_perm_0 = const()[name = tensor("transpose_253_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_253 = transpose(perm = transpose_253_perm_0, x = var_2433_cast_fp16)[name = tensor("transpose_639")]; + tensor transpose_252 = transpose(perm = transpose_252_perm_0, x = q_h_87_cast_fp16)[name = tensor("transpose_640")]; + tensor scores_85_cast_fp16 = matmul(transpose_x = scores_85_transpose_x_0, transpose_y = scores_85_transpose_y_0, x = transpose_252, y = transpose_253)[name = tensor("scores_85_cast_fp16")]; + tensor scores_87_cast_fp16 = select(a = var_48_to_fp16, b = scores_85_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_87_cast_fp16")]; + tensor var_2463_cast_fp16 = softmax(axis = var_61, x = scores_87_cast_fp16)[name = tensor("op_2463_cast_fp16")]; + tensor input_647_cast_fp16 = select(a = var_53_to_fp16, b = var_2463_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_647_cast_fp16")]; + tensor x_221_transpose_x_0 = const()[name = tensor("x_221_transpose_x_0"), val = tensor(false)]; + tensor x_221_transpose_y_0 = const()[name = tensor("x_221_transpose_y_0"), val = tensor(false)]; + tensor value_43_cast_fp16 = transpose(perm = value_43_perm_0, x = var_2436_cast_fp16)[name = tensor("transpose_643")]; + tensor x_221_cast_fp16 = matmul(transpose_x = x_221_transpose_x_0, transpose_y = x_221_transpose_y_0, x = input_647_cast_fp16, y = value_43_cast_fp16)[name = tensor("x_221_cast_fp16")]; + tensor var_2467_perm_0 = const()[name = tensor("op_2467_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2469 = const()[name = tensor("op_2469"), val = tensor([1, -1, 512])]; + tensor var_2467_cast_fp16 = transpose(perm = var_2467_perm_0, x = x_221_cast_fp16)[name = tensor("transpose_638")]; + tensor input_649_cast_fp16 = reshape(shape = var_2469, x = var_2467_cast_fp16)[name = tensor("input_649_cast_fp16")]; + tensor encoder_encoders_20_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_20_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134412416)))]; + tensor encoder_encoders_20_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_20_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134936768)))]; + tensor linear_85_cast_fp16 = linear(bias = encoder_encoders_20_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_20_self_attn_linear_out_weight_to_fp16, x = input_649_cast_fp16)[name = tensor("linear_85_cast_fp16")]; + tensor input_651_cast_fp16 = add(x = linear_85_cast_fp16, y = fsmn_memory_43_cast_fp16)[name = tensor("input_651_cast_fp16")]; + tensor input_653_cast_fp16 = add(x = input_637_cast_fp16, y = input_651_cast_fp16)[name = tensor("input_653_cast_fp16")]; + tensor output_87_axes_0 = const()[name = tensor("output_87_axes_0"), val = tensor([-1])]; + tensor const_136_to_fp16 = const()[name = tensor("const_136_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134937856)))]; + tensor const_137_to_fp16 = const()[name = tensor("const_137_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134938944)))]; + tensor output_87_cast_fp16 = layer_norm(axes = output_87_axes_0, beta = const_137_to_fp16, epsilon = var_46_to_fp16, gamma = const_136_to_fp16, x = input_653_cast_fp16)[name = tensor("output_87_cast_fp16")]; + tensor encoder_encoders_20_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_20_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134940032)))]; + tensor encoder_encoders_20_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_20_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137037248)))]; + tensor linear_86_cast_fp16 = linear(bias = encoder_encoders_20_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_20_feed_forward_w_1_weight_to_fp16, x = output_87_cast_fp16)[name = tensor("linear_86_cast_fp16")]; + tensor input_661_cast_fp16 = relu(x = linear_86_cast_fp16)[name = tensor("input_661_cast_fp16")]; + tensor encoder_encoders_20_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_20_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137041408)))]; + tensor encoder_encoders_20_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_20_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139138624)))]; + tensor linear_87_cast_fp16 = linear(bias = encoder_encoders_20_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_20_feed_forward_w_2_weight_to_fp16, x = input_661_cast_fp16)[name = tensor("linear_87_cast_fp16")]; + tensor input_667_cast_fp16 = add(x = input_653_cast_fp16, y = linear_87_cast_fp16)[name = tensor("input_667_cast_fp16")]; + tensor output_89_axes_0 = const()[name = tensor("output_89_axes_0"), val = tensor([-1])]; + tensor const_138_to_fp16 = const()[name = tensor("const_138_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139139712)))]; + tensor const_139_to_fp16 = const()[name = tensor("const_139_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139140800)))]; + tensor output_89_cast_fp16 = layer_norm(axes = output_89_axes_0, beta = const_139_to_fp16, epsilon = var_46_to_fp16, gamma = const_138_to_fp16, x = input_667_cast_fp16)[name = tensor("output_89_cast_fp16")]; + tensor encoder_encoders_21_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_21_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139141888)))]; + tensor encoder_encoders_21_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_21_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140714816)))]; + tensor linear_88_cast_fp16 = linear(bias = encoder_encoders_21_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_21_self_attn_linear_q_k_v_weight_to_fp16, x = output_89_cast_fp16)[name = tensor("linear_88_cast_fp16")]; + tensor tile_22 = const()[name = tensor("tile_22"), val = tensor([512, 512, 512])]; + tensor var_2527_axis_0 = const()[name = tensor("op_2527_axis_0"), val = tensor(-1)]; + tensor var_2527_cast_fp16_0, tensor var_2527_cast_fp16_1, tensor var_2527_cast_fp16_2 = split(axis = var_2527_axis_0, split_sizes = tile_22, x = linear_88_cast_fp16)[name = tensor("op_2527_cast_fp16")]; + tensor concat_66x = const()[name = tensor("concat_66x"), val = tensor([1, -1, 4, 128])]; + tensor var_2532_cast_fp16 = reshape(shape = concat_66x, x = var_2527_cast_fp16_0)[name = tensor("op_2532_cast_fp16")]; + tensor concat_67x = const()[name = tensor("concat_67x"), val = tensor([1, -1, 4, 128])]; + tensor var_2535_cast_fp16 = reshape(shape = concat_67x, x = var_2527_cast_fp16_1)[name = tensor("op_2535_cast_fp16")]; + tensor concat_68x = const()[name = tensor("concat_68x"), val = tensor([1, -1, 4, 128])]; + tensor var_2538_cast_fp16 = reshape(shape = concat_68x, x = var_2527_cast_fp16_2)[name = tensor("op_2538_cast_fp16")]; + tensor value_45_perm_0 = const()[name = tensor("value_45_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_45_cast_fp16 = mul(x = var_2527_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_45_cast_fp16")]; + tensor input_671_perm_0 = const()[name = tensor("input_671_perm_0"), val = tensor([0, 2, 1])]; + tensor input_673_pad_0 = const()[name = tensor("input_673_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_673_mode_0 = const()[name = tensor("input_673_mode_0"), val = tensor("constant")]; + tensor const_141_to_fp16 = const()[name = tensor("const_141_to_fp16"), val = tensor(0x0p+0)]; + tensor input_671_cast_fp16 = transpose(perm = input_671_perm_0, x = inputs_45_cast_fp16)[name = tensor("transpose_636")]; + tensor input_673_cast_fp16 = pad(constant_val = const_141_to_fp16, mode = input_673_mode_0, pad = input_673_pad_0, x = input_671_cast_fp16)[name = tensor("input_673_cast_fp16")]; + tensor x_225_pad_type_0 = const()[name = tensor("x_225_pad_type_0"), val = tensor("valid")]; + tensor x_225_groups_0 = const()[name = tensor("x_225_groups_0"), val = tensor(512)]; + tensor x_225_strides_0 = const()[name = tensor("x_225_strides_0"), val = tensor([1])]; + tensor x_225_pad_0 = const()[name = tensor("x_225_pad_0"), val = tensor([0, 0])]; + tensor x_225_dilations_0 = const()[name = tensor("x_225_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_21_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_21_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140717952)))]; + tensor x_225_cast_fp16 = conv(dilations = x_225_dilations_0, groups = x_225_groups_0, pad = x_225_pad_0, pad_type = x_225_pad_type_0, strides = x_225_strides_0, weight = encoder_encoders_21_self_attn_fsmn_block_weight_to_fp16, x = input_673_cast_fp16)[name = tensor("x_225_cast_fp16")]; + tensor x_227_perm_0 = const()[name = tensor("x_227_perm_0"), val = tensor([0, 2, 1])]; + tensor x_227_cast_fp16 = transpose(perm = x_227_perm_0, x = x_225_cast_fp16)[name = tensor("transpose_635")]; + tensor input_675_cast_fp16 = add(x = x_227_cast_fp16, y = inputs_45_cast_fp16)[name = tensor("input_675_cast_fp16")]; + tensor fsmn_memory_45_cast_fp16 = mul(x = input_675_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_45_cast_fp16")]; + tensor var_2557_to_fp16 = const()[name = tensor("op_2557_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_91_cast_fp16 = mul(x = var_2532_cast_fp16, y = var_2557_to_fp16)[name = tensor("q_h_91_cast_fp16")]; + tensor scores_89_transpose_x_0 = const()[name = tensor("scores_89_transpose_x_0"), val = tensor(false)]; + tensor scores_89_transpose_y_0 = const()[name = tensor("scores_89_transpose_y_0"), val = tensor(false)]; + tensor transpose_254_perm_0 = const()[name = tensor("transpose_254_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_255_perm_0 = const()[name = tensor("transpose_255_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_255 = transpose(perm = transpose_255_perm_0, x = var_2535_cast_fp16)[name = tensor("transpose_633")]; + tensor transpose_254 = transpose(perm = transpose_254_perm_0, x = q_h_91_cast_fp16)[name = tensor("transpose_634")]; + tensor scores_89_cast_fp16 = matmul(transpose_x = scores_89_transpose_x_0, transpose_y = scores_89_transpose_y_0, x = transpose_254, y = transpose_255)[name = tensor("scores_89_cast_fp16")]; + tensor scores_91_cast_fp16 = select(a = var_48_to_fp16, b = scores_89_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_91_cast_fp16")]; + tensor var_2565_cast_fp16 = softmax(axis = var_61, x = scores_91_cast_fp16)[name = tensor("op_2565_cast_fp16")]; + tensor input_677_cast_fp16 = select(a = var_53_to_fp16, b = var_2565_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_677_cast_fp16")]; + tensor x_231_transpose_x_0 = const()[name = tensor("x_231_transpose_x_0"), val = tensor(false)]; + tensor x_231_transpose_y_0 = const()[name = tensor("x_231_transpose_y_0"), val = tensor(false)]; + tensor value_45_cast_fp16 = transpose(perm = value_45_perm_0, x = var_2538_cast_fp16)[name = tensor("transpose_637")]; + tensor x_231_cast_fp16 = matmul(transpose_x = x_231_transpose_x_0, transpose_y = x_231_transpose_y_0, x = input_677_cast_fp16, y = value_45_cast_fp16)[name = tensor("x_231_cast_fp16")]; + tensor var_2569_perm_0 = const()[name = tensor("op_2569_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2571 = const()[name = tensor("op_2571"), val = tensor([1, -1, 512])]; + tensor var_2569_cast_fp16 = transpose(perm = var_2569_perm_0, x = x_231_cast_fp16)[name = tensor("transpose_632")]; + tensor input_679_cast_fp16 = reshape(shape = var_2571, x = var_2569_cast_fp16)[name = tensor("input_679_cast_fp16")]; + tensor encoder_encoders_21_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_21_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140729280)))]; + tensor encoder_encoders_21_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_21_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141253632)))]; + tensor linear_89_cast_fp16 = linear(bias = encoder_encoders_21_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_21_self_attn_linear_out_weight_to_fp16, x = input_679_cast_fp16)[name = tensor("linear_89_cast_fp16")]; + tensor input_681_cast_fp16 = add(x = linear_89_cast_fp16, y = fsmn_memory_45_cast_fp16)[name = tensor("input_681_cast_fp16")]; + tensor input_683_cast_fp16 = add(x = input_667_cast_fp16, y = input_681_cast_fp16)[name = tensor("input_683_cast_fp16")]; + tensor output_91_axes_0 = const()[name = tensor("output_91_axes_0"), val = tensor([-1])]; + tensor const_142_to_fp16 = const()[name = tensor("const_142_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141254720)))]; + tensor const_143_to_fp16 = const()[name = tensor("const_143_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141255808)))]; + tensor output_91_cast_fp16 = layer_norm(axes = output_91_axes_0, beta = const_143_to_fp16, epsilon = var_46_to_fp16, gamma = const_142_to_fp16, x = input_683_cast_fp16)[name = tensor("output_91_cast_fp16")]; + tensor encoder_encoders_21_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_21_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141256896)))]; + tensor encoder_encoders_21_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_21_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(143354112)))]; + tensor linear_90_cast_fp16 = linear(bias = encoder_encoders_21_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_21_feed_forward_w_1_weight_to_fp16, x = output_91_cast_fp16)[name = tensor("linear_90_cast_fp16")]; + tensor input_691_cast_fp16 = relu(x = linear_90_cast_fp16)[name = tensor("input_691_cast_fp16")]; + tensor encoder_encoders_21_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_21_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(143358272)))]; + tensor encoder_encoders_21_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_21_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145455488)))]; + tensor linear_91_cast_fp16 = linear(bias = encoder_encoders_21_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_21_feed_forward_w_2_weight_to_fp16, x = input_691_cast_fp16)[name = tensor("linear_91_cast_fp16")]; + tensor input_697_cast_fp16 = add(x = input_683_cast_fp16, y = linear_91_cast_fp16)[name = tensor("input_697_cast_fp16")]; + tensor output_93_axes_0 = const()[name = tensor("output_93_axes_0"), val = tensor([-1])]; + tensor const_144_to_fp16 = const()[name = tensor("const_144_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145456576)))]; + tensor const_145_to_fp16 = const()[name = tensor("const_145_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145457664)))]; + tensor output_93_cast_fp16 = layer_norm(axes = output_93_axes_0, beta = const_145_to_fp16, epsilon = var_46_to_fp16, gamma = const_144_to_fp16, x = input_697_cast_fp16)[name = tensor("output_93_cast_fp16")]; + tensor encoder_encoders_22_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_22_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145458752)))]; + tensor encoder_encoders_22_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_22_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147031680)))]; + tensor linear_92_cast_fp16 = linear(bias = encoder_encoders_22_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_22_self_attn_linear_q_k_v_weight_to_fp16, x = output_93_cast_fp16)[name = tensor("linear_92_cast_fp16")]; + tensor tile_23 = const()[name = tensor("tile_23"), val = tensor([512, 512, 512])]; + tensor var_2629_axis_0 = const()[name = tensor("op_2629_axis_0"), val = tensor(-1)]; + tensor var_2629_cast_fp16_0, tensor var_2629_cast_fp16_1, tensor var_2629_cast_fp16_2 = split(axis = var_2629_axis_0, split_sizes = tile_23, x = linear_92_cast_fp16)[name = tensor("op_2629_cast_fp16")]; + tensor concat_69x = const()[name = tensor("concat_69x"), val = tensor([1, -1, 4, 128])]; + tensor var_2634_cast_fp16 = reshape(shape = concat_69x, x = var_2629_cast_fp16_0)[name = tensor("op_2634_cast_fp16")]; + tensor concat_70x = const()[name = tensor("concat_70x"), val = tensor([1, -1, 4, 128])]; + tensor var_2637_cast_fp16 = reshape(shape = concat_70x, x = var_2629_cast_fp16_1)[name = tensor("op_2637_cast_fp16")]; + tensor concat_71x = const()[name = tensor("concat_71x"), val = tensor([1, -1, 4, 128])]; + tensor var_2640_cast_fp16 = reshape(shape = concat_71x, x = var_2629_cast_fp16_2)[name = tensor("op_2640_cast_fp16")]; + tensor value_47_perm_0 = const()[name = tensor("value_47_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_47_cast_fp16 = mul(x = var_2629_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_47_cast_fp16")]; + tensor input_701_perm_0 = const()[name = tensor("input_701_perm_0"), val = tensor([0, 2, 1])]; + tensor input_703_pad_0 = const()[name = tensor("input_703_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_703_mode_0 = const()[name = tensor("input_703_mode_0"), val = tensor("constant")]; + tensor const_147_to_fp16 = const()[name = tensor("const_147_to_fp16"), val = tensor(0x0p+0)]; + tensor input_701_cast_fp16 = transpose(perm = input_701_perm_0, x = inputs_47_cast_fp16)[name = tensor("transpose_630")]; + tensor input_703_cast_fp16 = pad(constant_val = const_147_to_fp16, mode = input_703_mode_0, pad = input_703_pad_0, x = input_701_cast_fp16)[name = tensor("input_703_cast_fp16")]; + tensor x_235_pad_type_0 = const()[name = tensor("x_235_pad_type_0"), val = tensor("valid")]; + tensor x_235_groups_0 = const()[name = tensor("x_235_groups_0"), val = tensor(512)]; + tensor x_235_strides_0 = const()[name = tensor("x_235_strides_0"), val = tensor([1])]; + tensor x_235_pad_0 = const()[name = tensor("x_235_pad_0"), val = tensor([0, 0])]; + tensor x_235_dilations_0 = const()[name = tensor("x_235_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_22_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_22_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147034816)))]; + tensor x_235_cast_fp16 = conv(dilations = x_235_dilations_0, groups = x_235_groups_0, pad = x_235_pad_0, pad_type = x_235_pad_type_0, strides = x_235_strides_0, weight = encoder_encoders_22_self_attn_fsmn_block_weight_to_fp16, x = input_703_cast_fp16)[name = tensor("x_235_cast_fp16")]; + tensor x_237_perm_0 = const()[name = tensor("x_237_perm_0"), val = tensor([0, 2, 1])]; + tensor x_237_cast_fp16 = transpose(perm = x_237_perm_0, x = x_235_cast_fp16)[name = tensor("transpose_629")]; + tensor input_705_cast_fp16 = add(x = x_237_cast_fp16, y = inputs_47_cast_fp16)[name = tensor("input_705_cast_fp16")]; + tensor fsmn_memory_47_cast_fp16 = mul(x = input_705_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_47_cast_fp16")]; + tensor var_2659_to_fp16 = const()[name = tensor("op_2659_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_95_cast_fp16 = mul(x = var_2634_cast_fp16, y = var_2659_to_fp16)[name = tensor("q_h_95_cast_fp16")]; + tensor scores_93_transpose_x_0 = const()[name = tensor("scores_93_transpose_x_0"), val = tensor(false)]; + tensor scores_93_transpose_y_0 = const()[name = tensor("scores_93_transpose_y_0"), val = tensor(false)]; + tensor transpose_256_perm_0 = const()[name = tensor("transpose_256_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_257_perm_0 = const()[name = tensor("transpose_257_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_257 = transpose(perm = transpose_257_perm_0, x = var_2637_cast_fp16)[name = tensor("transpose_627")]; + tensor transpose_256 = transpose(perm = transpose_256_perm_0, x = q_h_95_cast_fp16)[name = tensor("transpose_628")]; + tensor scores_93_cast_fp16 = matmul(transpose_x = scores_93_transpose_x_0, transpose_y = scores_93_transpose_y_0, x = transpose_256, y = transpose_257)[name = tensor("scores_93_cast_fp16")]; + tensor scores_95_cast_fp16 = select(a = var_48_to_fp16, b = scores_93_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_95_cast_fp16")]; + tensor var_2667_cast_fp16 = softmax(axis = var_61, x = scores_95_cast_fp16)[name = tensor("op_2667_cast_fp16")]; + tensor input_707_cast_fp16 = select(a = var_53_to_fp16, b = var_2667_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_707_cast_fp16")]; + tensor x_241_transpose_x_0 = const()[name = tensor("x_241_transpose_x_0"), val = tensor(false)]; + tensor x_241_transpose_y_0 = const()[name = tensor("x_241_transpose_y_0"), val = tensor(false)]; + tensor value_47_cast_fp16 = transpose(perm = value_47_perm_0, x = var_2640_cast_fp16)[name = tensor("transpose_631")]; + tensor x_241_cast_fp16 = matmul(transpose_x = x_241_transpose_x_0, transpose_y = x_241_transpose_y_0, x = input_707_cast_fp16, y = value_47_cast_fp16)[name = tensor("x_241_cast_fp16")]; + tensor var_2671_perm_0 = const()[name = tensor("op_2671_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2673 = const()[name = tensor("op_2673"), val = tensor([1, -1, 512])]; + tensor var_2671_cast_fp16 = transpose(perm = var_2671_perm_0, x = x_241_cast_fp16)[name = tensor("transpose_626")]; + tensor input_709_cast_fp16 = reshape(shape = var_2673, x = var_2671_cast_fp16)[name = tensor("input_709_cast_fp16")]; + tensor encoder_encoders_22_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_22_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147046144)))]; + tensor encoder_encoders_22_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_22_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147570496)))]; + tensor linear_93_cast_fp16 = linear(bias = encoder_encoders_22_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_22_self_attn_linear_out_weight_to_fp16, x = input_709_cast_fp16)[name = tensor("linear_93_cast_fp16")]; + tensor input_711_cast_fp16 = add(x = linear_93_cast_fp16, y = fsmn_memory_47_cast_fp16)[name = tensor("input_711_cast_fp16")]; + tensor input_713_cast_fp16 = add(x = input_697_cast_fp16, y = input_711_cast_fp16)[name = tensor("input_713_cast_fp16")]; + tensor output_95_axes_0 = const()[name = tensor("output_95_axes_0"), val = tensor([-1])]; + tensor const_148_to_fp16 = const()[name = tensor("const_148_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147571584)))]; + tensor const_149_to_fp16 = const()[name = tensor("const_149_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147572672)))]; + tensor output_95_cast_fp16 = layer_norm(axes = output_95_axes_0, beta = const_149_to_fp16, epsilon = var_46_to_fp16, gamma = const_148_to_fp16, x = input_713_cast_fp16)[name = tensor("output_95_cast_fp16")]; + tensor encoder_encoders_22_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_22_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147573760)))]; + tensor encoder_encoders_22_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_22_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(149670976)))]; + tensor linear_94_cast_fp16 = linear(bias = encoder_encoders_22_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_22_feed_forward_w_1_weight_to_fp16, x = output_95_cast_fp16)[name = tensor("linear_94_cast_fp16")]; + tensor input_721_cast_fp16 = relu(x = linear_94_cast_fp16)[name = tensor("input_721_cast_fp16")]; + tensor encoder_encoders_22_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_22_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(149675136)))]; + tensor encoder_encoders_22_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_22_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151772352)))]; + tensor linear_95_cast_fp16 = linear(bias = encoder_encoders_22_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_22_feed_forward_w_2_weight_to_fp16, x = input_721_cast_fp16)[name = tensor("linear_95_cast_fp16")]; + tensor input_727_cast_fp16 = add(x = input_713_cast_fp16, y = linear_95_cast_fp16)[name = tensor("input_727_cast_fp16")]; + tensor output_97_axes_0 = const()[name = tensor("output_97_axes_0"), val = tensor([-1])]; + tensor const_150_to_fp16 = const()[name = tensor("const_150_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151773440)))]; + tensor const_151_to_fp16 = const()[name = tensor("const_151_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151774528)))]; + tensor output_97_cast_fp16 = layer_norm(axes = output_97_axes_0, beta = const_151_to_fp16, epsilon = var_46_to_fp16, gamma = const_150_to_fp16, x = input_727_cast_fp16)[name = tensor("output_97_cast_fp16")]; + tensor encoder_encoders_23_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_23_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151775616)))]; + tensor encoder_encoders_23_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_23_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153348544)))]; + tensor linear_96_cast_fp16 = linear(bias = encoder_encoders_23_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_23_self_attn_linear_q_k_v_weight_to_fp16, x = output_97_cast_fp16)[name = tensor("linear_96_cast_fp16")]; + tensor tile_24 = const()[name = tensor("tile_24"), val = tensor([512, 512, 512])]; + tensor var_2731_axis_0 = const()[name = tensor("op_2731_axis_0"), val = tensor(-1)]; + tensor var_2731_cast_fp16_0, tensor var_2731_cast_fp16_1, tensor var_2731_cast_fp16_2 = split(axis = var_2731_axis_0, split_sizes = tile_24, x = linear_96_cast_fp16)[name = tensor("op_2731_cast_fp16")]; + tensor concat_72x = const()[name = tensor("concat_72x"), val = tensor([1, -1, 4, 128])]; + tensor var_2736_cast_fp16 = reshape(shape = concat_72x, x = var_2731_cast_fp16_0)[name = tensor("op_2736_cast_fp16")]; + tensor concat_73x = const()[name = tensor("concat_73x"), val = tensor([1, -1, 4, 128])]; + tensor var_2739_cast_fp16 = reshape(shape = concat_73x, x = var_2731_cast_fp16_1)[name = tensor("op_2739_cast_fp16")]; + tensor concat_74x = const()[name = tensor("concat_74x"), val = tensor([1, -1, 4, 128])]; + tensor var_2742_cast_fp16 = reshape(shape = concat_74x, x = var_2731_cast_fp16_2)[name = tensor("op_2742_cast_fp16")]; + tensor value_49_perm_0 = const()[name = tensor("value_49_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_49_cast_fp16 = mul(x = var_2731_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_49_cast_fp16")]; + tensor input_731_perm_0 = const()[name = tensor("input_731_perm_0"), val = tensor([0, 2, 1])]; + tensor input_733_pad_0 = const()[name = tensor("input_733_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_733_mode_0 = const()[name = tensor("input_733_mode_0"), val = tensor("constant")]; + tensor const_153_to_fp16 = const()[name = tensor("const_153_to_fp16"), val = tensor(0x0p+0)]; + tensor input_731_cast_fp16 = transpose(perm = input_731_perm_0, x = inputs_49_cast_fp16)[name = tensor("transpose_624")]; + tensor input_733_cast_fp16 = pad(constant_val = const_153_to_fp16, mode = input_733_mode_0, pad = input_733_pad_0, x = input_731_cast_fp16)[name = tensor("input_733_cast_fp16")]; + tensor x_245_pad_type_0 = const()[name = tensor("x_245_pad_type_0"), val = tensor("valid")]; + tensor x_245_groups_0 = const()[name = tensor("x_245_groups_0"), val = tensor(512)]; + tensor x_245_strides_0 = const()[name = tensor("x_245_strides_0"), val = tensor([1])]; + tensor x_245_pad_0 = const()[name = tensor("x_245_pad_0"), val = tensor([0, 0])]; + tensor x_245_dilations_0 = const()[name = tensor("x_245_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_23_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_23_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153351680)))]; + tensor x_245_cast_fp16 = conv(dilations = x_245_dilations_0, groups = x_245_groups_0, pad = x_245_pad_0, pad_type = x_245_pad_type_0, strides = x_245_strides_0, weight = encoder_encoders_23_self_attn_fsmn_block_weight_to_fp16, x = input_733_cast_fp16)[name = tensor("x_245_cast_fp16")]; + tensor x_247_perm_0 = const()[name = tensor("x_247_perm_0"), val = tensor([0, 2, 1])]; + tensor x_247_cast_fp16 = transpose(perm = x_247_perm_0, x = x_245_cast_fp16)[name = tensor("transpose_623")]; + tensor input_735_cast_fp16 = add(x = x_247_cast_fp16, y = inputs_49_cast_fp16)[name = tensor("input_735_cast_fp16")]; + tensor fsmn_memory_49_cast_fp16 = mul(x = input_735_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_49_cast_fp16")]; + tensor var_2761_to_fp16 = const()[name = tensor("op_2761_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_99_cast_fp16 = mul(x = var_2736_cast_fp16, y = var_2761_to_fp16)[name = tensor("q_h_99_cast_fp16")]; + tensor scores_97_transpose_x_0 = const()[name = tensor("scores_97_transpose_x_0"), val = tensor(false)]; + tensor scores_97_transpose_y_0 = const()[name = tensor("scores_97_transpose_y_0"), val = tensor(false)]; + tensor transpose_258_perm_0 = const()[name = tensor("transpose_258_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_259_perm_0 = const()[name = tensor("transpose_259_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_259 = transpose(perm = transpose_259_perm_0, x = var_2739_cast_fp16)[name = tensor("transpose_621")]; + tensor transpose_258 = transpose(perm = transpose_258_perm_0, x = q_h_99_cast_fp16)[name = tensor("transpose_622")]; + tensor scores_97_cast_fp16 = matmul(transpose_x = scores_97_transpose_x_0, transpose_y = scores_97_transpose_y_0, x = transpose_258, y = transpose_259)[name = tensor("scores_97_cast_fp16")]; + tensor scores_99_cast_fp16 = select(a = var_48_to_fp16, b = scores_97_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_99_cast_fp16")]; + tensor var_2769_cast_fp16 = softmax(axis = var_61, x = scores_99_cast_fp16)[name = tensor("op_2769_cast_fp16")]; + tensor input_737_cast_fp16 = select(a = var_53_to_fp16, b = var_2769_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_737_cast_fp16")]; + tensor x_251_transpose_x_0 = const()[name = tensor("x_251_transpose_x_0"), val = tensor(false)]; + tensor x_251_transpose_y_0 = const()[name = tensor("x_251_transpose_y_0"), val = tensor(false)]; + tensor value_49_cast_fp16 = transpose(perm = value_49_perm_0, x = var_2742_cast_fp16)[name = tensor("transpose_625")]; + tensor x_251_cast_fp16 = matmul(transpose_x = x_251_transpose_x_0, transpose_y = x_251_transpose_y_0, x = input_737_cast_fp16, y = value_49_cast_fp16)[name = tensor("x_251_cast_fp16")]; + tensor var_2773_perm_0 = const()[name = tensor("op_2773_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2775 = const()[name = tensor("op_2775"), val = tensor([1, -1, 512])]; + tensor var_2773_cast_fp16 = transpose(perm = var_2773_perm_0, x = x_251_cast_fp16)[name = tensor("transpose_620")]; + tensor input_739_cast_fp16 = reshape(shape = var_2775, x = var_2773_cast_fp16)[name = tensor("input_739_cast_fp16")]; + tensor encoder_encoders_23_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_23_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153363008)))]; + tensor encoder_encoders_23_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_23_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153887360)))]; + tensor linear_97_cast_fp16 = linear(bias = encoder_encoders_23_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_23_self_attn_linear_out_weight_to_fp16, x = input_739_cast_fp16)[name = tensor("linear_97_cast_fp16")]; + tensor input_741_cast_fp16 = add(x = linear_97_cast_fp16, y = fsmn_memory_49_cast_fp16)[name = tensor("input_741_cast_fp16")]; + tensor input_743_cast_fp16 = add(x = input_727_cast_fp16, y = input_741_cast_fp16)[name = tensor("input_743_cast_fp16")]; + tensor output_99_axes_0 = const()[name = tensor("output_99_axes_0"), val = tensor([-1])]; + tensor const_154_to_fp16 = const()[name = tensor("const_154_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153888448)))]; + tensor const_155_to_fp16 = const()[name = tensor("const_155_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153889536)))]; + tensor output_99_cast_fp16 = layer_norm(axes = output_99_axes_0, beta = const_155_to_fp16, epsilon = var_46_to_fp16, gamma = const_154_to_fp16, x = input_743_cast_fp16)[name = tensor("output_99_cast_fp16")]; + tensor encoder_encoders_23_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_23_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153890624)))]; + tensor encoder_encoders_23_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_23_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(155987840)))]; + tensor linear_98_cast_fp16 = linear(bias = encoder_encoders_23_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_23_feed_forward_w_1_weight_to_fp16, x = output_99_cast_fp16)[name = tensor("linear_98_cast_fp16")]; + tensor input_751_cast_fp16 = relu(x = linear_98_cast_fp16)[name = tensor("input_751_cast_fp16")]; + tensor encoder_encoders_23_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_23_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(155992000)))]; + tensor encoder_encoders_23_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_23_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158089216)))]; + tensor linear_99_cast_fp16 = linear(bias = encoder_encoders_23_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_23_feed_forward_w_2_weight_to_fp16, x = input_751_cast_fp16)[name = tensor("linear_99_cast_fp16")]; + tensor input_757_cast_fp16 = add(x = input_743_cast_fp16, y = linear_99_cast_fp16)[name = tensor("input_757_cast_fp16")]; + tensor output_101_axes_0 = const()[name = tensor("output_101_axes_0"), val = tensor([-1])]; + tensor const_156_to_fp16 = const()[name = tensor("const_156_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158090304)))]; + tensor const_157_to_fp16 = const()[name = tensor("const_157_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158091392)))]; + tensor output_101_cast_fp16 = layer_norm(axes = output_101_axes_0, beta = const_157_to_fp16, epsilon = var_46_to_fp16, gamma = const_156_to_fp16, x = input_757_cast_fp16)[name = tensor("output_101_cast_fp16")]; + tensor encoder_encoders_24_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_24_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158092480)))]; + tensor encoder_encoders_24_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_24_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159665408)))]; + tensor linear_100_cast_fp16 = linear(bias = encoder_encoders_24_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_24_self_attn_linear_q_k_v_weight_to_fp16, x = output_101_cast_fp16)[name = tensor("linear_100_cast_fp16")]; + tensor tile_25 = const()[name = tensor("tile_25"), val = tensor([512, 512, 512])]; + tensor var_2833_axis_0 = const()[name = tensor("op_2833_axis_0"), val = tensor(-1)]; + tensor var_2833_cast_fp16_0, tensor var_2833_cast_fp16_1, tensor var_2833_cast_fp16_2 = split(axis = var_2833_axis_0, split_sizes = tile_25, x = linear_100_cast_fp16)[name = tensor("op_2833_cast_fp16")]; + tensor concat_75x = const()[name = tensor("concat_75x"), val = tensor([1, -1, 4, 128])]; + tensor var_2838_cast_fp16 = reshape(shape = concat_75x, x = var_2833_cast_fp16_0)[name = tensor("op_2838_cast_fp16")]; + tensor concat_76x = const()[name = tensor("concat_76x"), val = tensor([1, -1, 4, 128])]; + tensor var_2841_cast_fp16 = reshape(shape = concat_76x, x = var_2833_cast_fp16_1)[name = tensor("op_2841_cast_fp16")]; + tensor concat_77x = const()[name = tensor("concat_77x"), val = tensor([1, -1, 4, 128])]; + tensor var_2844_cast_fp16 = reshape(shape = concat_77x, x = var_2833_cast_fp16_2)[name = tensor("op_2844_cast_fp16")]; + tensor value_51_perm_0 = const()[name = tensor("value_51_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_51_cast_fp16 = mul(x = var_2833_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_51_cast_fp16")]; + tensor input_761_perm_0 = const()[name = tensor("input_761_perm_0"), val = tensor([0, 2, 1])]; + tensor input_763_pad_0 = const()[name = tensor("input_763_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_763_mode_0 = const()[name = tensor("input_763_mode_0"), val = tensor("constant")]; + tensor const_159_to_fp16 = const()[name = tensor("const_159_to_fp16"), val = tensor(0x0p+0)]; + tensor input_761_cast_fp16 = transpose(perm = input_761_perm_0, x = inputs_51_cast_fp16)[name = tensor("transpose_618")]; + tensor input_763_cast_fp16 = pad(constant_val = const_159_to_fp16, mode = input_763_mode_0, pad = input_763_pad_0, x = input_761_cast_fp16)[name = tensor("input_763_cast_fp16")]; + tensor x_255_pad_type_0 = const()[name = tensor("x_255_pad_type_0"), val = tensor("valid")]; + tensor x_255_groups_0 = const()[name = tensor("x_255_groups_0"), val = tensor(512)]; + tensor x_255_strides_0 = const()[name = tensor("x_255_strides_0"), val = tensor([1])]; + tensor x_255_pad_0 = const()[name = tensor("x_255_pad_0"), val = tensor([0, 0])]; + tensor x_255_dilations_0 = const()[name = tensor("x_255_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_24_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_24_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159668544)))]; + tensor x_255_cast_fp16 = conv(dilations = x_255_dilations_0, groups = x_255_groups_0, pad = x_255_pad_0, pad_type = x_255_pad_type_0, strides = x_255_strides_0, weight = encoder_encoders_24_self_attn_fsmn_block_weight_to_fp16, x = input_763_cast_fp16)[name = tensor("x_255_cast_fp16")]; + tensor x_257_perm_0 = const()[name = tensor("x_257_perm_0"), val = tensor([0, 2, 1])]; + tensor x_257_cast_fp16 = transpose(perm = x_257_perm_0, x = x_255_cast_fp16)[name = tensor("transpose_617")]; + tensor input_765_cast_fp16 = add(x = x_257_cast_fp16, y = inputs_51_cast_fp16)[name = tensor("input_765_cast_fp16")]; + tensor fsmn_memory_51_cast_fp16 = mul(x = input_765_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_51_cast_fp16")]; + tensor var_2863_to_fp16 = const()[name = tensor("op_2863_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_103_cast_fp16 = mul(x = var_2838_cast_fp16, y = var_2863_to_fp16)[name = tensor("q_h_103_cast_fp16")]; + tensor scores_101_transpose_x_0 = const()[name = tensor("scores_101_transpose_x_0"), val = tensor(false)]; + tensor scores_101_transpose_y_0 = const()[name = tensor("scores_101_transpose_y_0"), val = tensor(false)]; + tensor transpose_260_perm_0 = const()[name = tensor("transpose_260_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_261_perm_0 = const()[name = tensor("transpose_261_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_261 = transpose(perm = transpose_261_perm_0, x = var_2841_cast_fp16)[name = tensor("transpose_615")]; + tensor transpose_260 = transpose(perm = transpose_260_perm_0, x = q_h_103_cast_fp16)[name = tensor("transpose_616")]; + tensor scores_101_cast_fp16 = matmul(transpose_x = scores_101_transpose_x_0, transpose_y = scores_101_transpose_y_0, x = transpose_260, y = transpose_261)[name = tensor("scores_101_cast_fp16")]; + tensor scores_103_cast_fp16 = select(a = var_48_to_fp16, b = scores_101_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_103_cast_fp16")]; + tensor var_2871_cast_fp16 = softmax(axis = var_61, x = scores_103_cast_fp16)[name = tensor("op_2871_cast_fp16")]; + tensor input_767_cast_fp16 = select(a = var_53_to_fp16, b = var_2871_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_767_cast_fp16")]; + tensor x_261_transpose_x_0 = const()[name = tensor("x_261_transpose_x_0"), val = tensor(false)]; + tensor x_261_transpose_y_0 = const()[name = tensor("x_261_transpose_y_0"), val = tensor(false)]; + tensor value_51_cast_fp16 = transpose(perm = value_51_perm_0, x = var_2844_cast_fp16)[name = tensor("transpose_619")]; + tensor x_261_cast_fp16 = matmul(transpose_x = x_261_transpose_x_0, transpose_y = x_261_transpose_y_0, x = input_767_cast_fp16, y = value_51_cast_fp16)[name = tensor("x_261_cast_fp16")]; + tensor var_2875_perm_0 = const()[name = tensor("op_2875_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2877 = const()[name = tensor("op_2877"), val = tensor([1, -1, 512])]; + tensor var_2875_cast_fp16 = transpose(perm = var_2875_perm_0, x = x_261_cast_fp16)[name = tensor("transpose_614")]; + tensor input_769_cast_fp16 = reshape(shape = var_2877, x = var_2875_cast_fp16)[name = tensor("input_769_cast_fp16")]; + tensor encoder_encoders_24_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_24_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159679872)))]; + tensor encoder_encoders_24_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_24_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160204224)))]; + tensor linear_101_cast_fp16 = linear(bias = encoder_encoders_24_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_24_self_attn_linear_out_weight_to_fp16, x = input_769_cast_fp16)[name = tensor("linear_101_cast_fp16")]; + tensor input_771_cast_fp16 = add(x = linear_101_cast_fp16, y = fsmn_memory_51_cast_fp16)[name = tensor("input_771_cast_fp16")]; + tensor input_773_cast_fp16 = add(x = input_757_cast_fp16, y = input_771_cast_fp16)[name = tensor("input_773_cast_fp16")]; + tensor output_103_axes_0 = const()[name = tensor("output_103_axes_0"), val = tensor([-1])]; + tensor const_160_to_fp16 = const()[name = tensor("const_160_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160205312)))]; + tensor const_161_to_fp16 = const()[name = tensor("const_161_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160206400)))]; + tensor output_103_cast_fp16 = layer_norm(axes = output_103_axes_0, beta = const_161_to_fp16, epsilon = var_46_to_fp16, gamma = const_160_to_fp16, x = input_773_cast_fp16)[name = tensor("output_103_cast_fp16")]; + tensor encoder_encoders_24_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_24_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160207488)))]; + tensor encoder_encoders_24_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_24_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(162304704)))]; + tensor linear_102_cast_fp16 = linear(bias = encoder_encoders_24_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_24_feed_forward_w_1_weight_to_fp16, x = output_103_cast_fp16)[name = tensor("linear_102_cast_fp16")]; + tensor input_781_cast_fp16 = relu(x = linear_102_cast_fp16)[name = tensor("input_781_cast_fp16")]; + tensor encoder_encoders_24_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_24_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(162308864)))]; + tensor encoder_encoders_24_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_24_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164406080)))]; + tensor linear_103_cast_fp16 = linear(bias = encoder_encoders_24_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_24_feed_forward_w_2_weight_to_fp16, x = input_781_cast_fp16)[name = tensor("linear_103_cast_fp16")]; + tensor input_787_cast_fp16 = add(x = input_773_cast_fp16, y = linear_103_cast_fp16)[name = tensor("input_787_cast_fp16")]; + tensor output_105_axes_0 = const()[name = tensor("output_105_axes_0"), val = tensor([-1])]; + tensor const_162_to_fp16 = const()[name = tensor("const_162_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164407168)))]; + tensor const_163_to_fp16 = const()[name = tensor("const_163_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164408256)))]; + tensor output_105_cast_fp16 = layer_norm(axes = output_105_axes_0, beta = const_163_to_fp16, epsilon = var_46_to_fp16, gamma = const_162_to_fp16, x = input_787_cast_fp16)[name = tensor("output_105_cast_fp16")]; + tensor encoder_encoders_25_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_25_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164409344)))]; + tensor encoder_encoders_25_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_25_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165982272)))]; + tensor linear_104_cast_fp16 = linear(bias = encoder_encoders_25_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_25_self_attn_linear_q_k_v_weight_to_fp16, x = output_105_cast_fp16)[name = tensor("linear_104_cast_fp16")]; + tensor tile_26 = const()[name = tensor("tile_26"), val = tensor([512, 512, 512])]; + tensor var_2935_axis_0 = const()[name = tensor("op_2935_axis_0"), val = tensor(-1)]; + tensor var_2935_cast_fp16_0, tensor var_2935_cast_fp16_1, tensor var_2935_cast_fp16_2 = split(axis = var_2935_axis_0, split_sizes = tile_26, x = linear_104_cast_fp16)[name = tensor("op_2935_cast_fp16")]; + tensor concat_78x = const()[name = tensor("concat_78x"), val = tensor([1, -1, 4, 128])]; + tensor var_2940_cast_fp16 = reshape(shape = concat_78x, x = var_2935_cast_fp16_0)[name = tensor("op_2940_cast_fp16")]; + tensor concat_79x = const()[name = tensor("concat_79x"), val = tensor([1, -1, 4, 128])]; + tensor var_2943_cast_fp16 = reshape(shape = concat_79x, x = var_2935_cast_fp16_1)[name = tensor("op_2943_cast_fp16")]; + tensor concat_80x = const()[name = tensor("concat_80x"), val = tensor([1, -1, 4, 128])]; + tensor var_2946_cast_fp16 = reshape(shape = concat_80x, x = var_2935_cast_fp16_2)[name = tensor("op_2946_cast_fp16")]; + tensor value_53_perm_0 = const()[name = tensor("value_53_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_53_cast_fp16 = mul(x = var_2935_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_53_cast_fp16")]; + tensor input_791_perm_0 = const()[name = tensor("input_791_perm_0"), val = tensor([0, 2, 1])]; + tensor input_793_pad_0 = const()[name = tensor("input_793_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_793_mode_0 = const()[name = tensor("input_793_mode_0"), val = tensor("constant")]; + tensor const_165_to_fp16 = const()[name = tensor("const_165_to_fp16"), val = tensor(0x0p+0)]; + tensor input_791_cast_fp16 = transpose(perm = input_791_perm_0, x = inputs_53_cast_fp16)[name = tensor("transpose_612")]; + tensor input_793_cast_fp16 = pad(constant_val = const_165_to_fp16, mode = input_793_mode_0, pad = input_793_pad_0, x = input_791_cast_fp16)[name = tensor("input_793_cast_fp16")]; + tensor x_265_pad_type_0 = const()[name = tensor("x_265_pad_type_0"), val = tensor("valid")]; + tensor x_265_groups_0 = const()[name = tensor("x_265_groups_0"), val = tensor(512)]; + tensor x_265_strides_0 = const()[name = tensor("x_265_strides_0"), val = tensor([1])]; + tensor x_265_pad_0 = const()[name = tensor("x_265_pad_0"), val = tensor([0, 0])]; + tensor x_265_dilations_0 = const()[name = tensor("x_265_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_25_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_25_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165985408)))]; + tensor x_265_cast_fp16 = conv(dilations = x_265_dilations_0, groups = x_265_groups_0, pad = x_265_pad_0, pad_type = x_265_pad_type_0, strides = x_265_strides_0, weight = encoder_encoders_25_self_attn_fsmn_block_weight_to_fp16, x = input_793_cast_fp16)[name = tensor("x_265_cast_fp16")]; + tensor x_267_perm_0 = const()[name = tensor("x_267_perm_0"), val = tensor([0, 2, 1])]; + tensor x_267_cast_fp16 = transpose(perm = x_267_perm_0, x = x_265_cast_fp16)[name = tensor("transpose_611")]; + tensor input_795_cast_fp16 = add(x = x_267_cast_fp16, y = inputs_53_cast_fp16)[name = tensor("input_795_cast_fp16")]; + tensor fsmn_memory_53_cast_fp16 = mul(x = input_795_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_53_cast_fp16")]; + tensor var_2965_to_fp16 = const()[name = tensor("op_2965_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_107_cast_fp16 = mul(x = var_2940_cast_fp16, y = var_2965_to_fp16)[name = tensor("q_h_107_cast_fp16")]; + tensor scores_105_transpose_x_0 = const()[name = tensor("scores_105_transpose_x_0"), val = tensor(false)]; + tensor scores_105_transpose_y_0 = const()[name = tensor("scores_105_transpose_y_0"), val = tensor(false)]; + tensor transpose_262_perm_0 = const()[name = tensor("transpose_262_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_263_perm_0 = const()[name = tensor("transpose_263_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_263 = transpose(perm = transpose_263_perm_0, x = var_2943_cast_fp16)[name = tensor("transpose_609")]; + tensor transpose_262 = transpose(perm = transpose_262_perm_0, x = q_h_107_cast_fp16)[name = tensor("transpose_610")]; + tensor scores_105_cast_fp16 = matmul(transpose_x = scores_105_transpose_x_0, transpose_y = scores_105_transpose_y_0, x = transpose_262, y = transpose_263)[name = tensor("scores_105_cast_fp16")]; + tensor scores_107_cast_fp16 = select(a = var_48_to_fp16, b = scores_105_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_107_cast_fp16")]; + tensor var_2973_cast_fp16 = softmax(axis = var_61, x = scores_107_cast_fp16)[name = tensor("op_2973_cast_fp16")]; + tensor input_797_cast_fp16 = select(a = var_53_to_fp16, b = var_2973_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_797_cast_fp16")]; + tensor x_271_transpose_x_0 = const()[name = tensor("x_271_transpose_x_0"), val = tensor(false)]; + tensor x_271_transpose_y_0 = const()[name = tensor("x_271_transpose_y_0"), val = tensor(false)]; + tensor value_53_cast_fp16 = transpose(perm = value_53_perm_0, x = var_2946_cast_fp16)[name = tensor("transpose_613")]; + tensor x_271_cast_fp16 = matmul(transpose_x = x_271_transpose_x_0, transpose_y = x_271_transpose_y_0, x = input_797_cast_fp16, y = value_53_cast_fp16)[name = tensor("x_271_cast_fp16")]; + tensor var_2977_perm_0 = const()[name = tensor("op_2977_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2979 = const()[name = tensor("op_2979"), val = tensor([1, -1, 512])]; + tensor var_2977_cast_fp16 = transpose(perm = var_2977_perm_0, x = x_271_cast_fp16)[name = tensor("transpose_608")]; + tensor input_799_cast_fp16 = reshape(shape = var_2979, x = var_2977_cast_fp16)[name = tensor("input_799_cast_fp16")]; + tensor encoder_encoders_25_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_25_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165996736)))]; + tensor encoder_encoders_25_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_25_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166521088)))]; + tensor linear_105_cast_fp16 = linear(bias = encoder_encoders_25_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_25_self_attn_linear_out_weight_to_fp16, x = input_799_cast_fp16)[name = tensor("linear_105_cast_fp16")]; + tensor input_801_cast_fp16 = add(x = linear_105_cast_fp16, y = fsmn_memory_53_cast_fp16)[name = tensor("input_801_cast_fp16")]; + tensor input_803_cast_fp16 = add(x = input_787_cast_fp16, y = input_801_cast_fp16)[name = tensor("input_803_cast_fp16")]; + tensor output_107_axes_0 = const()[name = tensor("output_107_axes_0"), val = tensor([-1])]; + tensor const_166_to_fp16 = const()[name = tensor("const_166_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166522176)))]; + tensor const_167_to_fp16 = const()[name = tensor("const_167_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166523264)))]; + tensor output_107_cast_fp16 = layer_norm(axes = output_107_axes_0, beta = const_167_to_fp16, epsilon = var_46_to_fp16, gamma = const_166_to_fp16, x = input_803_cast_fp16)[name = tensor("output_107_cast_fp16")]; + tensor encoder_encoders_25_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_25_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166524352)))]; + tensor encoder_encoders_25_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_25_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(168621568)))]; + tensor linear_106_cast_fp16 = linear(bias = encoder_encoders_25_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_25_feed_forward_w_1_weight_to_fp16, x = output_107_cast_fp16)[name = tensor("linear_106_cast_fp16")]; + tensor input_811_cast_fp16 = relu(x = linear_106_cast_fp16)[name = tensor("input_811_cast_fp16")]; + tensor encoder_encoders_25_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_25_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(168625728)))]; + tensor encoder_encoders_25_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_25_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170722944)))]; + tensor linear_107_cast_fp16 = linear(bias = encoder_encoders_25_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_25_feed_forward_w_2_weight_to_fp16, x = input_811_cast_fp16)[name = tensor("linear_107_cast_fp16")]; + tensor input_817_cast_fp16 = add(x = input_803_cast_fp16, y = linear_107_cast_fp16)[name = tensor("input_817_cast_fp16")]; + tensor output_109_axes_0 = const()[name = tensor("output_109_axes_0"), val = tensor([-1])]; + tensor const_168_to_fp16 = const()[name = tensor("const_168_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170724032)))]; + tensor const_169_to_fp16 = const()[name = tensor("const_169_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170725120)))]; + tensor output_109_cast_fp16 = layer_norm(axes = output_109_axes_0, beta = const_169_to_fp16, epsilon = var_46_to_fp16, gamma = const_168_to_fp16, x = input_817_cast_fp16)[name = tensor("output_109_cast_fp16")]; + tensor encoder_encoders_26_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_26_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170726208)))]; + tensor encoder_encoders_26_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_26_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172299136)))]; + tensor linear_108_cast_fp16 = linear(bias = encoder_encoders_26_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_26_self_attn_linear_q_k_v_weight_to_fp16, x = output_109_cast_fp16)[name = tensor("linear_108_cast_fp16")]; + tensor tile_27 = const()[name = tensor("tile_27"), val = tensor([512, 512, 512])]; + tensor var_3037_axis_0 = const()[name = tensor("op_3037_axis_0"), val = tensor(-1)]; + tensor var_3037_cast_fp16_0, tensor var_3037_cast_fp16_1, tensor var_3037_cast_fp16_2 = split(axis = var_3037_axis_0, split_sizes = tile_27, x = linear_108_cast_fp16)[name = tensor("op_3037_cast_fp16")]; + tensor concat_81x = const()[name = tensor("concat_81x"), val = tensor([1, -1, 4, 128])]; + tensor var_3042_cast_fp16 = reshape(shape = concat_81x, x = var_3037_cast_fp16_0)[name = tensor("op_3042_cast_fp16")]; + tensor concat_82x = const()[name = tensor("concat_82x"), val = tensor([1, -1, 4, 128])]; + tensor var_3045_cast_fp16 = reshape(shape = concat_82x, x = var_3037_cast_fp16_1)[name = tensor("op_3045_cast_fp16")]; + tensor concat_83x = const()[name = tensor("concat_83x"), val = tensor([1, -1, 4, 128])]; + tensor var_3048_cast_fp16 = reshape(shape = concat_83x, x = var_3037_cast_fp16_2)[name = tensor("op_3048_cast_fp16")]; + tensor value_55_perm_0 = const()[name = tensor("value_55_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_55_cast_fp16 = mul(x = var_3037_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_55_cast_fp16")]; + tensor input_821_perm_0 = const()[name = tensor("input_821_perm_0"), val = tensor([0, 2, 1])]; + tensor input_823_pad_0 = const()[name = tensor("input_823_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_823_mode_0 = const()[name = tensor("input_823_mode_0"), val = tensor("constant")]; + tensor const_171_to_fp16 = const()[name = tensor("const_171_to_fp16"), val = tensor(0x0p+0)]; + tensor input_821_cast_fp16 = transpose(perm = input_821_perm_0, x = inputs_55_cast_fp16)[name = tensor("transpose_606")]; + tensor input_823_cast_fp16 = pad(constant_val = const_171_to_fp16, mode = input_823_mode_0, pad = input_823_pad_0, x = input_821_cast_fp16)[name = tensor("input_823_cast_fp16")]; + tensor x_275_pad_type_0 = const()[name = tensor("x_275_pad_type_0"), val = tensor("valid")]; + tensor x_275_groups_0 = const()[name = tensor("x_275_groups_0"), val = tensor(512)]; + tensor x_275_strides_0 = const()[name = tensor("x_275_strides_0"), val = tensor([1])]; + tensor x_275_pad_0 = const()[name = tensor("x_275_pad_0"), val = tensor([0, 0])]; + tensor x_275_dilations_0 = const()[name = tensor("x_275_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_26_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_26_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172302272)))]; + tensor x_275_cast_fp16 = conv(dilations = x_275_dilations_0, groups = x_275_groups_0, pad = x_275_pad_0, pad_type = x_275_pad_type_0, strides = x_275_strides_0, weight = encoder_encoders_26_self_attn_fsmn_block_weight_to_fp16, x = input_823_cast_fp16)[name = tensor("x_275_cast_fp16")]; + tensor x_277_perm_0 = const()[name = tensor("x_277_perm_0"), val = tensor([0, 2, 1])]; + tensor x_277_cast_fp16 = transpose(perm = x_277_perm_0, x = x_275_cast_fp16)[name = tensor("transpose_605")]; + tensor input_825_cast_fp16 = add(x = x_277_cast_fp16, y = inputs_55_cast_fp16)[name = tensor("input_825_cast_fp16")]; + tensor fsmn_memory_55_cast_fp16 = mul(x = input_825_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_55_cast_fp16")]; + tensor var_3067_to_fp16 = const()[name = tensor("op_3067_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_111_cast_fp16 = mul(x = var_3042_cast_fp16, y = var_3067_to_fp16)[name = tensor("q_h_111_cast_fp16")]; + tensor scores_109_transpose_x_0 = const()[name = tensor("scores_109_transpose_x_0"), val = tensor(false)]; + tensor scores_109_transpose_y_0 = const()[name = tensor("scores_109_transpose_y_0"), val = tensor(false)]; + tensor transpose_264_perm_0 = const()[name = tensor("transpose_264_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_265_perm_0 = const()[name = tensor("transpose_265_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_265 = transpose(perm = transpose_265_perm_0, x = var_3045_cast_fp16)[name = tensor("transpose_603")]; + tensor transpose_264 = transpose(perm = transpose_264_perm_0, x = q_h_111_cast_fp16)[name = tensor("transpose_604")]; + tensor scores_109_cast_fp16 = matmul(transpose_x = scores_109_transpose_x_0, transpose_y = scores_109_transpose_y_0, x = transpose_264, y = transpose_265)[name = tensor("scores_109_cast_fp16")]; + tensor scores_111_cast_fp16 = select(a = var_48_to_fp16, b = scores_109_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_111_cast_fp16")]; + tensor var_3075_cast_fp16 = softmax(axis = var_61, x = scores_111_cast_fp16)[name = tensor("op_3075_cast_fp16")]; + tensor input_827_cast_fp16 = select(a = var_53_to_fp16, b = var_3075_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_827_cast_fp16")]; + tensor x_281_transpose_x_0 = const()[name = tensor("x_281_transpose_x_0"), val = tensor(false)]; + tensor x_281_transpose_y_0 = const()[name = tensor("x_281_transpose_y_0"), val = tensor(false)]; + tensor value_55_cast_fp16 = transpose(perm = value_55_perm_0, x = var_3048_cast_fp16)[name = tensor("transpose_607")]; + tensor x_281_cast_fp16 = matmul(transpose_x = x_281_transpose_x_0, transpose_y = x_281_transpose_y_0, x = input_827_cast_fp16, y = value_55_cast_fp16)[name = tensor("x_281_cast_fp16")]; + tensor var_3079_perm_0 = const()[name = tensor("op_3079_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3081 = const()[name = tensor("op_3081"), val = tensor([1, -1, 512])]; + tensor var_3079_cast_fp16 = transpose(perm = var_3079_perm_0, x = x_281_cast_fp16)[name = tensor("transpose_602")]; + tensor input_829_cast_fp16 = reshape(shape = var_3081, x = var_3079_cast_fp16)[name = tensor("input_829_cast_fp16")]; + tensor encoder_encoders_26_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_26_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172313600)))]; + tensor encoder_encoders_26_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_26_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172837952)))]; + tensor linear_109_cast_fp16 = linear(bias = encoder_encoders_26_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_26_self_attn_linear_out_weight_to_fp16, x = input_829_cast_fp16)[name = tensor("linear_109_cast_fp16")]; + tensor input_831_cast_fp16 = add(x = linear_109_cast_fp16, y = fsmn_memory_55_cast_fp16)[name = tensor("input_831_cast_fp16")]; + tensor input_833_cast_fp16 = add(x = input_817_cast_fp16, y = input_831_cast_fp16)[name = tensor("input_833_cast_fp16")]; + tensor output_111_axes_0 = const()[name = tensor("output_111_axes_0"), val = tensor([-1])]; + tensor const_172_to_fp16 = const()[name = tensor("const_172_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172839040)))]; + tensor const_173_to_fp16 = const()[name = tensor("const_173_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172840128)))]; + tensor output_111_cast_fp16 = layer_norm(axes = output_111_axes_0, beta = const_173_to_fp16, epsilon = var_46_to_fp16, gamma = const_172_to_fp16, x = input_833_cast_fp16)[name = tensor("output_111_cast_fp16")]; + tensor encoder_encoders_26_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_26_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172841216)))]; + tensor encoder_encoders_26_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_26_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174938432)))]; + tensor linear_110_cast_fp16 = linear(bias = encoder_encoders_26_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_26_feed_forward_w_1_weight_to_fp16, x = output_111_cast_fp16)[name = tensor("linear_110_cast_fp16")]; + tensor input_841_cast_fp16 = relu(x = linear_110_cast_fp16)[name = tensor("input_841_cast_fp16")]; + tensor encoder_encoders_26_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_26_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(174942592)))]; + tensor encoder_encoders_26_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_26_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177039808)))]; + tensor linear_111_cast_fp16 = linear(bias = encoder_encoders_26_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_26_feed_forward_w_2_weight_to_fp16, x = input_841_cast_fp16)[name = tensor("linear_111_cast_fp16")]; + tensor input_847_cast_fp16 = add(x = input_833_cast_fp16, y = linear_111_cast_fp16)[name = tensor("input_847_cast_fp16")]; + tensor output_113_axes_0 = const()[name = tensor("output_113_axes_0"), val = tensor([-1])]; + tensor const_174_to_fp16 = const()[name = tensor("const_174_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177040896)))]; + tensor const_175_to_fp16 = const()[name = tensor("const_175_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177041984)))]; + tensor output_113_cast_fp16 = layer_norm(axes = output_113_axes_0, beta = const_175_to_fp16, epsilon = var_46_to_fp16, gamma = const_174_to_fp16, x = input_847_cast_fp16)[name = tensor("output_113_cast_fp16")]; + tensor encoder_encoders_27_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_27_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177043072)))]; + tensor encoder_encoders_27_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_27_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178616000)))]; + tensor linear_112_cast_fp16 = linear(bias = encoder_encoders_27_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_27_self_attn_linear_q_k_v_weight_to_fp16, x = output_113_cast_fp16)[name = tensor("linear_112_cast_fp16")]; + tensor tile_28 = const()[name = tensor("tile_28"), val = tensor([512, 512, 512])]; + tensor var_3139_axis_0 = const()[name = tensor("op_3139_axis_0"), val = tensor(-1)]; + tensor var_3139_cast_fp16_0, tensor var_3139_cast_fp16_1, tensor var_3139_cast_fp16_2 = split(axis = var_3139_axis_0, split_sizes = tile_28, x = linear_112_cast_fp16)[name = tensor("op_3139_cast_fp16")]; + tensor concat_84x = const()[name = tensor("concat_84x"), val = tensor([1, -1, 4, 128])]; + tensor var_3144_cast_fp16 = reshape(shape = concat_84x, x = var_3139_cast_fp16_0)[name = tensor("op_3144_cast_fp16")]; + tensor concat_85x = const()[name = tensor("concat_85x"), val = tensor([1, -1, 4, 128])]; + tensor var_3147_cast_fp16 = reshape(shape = concat_85x, x = var_3139_cast_fp16_1)[name = tensor("op_3147_cast_fp16")]; + tensor concat_86x = const()[name = tensor("concat_86x"), val = tensor([1, -1, 4, 128])]; + tensor var_3150_cast_fp16 = reshape(shape = concat_86x, x = var_3139_cast_fp16_2)[name = tensor("op_3150_cast_fp16")]; + tensor value_57_perm_0 = const()[name = tensor("value_57_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_57_cast_fp16 = mul(x = var_3139_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_57_cast_fp16")]; + tensor input_851_perm_0 = const()[name = tensor("input_851_perm_0"), val = tensor([0, 2, 1])]; + tensor input_853_pad_0 = const()[name = tensor("input_853_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_853_mode_0 = const()[name = tensor("input_853_mode_0"), val = tensor("constant")]; + tensor const_177_to_fp16 = const()[name = tensor("const_177_to_fp16"), val = tensor(0x0p+0)]; + tensor input_851_cast_fp16 = transpose(perm = input_851_perm_0, x = inputs_57_cast_fp16)[name = tensor("transpose_600")]; + tensor input_853_cast_fp16 = pad(constant_val = const_177_to_fp16, mode = input_853_mode_0, pad = input_853_pad_0, x = input_851_cast_fp16)[name = tensor("input_853_cast_fp16")]; + tensor x_285_pad_type_0 = const()[name = tensor("x_285_pad_type_0"), val = tensor("valid")]; + tensor x_285_groups_0 = const()[name = tensor("x_285_groups_0"), val = tensor(512)]; + tensor x_285_strides_0 = const()[name = tensor("x_285_strides_0"), val = tensor([1])]; + tensor x_285_pad_0 = const()[name = tensor("x_285_pad_0"), val = tensor([0, 0])]; + tensor x_285_dilations_0 = const()[name = tensor("x_285_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_27_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_27_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178619136)))]; + tensor x_285_cast_fp16 = conv(dilations = x_285_dilations_0, groups = x_285_groups_0, pad = x_285_pad_0, pad_type = x_285_pad_type_0, strides = x_285_strides_0, weight = encoder_encoders_27_self_attn_fsmn_block_weight_to_fp16, x = input_853_cast_fp16)[name = tensor("x_285_cast_fp16")]; + tensor x_287_perm_0 = const()[name = tensor("x_287_perm_0"), val = tensor([0, 2, 1])]; + tensor x_287_cast_fp16 = transpose(perm = x_287_perm_0, x = x_285_cast_fp16)[name = tensor("transpose_599")]; + tensor input_855_cast_fp16 = add(x = x_287_cast_fp16, y = inputs_57_cast_fp16)[name = tensor("input_855_cast_fp16")]; + tensor fsmn_memory_57_cast_fp16 = mul(x = input_855_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_57_cast_fp16")]; + tensor var_3169_to_fp16 = const()[name = tensor("op_3169_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_115_cast_fp16 = mul(x = var_3144_cast_fp16, y = var_3169_to_fp16)[name = tensor("q_h_115_cast_fp16")]; + tensor scores_113_transpose_x_0 = const()[name = tensor("scores_113_transpose_x_0"), val = tensor(false)]; + tensor scores_113_transpose_y_0 = const()[name = tensor("scores_113_transpose_y_0"), val = tensor(false)]; + tensor transpose_266_perm_0 = const()[name = tensor("transpose_266_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_267_perm_0 = const()[name = tensor("transpose_267_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_267 = transpose(perm = transpose_267_perm_0, x = var_3147_cast_fp16)[name = tensor("transpose_597")]; + tensor transpose_266 = transpose(perm = transpose_266_perm_0, x = q_h_115_cast_fp16)[name = tensor("transpose_598")]; + tensor scores_113_cast_fp16 = matmul(transpose_x = scores_113_transpose_x_0, transpose_y = scores_113_transpose_y_0, x = transpose_266, y = transpose_267)[name = tensor("scores_113_cast_fp16")]; + tensor scores_115_cast_fp16 = select(a = var_48_to_fp16, b = scores_113_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_115_cast_fp16")]; + tensor var_3177_cast_fp16 = softmax(axis = var_61, x = scores_115_cast_fp16)[name = tensor("op_3177_cast_fp16")]; + tensor input_857_cast_fp16 = select(a = var_53_to_fp16, b = var_3177_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_857_cast_fp16")]; + tensor x_291_transpose_x_0 = const()[name = tensor("x_291_transpose_x_0"), val = tensor(false)]; + tensor x_291_transpose_y_0 = const()[name = tensor("x_291_transpose_y_0"), val = tensor(false)]; + tensor value_57_cast_fp16 = transpose(perm = value_57_perm_0, x = var_3150_cast_fp16)[name = tensor("transpose_601")]; + tensor x_291_cast_fp16 = matmul(transpose_x = x_291_transpose_x_0, transpose_y = x_291_transpose_y_0, x = input_857_cast_fp16, y = value_57_cast_fp16)[name = tensor("x_291_cast_fp16")]; + tensor var_3181_perm_0 = const()[name = tensor("op_3181_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3183 = const()[name = tensor("op_3183"), val = tensor([1, -1, 512])]; + tensor var_3181_cast_fp16 = transpose(perm = var_3181_perm_0, x = x_291_cast_fp16)[name = tensor("transpose_596")]; + tensor input_859_cast_fp16 = reshape(shape = var_3183, x = var_3181_cast_fp16)[name = tensor("input_859_cast_fp16")]; + tensor encoder_encoders_27_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_27_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178630464)))]; + tensor encoder_encoders_27_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_27_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179154816)))]; + tensor linear_113_cast_fp16 = linear(bias = encoder_encoders_27_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_27_self_attn_linear_out_weight_to_fp16, x = input_859_cast_fp16)[name = tensor("linear_113_cast_fp16")]; + tensor input_861_cast_fp16 = add(x = linear_113_cast_fp16, y = fsmn_memory_57_cast_fp16)[name = tensor("input_861_cast_fp16")]; + tensor input_863_cast_fp16 = add(x = input_847_cast_fp16, y = input_861_cast_fp16)[name = tensor("input_863_cast_fp16")]; + tensor output_115_axes_0 = const()[name = tensor("output_115_axes_0"), val = tensor([-1])]; + tensor const_178_to_fp16 = const()[name = tensor("const_178_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179155904)))]; + tensor const_179_to_fp16 = const()[name = tensor("const_179_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179156992)))]; + tensor output_115_cast_fp16 = layer_norm(axes = output_115_axes_0, beta = const_179_to_fp16, epsilon = var_46_to_fp16, gamma = const_178_to_fp16, x = input_863_cast_fp16)[name = tensor("output_115_cast_fp16")]; + tensor encoder_encoders_27_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_27_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179158080)))]; + tensor encoder_encoders_27_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_27_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(181255296)))]; + tensor linear_114_cast_fp16 = linear(bias = encoder_encoders_27_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_27_feed_forward_w_1_weight_to_fp16, x = output_115_cast_fp16)[name = tensor("linear_114_cast_fp16")]; + tensor input_871_cast_fp16 = relu(x = linear_114_cast_fp16)[name = tensor("input_871_cast_fp16")]; + tensor encoder_encoders_27_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_27_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(181259456)))]; + tensor encoder_encoders_27_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_27_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183356672)))]; + tensor linear_115_cast_fp16 = linear(bias = encoder_encoders_27_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_27_feed_forward_w_2_weight_to_fp16, x = input_871_cast_fp16)[name = tensor("linear_115_cast_fp16")]; + tensor input_877_cast_fp16 = add(x = input_863_cast_fp16, y = linear_115_cast_fp16)[name = tensor("input_877_cast_fp16")]; + tensor output_117_axes_0 = const()[name = tensor("output_117_axes_0"), val = tensor([-1])]; + tensor const_180_to_fp16 = const()[name = tensor("const_180_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183357760)))]; + tensor const_181_to_fp16 = const()[name = tensor("const_181_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183358848)))]; + tensor output_117_cast_fp16 = layer_norm(axes = output_117_axes_0, beta = const_181_to_fp16, epsilon = var_46_to_fp16, gamma = const_180_to_fp16, x = input_877_cast_fp16)[name = tensor("output_117_cast_fp16")]; + tensor encoder_encoders_28_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_28_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183359936)))]; + tensor encoder_encoders_28_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_28_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184932864)))]; + tensor linear_116_cast_fp16 = linear(bias = encoder_encoders_28_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_28_self_attn_linear_q_k_v_weight_to_fp16, x = output_117_cast_fp16)[name = tensor("linear_116_cast_fp16")]; + tensor tile_29 = const()[name = tensor("tile_29"), val = tensor([512, 512, 512])]; + tensor var_3241_axis_0 = const()[name = tensor("op_3241_axis_0"), val = tensor(-1)]; + tensor var_3241_cast_fp16_0, tensor var_3241_cast_fp16_1, tensor var_3241_cast_fp16_2 = split(axis = var_3241_axis_0, split_sizes = tile_29, x = linear_116_cast_fp16)[name = tensor("op_3241_cast_fp16")]; + tensor concat_87x = const()[name = tensor("concat_87x"), val = tensor([1, -1, 4, 128])]; + tensor var_3246_cast_fp16 = reshape(shape = concat_87x, x = var_3241_cast_fp16_0)[name = tensor("op_3246_cast_fp16")]; + tensor concat_88x = const()[name = tensor("concat_88x"), val = tensor([1, -1, 4, 128])]; + tensor var_3249_cast_fp16 = reshape(shape = concat_88x, x = var_3241_cast_fp16_1)[name = tensor("op_3249_cast_fp16")]; + tensor concat_89x = const()[name = tensor("concat_89x"), val = tensor([1, -1, 4, 128])]; + tensor var_3252_cast_fp16 = reshape(shape = concat_89x, x = var_3241_cast_fp16_2)[name = tensor("op_3252_cast_fp16")]; + tensor value_59_perm_0 = const()[name = tensor("value_59_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_59_cast_fp16 = mul(x = var_3241_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_59_cast_fp16")]; + tensor input_881_perm_0 = const()[name = tensor("input_881_perm_0"), val = tensor([0, 2, 1])]; + tensor input_883_pad_0 = const()[name = tensor("input_883_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_883_mode_0 = const()[name = tensor("input_883_mode_0"), val = tensor("constant")]; + tensor const_183_to_fp16 = const()[name = tensor("const_183_to_fp16"), val = tensor(0x0p+0)]; + tensor input_881_cast_fp16 = transpose(perm = input_881_perm_0, x = inputs_59_cast_fp16)[name = tensor("transpose_594")]; + tensor input_883_cast_fp16 = pad(constant_val = const_183_to_fp16, mode = input_883_mode_0, pad = input_883_pad_0, x = input_881_cast_fp16)[name = tensor("input_883_cast_fp16")]; + tensor x_295_pad_type_0 = const()[name = tensor("x_295_pad_type_0"), val = tensor("valid")]; + tensor x_295_groups_0 = const()[name = tensor("x_295_groups_0"), val = tensor(512)]; + tensor x_295_strides_0 = const()[name = tensor("x_295_strides_0"), val = tensor([1])]; + tensor x_295_pad_0 = const()[name = tensor("x_295_pad_0"), val = tensor([0, 0])]; + tensor x_295_dilations_0 = const()[name = tensor("x_295_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_28_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_28_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184936000)))]; + tensor x_295_cast_fp16 = conv(dilations = x_295_dilations_0, groups = x_295_groups_0, pad = x_295_pad_0, pad_type = x_295_pad_type_0, strides = x_295_strides_0, weight = encoder_encoders_28_self_attn_fsmn_block_weight_to_fp16, x = input_883_cast_fp16)[name = tensor("x_295_cast_fp16")]; + tensor x_297_perm_0 = const()[name = tensor("x_297_perm_0"), val = tensor([0, 2, 1])]; + tensor x_297_cast_fp16 = transpose(perm = x_297_perm_0, x = x_295_cast_fp16)[name = tensor("transpose_593")]; + tensor input_885_cast_fp16 = add(x = x_297_cast_fp16, y = inputs_59_cast_fp16)[name = tensor("input_885_cast_fp16")]; + tensor fsmn_memory_59_cast_fp16 = mul(x = input_885_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_59_cast_fp16")]; + tensor var_3271_to_fp16 = const()[name = tensor("op_3271_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_119_cast_fp16 = mul(x = var_3246_cast_fp16, y = var_3271_to_fp16)[name = tensor("q_h_119_cast_fp16")]; + tensor scores_117_transpose_x_0 = const()[name = tensor("scores_117_transpose_x_0"), val = tensor(false)]; + tensor scores_117_transpose_y_0 = const()[name = tensor("scores_117_transpose_y_0"), val = tensor(false)]; + tensor transpose_268_perm_0 = const()[name = tensor("transpose_268_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_269_perm_0 = const()[name = tensor("transpose_269_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_269 = transpose(perm = transpose_269_perm_0, x = var_3249_cast_fp16)[name = tensor("transpose_591")]; + tensor transpose_268 = transpose(perm = transpose_268_perm_0, x = q_h_119_cast_fp16)[name = tensor("transpose_592")]; + tensor scores_117_cast_fp16 = matmul(transpose_x = scores_117_transpose_x_0, transpose_y = scores_117_transpose_y_0, x = transpose_268, y = transpose_269)[name = tensor("scores_117_cast_fp16")]; + tensor scores_119_cast_fp16 = select(a = var_48_to_fp16, b = scores_117_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_119_cast_fp16")]; + tensor var_3279_cast_fp16 = softmax(axis = var_61, x = scores_119_cast_fp16)[name = tensor("op_3279_cast_fp16")]; + tensor input_887_cast_fp16 = select(a = var_53_to_fp16, b = var_3279_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_887_cast_fp16")]; + tensor x_301_transpose_x_0 = const()[name = tensor("x_301_transpose_x_0"), val = tensor(false)]; + tensor x_301_transpose_y_0 = const()[name = tensor("x_301_transpose_y_0"), val = tensor(false)]; + tensor value_59_cast_fp16 = transpose(perm = value_59_perm_0, x = var_3252_cast_fp16)[name = tensor("transpose_595")]; + tensor x_301_cast_fp16 = matmul(transpose_x = x_301_transpose_x_0, transpose_y = x_301_transpose_y_0, x = input_887_cast_fp16, y = value_59_cast_fp16)[name = tensor("x_301_cast_fp16")]; + tensor var_3283_perm_0 = const()[name = tensor("op_3283_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3285 = const()[name = tensor("op_3285"), val = tensor([1, -1, 512])]; + tensor var_3283_cast_fp16 = transpose(perm = var_3283_perm_0, x = x_301_cast_fp16)[name = tensor("transpose_590")]; + tensor input_889_cast_fp16 = reshape(shape = var_3285, x = var_3283_cast_fp16)[name = tensor("input_889_cast_fp16")]; + tensor encoder_encoders_28_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_28_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(184947328)))]; + tensor encoder_encoders_28_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_28_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185471680)))]; + tensor linear_117_cast_fp16 = linear(bias = encoder_encoders_28_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_28_self_attn_linear_out_weight_to_fp16, x = input_889_cast_fp16)[name = tensor("linear_117_cast_fp16")]; + tensor input_891_cast_fp16 = add(x = linear_117_cast_fp16, y = fsmn_memory_59_cast_fp16)[name = tensor("input_891_cast_fp16")]; + tensor input_893_cast_fp16 = add(x = input_877_cast_fp16, y = input_891_cast_fp16)[name = tensor("input_893_cast_fp16")]; + tensor output_119_axes_0 = const()[name = tensor("output_119_axes_0"), val = tensor([-1])]; + tensor const_184_to_fp16 = const()[name = tensor("const_184_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185472768)))]; + tensor const_185_to_fp16 = const()[name = tensor("const_185_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185473856)))]; + tensor output_119_cast_fp16 = layer_norm(axes = output_119_axes_0, beta = const_185_to_fp16, epsilon = var_46_to_fp16, gamma = const_184_to_fp16, x = input_893_cast_fp16)[name = tensor("output_119_cast_fp16")]; + tensor encoder_encoders_28_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_28_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185474944)))]; + tensor encoder_encoders_28_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_28_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(187572160)))]; + tensor linear_118_cast_fp16 = linear(bias = encoder_encoders_28_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_28_feed_forward_w_1_weight_to_fp16, x = output_119_cast_fp16)[name = tensor("linear_118_cast_fp16")]; + tensor input_901_cast_fp16 = relu(x = linear_118_cast_fp16)[name = tensor("input_901_cast_fp16")]; + tensor encoder_encoders_28_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_28_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(187576320)))]; + tensor encoder_encoders_28_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_28_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189673536)))]; + tensor linear_119_cast_fp16 = linear(bias = encoder_encoders_28_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_28_feed_forward_w_2_weight_to_fp16, x = input_901_cast_fp16)[name = tensor("linear_119_cast_fp16")]; + tensor input_907_cast_fp16 = add(x = input_893_cast_fp16, y = linear_119_cast_fp16)[name = tensor("input_907_cast_fp16")]; + tensor output_121_axes_0 = const()[name = tensor("output_121_axes_0"), val = tensor([-1])]; + tensor const_186_to_fp16 = const()[name = tensor("const_186_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189674624)))]; + tensor const_187_to_fp16 = const()[name = tensor("const_187_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189675712)))]; + tensor output_121_cast_fp16 = layer_norm(axes = output_121_axes_0, beta = const_187_to_fp16, epsilon = var_46_to_fp16, gamma = const_186_to_fp16, x = input_907_cast_fp16)[name = tensor("output_121_cast_fp16")]; + tensor encoder_encoders_29_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_29_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189676800)))]; + tensor encoder_encoders_29_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_29_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191249728)))]; + tensor linear_120_cast_fp16 = linear(bias = encoder_encoders_29_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_29_self_attn_linear_q_k_v_weight_to_fp16, x = output_121_cast_fp16)[name = tensor("linear_120_cast_fp16")]; + tensor tile_30 = const()[name = tensor("tile_30"), val = tensor([512, 512, 512])]; + tensor var_3343_axis_0 = const()[name = tensor("op_3343_axis_0"), val = tensor(-1)]; + tensor var_3343_cast_fp16_0, tensor var_3343_cast_fp16_1, tensor var_3343_cast_fp16_2 = split(axis = var_3343_axis_0, split_sizes = tile_30, x = linear_120_cast_fp16)[name = tensor("op_3343_cast_fp16")]; + tensor concat_90x = const()[name = tensor("concat_90x"), val = tensor([1, -1, 4, 128])]; + tensor var_3348_cast_fp16 = reshape(shape = concat_90x, x = var_3343_cast_fp16_0)[name = tensor("op_3348_cast_fp16")]; + tensor concat_91x = const()[name = tensor("concat_91x"), val = tensor([1, -1, 4, 128])]; + tensor var_3351_cast_fp16 = reshape(shape = concat_91x, x = var_3343_cast_fp16_1)[name = tensor("op_3351_cast_fp16")]; + tensor concat_92x = const()[name = tensor("concat_92x"), val = tensor([1, -1, 4, 128])]; + tensor var_3354_cast_fp16 = reshape(shape = concat_92x, x = var_3343_cast_fp16_2)[name = tensor("op_3354_cast_fp16")]; + tensor value_61_perm_0 = const()[name = tensor("value_61_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_61_cast_fp16 = mul(x = var_3343_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_61_cast_fp16")]; + tensor input_911_perm_0 = const()[name = tensor("input_911_perm_0"), val = tensor([0, 2, 1])]; + tensor input_913_pad_0 = const()[name = tensor("input_913_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_913_mode_0 = const()[name = tensor("input_913_mode_0"), val = tensor("constant")]; + tensor const_189_to_fp16 = const()[name = tensor("const_189_to_fp16"), val = tensor(0x0p+0)]; + tensor input_911_cast_fp16 = transpose(perm = input_911_perm_0, x = inputs_61_cast_fp16)[name = tensor("transpose_588")]; + tensor input_913_cast_fp16 = pad(constant_val = const_189_to_fp16, mode = input_913_mode_0, pad = input_913_pad_0, x = input_911_cast_fp16)[name = tensor("input_913_cast_fp16")]; + tensor x_305_pad_type_0 = const()[name = tensor("x_305_pad_type_0"), val = tensor("valid")]; + tensor x_305_groups_0 = const()[name = tensor("x_305_groups_0"), val = tensor(512)]; + tensor x_305_strides_0 = const()[name = tensor("x_305_strides_0"), val = tensor([1])]; + tensor x_305_pad_0 = const()[name = tensor("x_305_pad_0"), val = tensor([0, 0])]; + tensor x_305_dilations_0 = const()[name = tensor("x_305_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_29_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_29_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191252864)))]; + tensor x_305_cast_fp16 = conv(dilations = x_305_dilations_0, groups = x_305_groups_0, pad = x_305_pad_0, pad_type = x_305_pad_type_0, strides = x_305_strides_0, weight = encoder_encoders_29_self_attn_fsmn_block_weight_to_fp16, x = input_913_cast_fp16)[name = tensor("x_305_cast_fp16")]; + tensor x_307_perm_0 = const()[name = tensor("x_307_perm_0"), val = tensor([0, 2, 1])]; + tensor x_307_cast_fp16 = transpose(perm = x_307_perm_0, x = x_305_cast_fp16)[name = tensor("transpose_587")]; + tensor input_915_cast_fp16 = add(x = x_307_cast_fp16, y = inputs_61_cast_fp16)[name = tensor("input_915_cast_fp16")]; + tensor fsmn_memory_61_cast_fp16 = mul(x = input_915_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_61_cast_fp16")]; + tensor var_3373_to_fp16 = const()[name = tensor("op_3373_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_123_cast_fp16 = mul(x = var_3348_cast_fp16, y = var_3373_to_fp16)[name = tensor("q_h_123_cast_fp16")]; + tensor scores_121_transpose_x_0 = const()[name = tensor("scores_121_transpose_x_0"), val = tensor(false)]; + tensor scores_121_transpose_y_0 = const()[name = tensor("scores_121_transpose_y_0"), val = tensor(false)]; + tensor transpose_270_perm_0 = const()[name = tensor("transpose_270_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_271_perm_0 = const()[name = tensor("transpose_271_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_271 = transpose(perm = transpose_271_perm_0, x = var_3351_cast_fp16)[name = tensor("transpose_585")]; + tensor transpose_270 = transpose(perm = transpose_270_perm_0, x = q_h_123_cast_fp16)[name = tensor("transpose_586")]; + tensor scores_121_cast_fp16 = matmul(transpose_x = scores_121_transpose_x_0, transpose_y = scores_121_transpose_y_0, x = transpose_270, y = transpose_271)[name = tensor("scores_121_cast_fp16")]; + tensor scores_123_cast_fp16 = select(a = var_48_to_fp16, b = scores_121_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_123_cast_fp16")]; + tensor var_3381_cast_fp16 = softmax(axis = var_61, x = scores_123_cast_fp16)[name = tensor("op_3381_cast_fp16")]; + tensor input_917_cast_fp16 = select(a = var_53_to_fp16, b = var_3381_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_917_cast_fp16")]; + tensor x_311_transpose_x_0 = const()[name = tensor("x_311_transpose_x_0"), val = tensor(false)]; + tensor x_311_transpose_y_0 = const()[name = tensor("x_311_transpose_y_0"), val = tensor(false)]; + tensor value_61_cast_fp16 = transpose(perm = value_61_perm_0, x = var_3354_cast_fp16)[name = tensor("transpose_589")]; + tensor x_311_cast_fp16 = matmul(transpose_x = x_311_transpose_x_0, transpose_y = x_311_transpose_y_0, x = input_917_cast_fp16, y = value_61_cast_fp16)[name = tensor("x_311_cast_fp16")]; + tensor var_3385_perm_0 = const()[name = tensor("op_3385_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3387 = const()[name = tensor("op_3387"), val = tensor([1, -1, 512])]; + tensor var_3385_cast_fp16 = transpose(perm = var_3385_perm_0, x = x_311_cast_fp16)[name = tensor("transpose_584")]; + tensor input_919_cast_fp16 = reshape(shape = var_3387, x = var_3385_cast_fp16)[name = tensor("input_919_cast_fp16")]; + tensor encoder_encoders_29_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_29_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191264192)))]; + tensor encoder_encoders_29_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_29_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191788544)))]; + tensor linear_121_cast_fp16 = linear(bias = encoder_encoders_29_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_29_self_attn_linear_out_weight_to_fp16, x = input_919_cast_fp16)[name = tensor("linear_121_cast_fp16")]; + tensor input_921_cast_fp16 = add(x = linear_121_cast_fp16, y = fsmn_memory_61_cast_fp16)[name = tensor("input_921_cast_fp16")]; + tensor input_923_cast_fp16 = add(x = input_907_cast_fp16, y = input_921_cast_fp16)[name = tensor("input_923_cast_fp16")]; + tensor output_123_axes_0 = const()[name = tensor("output_123_axes_0"), val = tensor([-1])]; + tensor const_190_to_fp16 = const()[name = tensor("const_190_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191789632)))]; + tensor const_191_to_fp16 = const()[name = tensor("const_191_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191790720)))]; + tensor output_123_cast_fp16 = layer_norm(axes = output_123_axes_0, beta = const_191_to_fp16, epsilon = var_46_to_fp16, gamma = const_190_to_fp16, x = input_923_cast_fp16)[name = tensor("output_123_cast_fp16")]; + tensor encoder_encoders_29_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_29_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191791808)))]; + tensor encoder_encoders_29_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_29_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(193889024)))]; + tensor linear_122_cast_fp16 = linear(bias = encoder_encoders_29_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_29_feed_forward_w_1_weight_to_fp16, x = output_123_cast_fp16)[name = tensor("linear_122_cast_fp16")]; + tensor input_931_cast_fp16 = relu(x = linear_122_cast_fp16)[name = tensor("input_931_cast_fp16")]; + tensor encoder_encoders_29_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_29_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(193893184)))]; + tensor encoder_encoders_29_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_29_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195990400)))]; + tensor linear_123_cast_fp16 = linear(bias = encoder_encoders_29_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_29_feed_forward_w_2_weight_to_fp16, x = input_931_cast_fp16)[name = tensor("linear_123_cast_fp16")]; + tensor input_937_cast_fp16 = add(x = input_923_cast_fp16, y = linear_123_cast_fp16)[name = tensor("input_937_cast_fp16")]; + tensor output_125_axes_0 = const()[name = tensor("output_125_axes_0"), val = tensor([-1])]; + tensor const_192_to_fp16 = const()[name = tensor("const_192_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195991488)))]; + tensor const_193_to_fp16 = const()[name = tensor("const_193_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195992576)))]; + tensor output_125_cast_fp16 = layer_norm(axes = output_125_axes_0, beta = const_193_to_fp16, epsilon = var_46_to_fp16, gamma = const_192_to_fp16, x = input_937_cast_fp16)[name = tensor("output_125_cast_fp16")]; + tensor encoder_encoders_30_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_30_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195993664)))]; + tensor encoder_encoders_30_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_30_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(197566592)))]; + tensor linear_124_cast_fp16 = linear(bias = encoder_encoders_30_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_30_self_attn_linear_q_k_v_weight_to_fp16, x = output_125_cast_fp16)[name = tensor("linear_124_cast_fp16")]; + tensor tile_31 = const()[name = tensor("tile_31"), val = tensor([512, 512, 512])]; + tensor var_3445_axis_0 = const()[name = tensor("op_3445_axis_0"), val = tensor(-1)]; + tensor var_3445_cast_fp16_0, tensor var_3445_cast_fp16_1, tensor var_3445_cast_fp16_2 = split(axis = var_3445_axis_0, split_sizes = tile_31, x = linear_124_cast_fp16)[name = tensor("op_3445_cast_fp16")]; + tensor concat_93x = const()[name = tensor("concat_93x"), val = tensor([1, -1, 4, 128])]; + tensor var_3450_cast_fp16 = reshape(shape = concat_93x, x = var_3445_cast_fp16_0)[name = tensor("op_3450_cast_fp16")]; + tensor concat_94x = const()[name = tensor("concat_94x"), val = tensor([1, -1, 4, 128])]; + tensor var_3453_cast_fp16 = reshape(shape = concat_94x, x = var_3445_cast_fp16_1)[name = tensor("op_3453_cast_fp16")]; + tensor concat_95x = const()[name = tensor("concat_95x"), val = tensor([1, -1, 4, 128])]; + tensor var_3456_cast_fp16 = reshape(shape = concat_95x, x = var_3445_cast_fp16_2)[name = tensor("op_3456_cast_fp16")]; + tensor value_63_perm_0 = const()[name = tensor("value_63_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_63_cast_fp16 = mul(x = var_3445_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_63_cast_fp16")]; + tensor input_941_perm_0 = const()[name = tensor("input_941_perm_0"), val = tensor([0, 2, 1])]; + tensor input_943_pad_0 = const()[name = tensor("input_943_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_943_mode_0 = const()[name = tensor("input_943_mode_0"), val = tensor("constant")]; + tensor const_195_to_fp16 = const()[name = tensor("const_195_to_fp16"), val = tensor(0x0p+0)]; + tensor input_941_cast_fp16 = transpose(perm = input_941_perm_0, x = inputs_63_cast_fp16)[name = tensor("transpose_582")]; + tensor input_943_cast_fp16 = pad(constant_val = const_195_to_fp16, mode = input_943_mode_0, pad = input_943_pad_0, x = input_941_cast_fp16)[name = tensor("input_943_cast_fp16")]; + tensor x_315_pad_type_0 = const()[name = tensor("x_315_pad_type_0"), val = tensor("valid")]; + tensor x_315_groups_0 = const()[name = tensor("x_315_groups_0"), val = tensor(512)]; + tensor x_315_strides_0 = const()[name = tensor("x_315_strides_0"), val = tensor([1])]; + tensor x_315_pad_0 = const()[name = tensor("x_315_pad_0"), val = tensor([0, 0])]; + tensor x_315_dilations_0 = const()[name = tensor("x_315_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_30_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_30_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(197569728)))]; + tensor x_315_cast_fp16 = conv(dilations = x_315_dilations_0, groups = x_315_groups_0, pad = x_315_pad_0, pad_type = x_315_pad_type_0, strides = x_315_strides_0, weight = encoder_encoders_30_self_attn_fsmn_block_weight_to_fp16, x = input_943_cast_fp16)[name = tensor("x_315_cast_fp16")]; + tensor x_317_perm_0 = const()[name = tensor("x_317_perm_0"), val = tensor([0, 2, 1])]; + tensor x_317_cast_fp16 = transpose(perm = x_317_perm_0, x = x_315_cast_fp16)[name = tensor("transpose_581")]; + tensor input_945_cast_fp16 = add(x = x_317_cast_fp16, y = inputs_63_cast_fp16)[name = tensor("input_945_cast_fp16")]; + tensor fsmn_memory_63_cast_fp16 = mul(x = input_945_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_63_cast_fp16")]; + tensor var_3475_to_fp16 = const()[name = tensor("op_3475_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_127_cast_fp16 = mul(x = var_3450_cast_fp16, y = var_3475_to_fp16)[name = tensor("q_h_127_cast_fp16")]; + tensor scores_125_transpose_x_0 = const()[name = tensor("scores_125_transpose_x_0"), val = tensor(false)]; + tensor scores_125_transpose_y_0 = const()[name = tensor("scores_125_transpose_y_0"), val = tensor(false)]; + tensor transpose_272_perm_0 = const()[name = tensor("transpose_272_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_273_perm_0 = const()[name = tensor("transpose_273_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_273 = transpose(perm = transpose_273_perm_0, x = var_3453_cast_fp16)[name = tensor("transpose_579")]; + tensor transpose_272 = transpose(perm = transpose_272_perm_0, x = q_h_127_cast_fp16)[name = tensor("transpose_580")]; + tensor scores_125_cast_fp16 = matmul(transpose_x = scores_125_transpose_x_0, transpose_y = scores_125_transpose_y_0, x = transpose_272, y = transpose_273)[name = tensor("scores_125_cast_fp16")]; + tensor scores_127_cast_fp16 = select(a = var_48_to_fp16, b = scores_125_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_127_cast_fp16")]; + tensor var_3483_cast_fp16 = softmax(axis = var_61, x = scores_127_cast_fp16)[name = tensor("op_3483_cast_fp16")]; + tensor input_947_cast_fp16 = select(a = var_53_to_fp16, b = var_3483_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_947_cast_fp16")]; + tensor x_321_transpose_x_0 = const()[name = tensor("x_321_transpose_x_0"), val = tensor(false)]; + tensor x_321_transpose_y_0 = const()[name = tensor("x_321_transpose_y_0"), val = tensor(false)]; + tensor value_63_cast_fp16 = transpose(perm = value_63_perm_0, x = var_3456_cast_fp16)[name = tensor("transpose_583")]; + tensor x_321_cast_fp16 = matmul(transpose_x = x_321_transpose_x_0, transpose_y = x_321_transpose_y_0, x = input_947_cast_fp16, y = value_63_cast_fp16)[name = tensor("x_321_cast_fp16")]; + tensor var_3487_perm_0 = const()[name = tensor("op_3487_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3489 = const()[name = tensor("op_3489"), val = tensor([1, -1, 512])]; + tensor var_3487_cast_fp16 = transpose(perm = var_3487_perm_0, x = x_321_cast_fp16)[name = tensor("transpose_578")]; + tensor input_949_cast_fp16 = reshape(shape = var_3489, x = var_3487_cast_fp16)[name = tensor("input_949_cast_fp16")]; + tensor encoder_encoders_30_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_30_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(197581056)))]; + tensor encoder_encoders_30_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_30_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198105408)))]; + tensor linear_125_cast_fp16 = linear(bias = encoder_encoders_30_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_30_self_attn_linear_out_weight_to_fp16, x = input_949_cast_fp16)[name = tensor("linear_125_cast_fp16")]; + tensor input_951_cast_fp16 = add(x = linear_125_cast_fp16, y = fsmn_memory_63_cast_fp16)[name = tensor("input_951_cast_fp16")]; + tensor input_953_cast_fp16 = add(x = input_937_cast_fp16, y = input_951_cast_fp16)[name = tensor("input_953_cast_fp16")]; + tensor output_127_axes_0 = const()[name = tensor("output_127_axes_0"), val = tensor([-1])]; + tensor const_196_to_fp16 = const()[name = tensor("const_196_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198106496)))]; + tensor const_197_to_fp16 = const()[name = tensor("const_197_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198107584)))]; + tensor output_127_cast_fp16 = layer_norm(axes = output_127_axes_0, beta = const_197_to_fp16, epsilon = var_46_to_fp16, gamma = const_196_to_fp16, x = input_953_cast_fp16)[name = tensor("output_127_cast_fp16")]; + tensor encoder_encoders_30_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_30_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198108672)))]; + tensor encoder_encoders_30_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_30_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200205888)))]; + tensor linear_126_cast_fp16 = linear(bias = encoder_encoders_30_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_30_feed_forward_w_1_weight_to_fp16, x = output_127_cast_fp16)[name = tensor("linear_126_cast_fp16")]; + tensor input_961_cast_fp16 = relu(x = linear_126_cast_fp16)[name = tensor("input_961_cast_fp16")]; + tensor encoder_encoders_30_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_30_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200210048)))]; + tensor encoder_encoders_30_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_30_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202307264)))]; + tensor linear_127_cast_fp16 = linear(bias = encoder_encoders_30_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_30_feed_forward_w_2_weight_to_fp16, x = input_961_cast_fp16)[name = tensor("linear_127_cast_fp16")]; + tensor input_967_cast_fp16 = add(x = input_953_cast_fp16, y = linear_127_cast_fp16)[name = tensor("input_967_cast_fp16")]; + tensor output_129_axes_0 = const()[name = tensor("output_129_axes_0"), val = tensor([-1])]; + tensor const_198_to_fp16 = const()[name = tensor("const_198_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202308352)))]; + tensor const_199_to_fp16 = const()[name = tensor("const_199_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202309440)))]; + tensor output_129_cast_fp16 = layer_norm(axes = output_129_axes_0, beta = const_199_to_fp16, epsilon = var_46_to_fp16, gamma = const_198_to_fp16, x = input_967_cast_fp16)[name = tensor("output_129_cast_fp16")]; + tensor encoder_encoders_31_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_31_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202310528)))]; + tensor encoder_encoders_31_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_31_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203883456)))]; + tensor linear_128_cast_fp16 = linear(bias = encoder_encoders_31_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_31_self_attn_linear_q_k_v_weight_to_fp16, x = output_129_cast_fp16)[name = tensor("linear_128_cast_fp16")]; + tensor tile_32 = const()[name = tensor("tile_32"), val = tensor([512, 512, 512])]; + tensor var_3547_axis_0 = const()[name = tensor("op_3547_axis_0"), val = tensor(-1)]; + tensor var_3547_cast_fp16_0, tensor var_3547_cast_fp16_1, tensor var_3547_cast_fp16_2 = split(axis = var_3547_axis_0, split_sizes = tile_32, x = linear_128_cast_fp16)[name = tensor("op_3547_cast_fp16")]; + tensor concat_96x = const()[name = tensor("concat_96x"), val = tensor([1, -1, 4, 128])]; + tensor var_3552_cast_fp16 = reshape(shape = concat_96x, x = var_3547_cast_fp16_0)[name = tensor("op_3552_cast_fp16")]; + tensor concat_97x = const()[name = tensor("concat_97x"), val = tensor([1, -1, 4, 128])]; + tensor var_3555_cast_fp16 = reshape(shape = concat_97x, x = var_3547_cast_fp16_1)[name = tensor("op_3555_cast_fp16")]; + tensor concat_98x = const()[name = tensor("concat_98x"), val = tensor([1, -1, 4, 128])]; + tensor var_3558_cast_fp16 = reshape(shape = concat_98x, x = var_3547_cast_fp16_2)[name = tensor("op_3558_cast_fp16")]; + tensor value_65_perm_0 = const()[name = tensor("value_65_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_65_cast_fp16 = mul(x = var_3547_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_65_cast_fp16")]; + tensor input_971_perm_0 = const()[name = tensor("input_971_perm_0"), val = tensor([0, 2, 1])]; + tensor input_973_pad_0 = const()[name = tensor("input_973_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_973_mode_0 = const()[name = tensor("input_973_mode_0"), val = tensor("constant")]; + tensor const_201_to_fp16 = const()[name = tensor("const_201_to_fp16"), val = tensor(0x0p+0)]; + tensor input_971_cast_fp16 = transpose(perm = input_971_perm_0, x = inputs_65_cast_fp16)[name = tensor("transpose_576")]; + tensor input_973_cast_fp16 = pad(constant_val = const_201_to_fp16, mode = input_973_mode_0, pad = input_973_pad_0, x = input_971_cast_fp16)[name = tensor("input_973_cast_fp16")]; + tensor x_325_pad_type_0 = const()[name = tensor("x_325_pad_type_0"), val = tensor("valid")]; + tensor x_325_groups_0 = const()[name = tensor("x_325_groups_0"), val = tensor(512)]; + tensor x_325_strides_0 = const()[name = tensor("x_325_strides_0"), val = tensor([1])]; + tensor x_325_pad_0 = const()[name = tensor("x_325_pad_0"), val = tensor([0, 0])]; + tensor x_325_dilations_0 = const()[name = tensor("x_325_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_31_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_31_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203886592)))]; + tensor x_325_cast_fp16 = conv(dilations = x_325_dilations_0, groups = x_325_groups_0, pad = x_325_pad_0, pad_type = x_325_pad_type_0, strides = x_325_strides_0, weight = encoder_encoders_31_self_attn_fsmn_block_weight_to_fp16, x = input_973_cast_fp16)[name = tensor("x_325_cast_fp16")]; + tensor x_327_perm_0 = const()[name = tensor("x_327_perm_0"), val = tensor([0, 2, 1])]; + tensor x_327_cast_fp16 = transpose(perm = x_327_perm_0, x = x_325_cast_fp16)[name = tensor("transpose_575")]; + tensor input_975_cast_fp16 = add(x = x_327_cast_fp16, y = inputs_65_cast_fp16)[name = tensor("input_975_cast_fp16")]; + tensor fsmn_memory_65_cast_fp16 = mul(x = input_975_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_65_cast_fp16")]; + tensor var_3577_to_fp16 = const()[name = tensor("op_3577_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_131_cast_fp16 = mul(x = var_3552_cast_fp16, y = var_3577_to_fp16)[name = tensor("q_h_131_cast_fp16")]; + tensor scores_129_transpose_x_0 = const()[name = tensor("scores_129_transpose_x_0"), val = tensor(false)]; + tensor scores_129_transpose_y_0 = const()[name = tensor("scores_129_transpose_y_0"), val = tensor(false)]; + tensor transpose_274_perm_0 = const()[name = tensor("transpose_274_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_275_perm_0 = const()[name = tensor("transpose_275_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_275 = transpose(perm = transpose_275_perm_0, x = var_3555_cast_fp16)[name = tensor("transpose_573")]; + tensor transpose_274 = transpose(perm = transpose_274_perm_0, x = q_h_131_cast_fp16)[name = tensor("transpose_574")]; + tensor scores_129_cast_fp16 = matmul(transpose_x = scores_129_transpose_x_0, transpose_y = scores_129_transpose_y_0, x = transpose_274, y = transpose_275)[name = tensor("scores_129_cast_fp16")]; + tensor scores_131_cast_fp16 = select(a = var_48_to_fp16, b = scores_129_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_131_cast_fp16")]; + tensor var_3585_cast_fp16 = softmax(axis = var_61, x = scores_131_cast_fp16)[name = tensor("op_3585_cast_fp16")]; + tensor input_977_cast_fp16 = select(a = var_53_to_fp16, b = var_3585_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_977_cast_fp16")]; + tensor x_331_transpose_x_0 = const()[name = tensor("x_331_transpose_x_0"), val = tensor(false)]; + tensor x_331_transpose_y_0 = const()[name = tensor("x_331_transpose_y_0"), val = tensor(false)]; + tensor value_65_cast_fp16 = transpose(perm = value_65_perm_0, x = var_3558_cast_fp16)[name = tensor("transpose_577")]; + tensor x_331_cast_fp16 = matmul(transpose_x = x_331_transpose_x_0, transpose_y = x_331_transpose_y_0, x = input_977_cast_fp16, y = value_65_cast_fp16)[name = tensor("x_331_cast_fp16")]; + tensor var_3589_perm_0 = const()[name = tensor("op_3589_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3591 = const()[name = tensor("op_3591"), val = tensor([1, -1, 512])]; + tensor var_3589_cast_fp16 = transpose(perm = var_3589_perm_0, x = x_331_cast_fp16)[name = tensor("transpose_572")]; + tensor input_979_cast_fp16 = reshape(shape = var_3591, x = var_3589_cast_fp16)[name = tensor("input_979_cast_fp16")]; + tensor encoder_encoders_31_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_31_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203897920)))]; + tensor encoder_encoders_31_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_31_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204422272)))]; + tensor linear_129_cast_fp16 = linear(bias = encoder_encoders_31_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_31_self_attn_linear_out_weight_to_fp16, x = input_979_cast_fp16)[name = tensor("linear_129_cast_fp16")]; + tensor input_981_cast_fp16 = add(x = linear_129_cast_fp16, y = fsmn_memory_65_cast_fp16)[name = tensor("input_981_cast_fp16")]; + tensor input_983_cast_fp16 = add(x = input_967_cast_fp16, y = input_981_cast_fp16)[name = tensor("input_983_cast_fp16")]; + tensor output_131_axes_0 = const()[name = tensor("output_131_axes_0"), val = tensor([-1])]; + tensor const_202_to_fp16 = const()[name = tensor("const_202_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204423360)))]; + tensor const_203_to_fp16 = const()[name = tensor("const_203_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204424448)))]; + tensor output_131_cast_fp16 = layer_norm(axes = output_131_axes_0, beta = const_203_to_fp16, epsilon = var_46_to_fp16, gamma = const_202_to_fp16, x = input_983_cast_fp16)[name = tensor("output_131_cast_fp16")]; + tensor encoder_encoders_31_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_31_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204425536)))]; + tensor encoder_encoders_31_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_31_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(206522752)))]; + tensor linear_130_cast_fp16 = linear(bias = encoder_encoders_31_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_31_feed_forward_w_1_weight_to_fp16, x = output_131_cast_fp16)[name = tensor("linear_130_cast_fp16")]; + tensor input_991_cast_fp16 = relu(x = linear_130_cast_fp16)[name = tensor("input_991_cast_fp16")]; + tensor encoder_encoders_31_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_31_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(206526912)))]; + tensor encoder_encoders_31_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_31_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208624128)))]; + tensor linear_131_cast_fp16 = linear(bias = encoder_encoders_31_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_31_feed_forward_w_2_weight_to_fp16, x = input_991_cast_fp16)[name = tensor("linear_131_cast_fp16")]; + tensor input_997_cast_fp16 = add(x = input_983_cast_fp16, y = linear_131_cast_fp16)[name = tensor("input_997_cast_fp16")]; + tensor output_133_axes_0 = const()[name = tensor("output_133_axes_0"), val = tensor([-1])]; + tensor const_204_to_fp16 = const()[name = tensor("const_204_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208625216)))]; + tensor const_205_to_fp16 = const()[name = tensor("const_205_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208626304)))]; + tensor output_133_cast_fp16 = layer_norm(axes = output_133_axes_0, beta = const_205_to_fp16, epsilon = var_46_to_fp16, gamma = const_204_to_fp16, x = input_997_cast_fp16)[name = tensor("output_133_cast_fp16")]; + tensor encoder_encoders_32_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_32_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208627392)))]; + tensor encoder_encoders_32_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_32_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210200320)))]; + tensor linear_132_cast_fp16 = linear(bias = encoder_encoders_32_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_32_self_attn_linear_q_k_v_weight_to_fp16, x = output_133_cast_fp16)[name = tensor("linear_132_cast_fp16")]; + tensor tile_33 = const()[name = tensor("tile_33"), val = tensor([512, 512, 512])]; + tensor var_3649_axis_0 = const()[name = tensor("op_3649_axis_0"), val = tensor(-1)]; + tensor var_3649_cast_fp16_0, tensor var_3649_cast_fp16_1, tensor var_3649_cast_fp16_2 = split(axis = var_3649_axis_0, split_sizes = tile_33, x = linear_132_cast_fp16)[name = tensor("op_3649_cast_fp16")]; + tensor concat_99x = const()[name = tensor("concat_99x"), val = tensor([1, -1, 4, 128])]; + tensor var_3654_cast_fp16 = reshape(shape = concat_99x, x = var_3649_cast_fp16_0)[name = tensor("op_3654_cast_fp16")]; + tensor concat_100x = const()[name = tensor("concat_100x"), val = tensor([1, -1, 4, 128])]; + tensor var_3657_cast_fp16 = reshape(shape = concat_100x, x = var_3649_cast_fp16_1)[name = tensor("op_3657_cast_fp16")]; + tensor concat_101x = const()[name = tensor("concat_101x"), val = tensor([1, -1, 4, 128])]; + tensor var_3660_cast_fp16 = reshape(shape = concat_101x, x = var_3649_cast_fp16_2)[name = tensor("op_3660_cast_fp16")]; + tensor value_67_perm_0 = const()[name = tensor("value_67_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_67_cast_fp16 = mul(x = var_3649_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_67_cast_fp16")]; + tensor input_1001_perm_0 = const()[name = tensor("input_1001_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1003_pad_0 = const()[name = tensor("input_1003_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1003_mode_0 = const()[name = tensor("input_1003_mode_0"), val = tensor("constant")]; + tensor const_207_to_fp16 = const()[name = tensor("const_207_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1001_cast_fp16 = transpose(perm = input_1001_perm_0, x = inputs_67_cast_fp16)[name = tensor("transpose_570")]; + tensor input_1003_cast_fp16 = pad(constant_val = const_207_to_fp16, mode = input_1003_mode_0, pad = input_1003_pad_0, x = input_1001_cast_fp16)[name = tensor("input_1003_cast_fp16")]; + tensor x_335_pad_type_0 = const()[name = tensor("x_335_pad_type_0"), val = tensor("valid")]; + tensor x_335_groups_0 = const()[name = tensor("x_335_groups_0"), val = tensor(512)]; + tensor x_335_strides_0 = const()[name = tensor("x_335_strides_0"), val = tensor([1])]; + tensor x_335_pad_0 = const()[name = tensor("x_335_pad_0"), val = tensor([0, 0])]; + tensor x_335_dilations_0 = const()[name = tensor("x_335_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_32_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_32_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210203456)))]; + tensor x_335_cast_fp16 = conv(dilations = x_335_dilations_0, groups = x_335_groups_0, pad = x_335_pad_0, pad_type = x_335_pad_type_0, strides = x_335_strides_0, weight = encoder_encoders_32_self_attn_fsmn_block_weight_to_fp16, x = input_1003_cast_fp16)[name = tensor("x_335_cast_fp16")]; + tensor x_337_perm_0 = const()[name = tensor("x_337_perm_0"), val = tensor([0, 2, 1])]; + tensor x_337_cast_fp16 = transpose(perm = x_337_perm_0, x = x_335_cast_fp16)[name = tensor("transpose_569")]; + tensor input_1005_cast_fp16 = add(x = x_337_cast_fp16, y = inputs_67_cast_fp16)[name = tensor("input_1005_cast_fp16")]; + tensor fsmn_memory_67_cast_fp16 = mul(x = input_1005_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_67_cast_fp16")]; + tensor var_3679_to_fp16 = const()[name = tensor("op_3679_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_135_cast_fp16 = mul(x = var_3654_cast_fp16, y = var_3679_to_fp16)[name = tensor("q_h_135_cast_fp16")]; + tensor scores_133_transpose_x_0 = const()[name = tensor("scores_133_transpose_x_0"), val = tensor(false)]; + tensor scores_133_transpose_y_0 = const()[name = tensor("scores_133_transpose_y_0"), val = tensor(false)]; + tensor transpose_276_perm_0 = const()[name = tensor("transpose_276_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_277_perm_0 = const()[name = tensor("transpose_277_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_277 = transpose(perm = transpose_277_perm_0, x = var_3657_cast_fp16)[name = tensor("transpose_567")]; + tensor transpose_276 = transpose(perm = transpose_276_perm_0, x = q_h_135_cast_fp16)[name = tensor("transpose_568")]; + tensor scores_133_cast_fp16 = matmul(transpose_x = scores_133_transpose_x_0, transpose_y = scores_133_transpose_y_0, x = transpose_276, y = transpose_277)[name = tensor("scores_133_cast_fp16")]; + tensor scores_135_cast_fp16 = select(a = var_48_to_fp16, b = scores_133_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_135_cast_fp16")]; + tensor var_3687_cast_fp16 = softmax(axis = var_61, x = scores_135_cast_fp16)[name = tensor("op_3687_cast_fp16")]; + tensor input_1007_cast_fp16 = select(a = var_53_to_fp16, b = var_3687_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1007_cast_fp16")]; + tensor x_341_transpose_x_0 = const()[name = tensor("x_341_transpose_x_0"), val = tensor(false)]; + tensor x_341_transpose_y_0 = const()[name = tensor("x_341_transpose_y_0"), val = tensor(false)]; + tensor value_67_cast_fp16 = transpose(perm = value_67_perm_0, x = var_3660_cast_fp16)[name = tensor("transpose_571")]; + tensor x_341_cast_fp16 = matmul(transpose_x = x_341_transpose_x_0, transpose_y = x_341_transpose_y_0, x = input_1007_cast_fp16, y = value_67_cast_fp16)[name = tensor("x_341_cast_fp16")]; + tensor var_3691_perm_0 = const()[name = tensor("op_3691_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3693 = const()[name = tensor("op_3693"), val = tensor([1, -1, 512])]; + tensor var_3691_cast_fp16 = transpose(perm = var_3691_perm_0, x = x_341_cast_fp16)[name = tensor("transpose_566")]; + tensor input_1009_cast_fp16 = reshape(shape = var_3693, x = var_3691_cast_fp16)[name = tensor("input_1009_cast_fp16")]; + tensor encoder_encoders_32_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_32_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210214784)))]; + tensor encoder_encoders_32_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_32_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210739136)))]; + tensor linear_133_cast_fp16 = linear(bias = encoder_encoders_32_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_32_self_attn_linear_out_weight_to_fp16, x = input_1009_cast_fp16)[name = tensor("linear_133_cast_fp16")]; + tensor input_1011_cast_fp16 = add(x = linear_133_cast_fp16, y = fsmn_memory_67_cast_fp16)[name = tensor("input_1011_cast_fp16")]; + tensor input_1013_cast_fp16 = add(x = input_997_cast_fp16, y = input_1011_cast_fp16)[name = tensor("input_1013_cast_fp16")]; + tensor output_135_axes_0 = const()[name = tensor("output_135_axes_0"), val = tensor([-1])]; + tensor const_208_to_fp16 = const()[name = tensor("const_208_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210740224)))]; + tensor const_209_to_fp16 = const()[name = tensor("const_209_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210741312)))]; + tensor output_135_cast_fp16 = layer_norm(axes = output_135_axes_0, beta = const_209_to_fp16, epsilon = var_46_to_fp16, gamma = const_208_to_fp16, x = input_1013_cast_fp16)[name = tensor("output_135_cast_fp16")]; + tensor encoder_encoders_32_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_32_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(210742400)))]; + tensor encoder_encoders_32_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_32_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(212839616)))]; + tensor linear_134_cast_fp16 = linear(bias = encoder_encoders_32_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_32_feed_forward_w_1_weight_to_fp16, x = output_135_cast_fp16)[name = tensor("linear_134_cast_fp16")]; + tensor input_1021_cast_fp16 = relu(x = linear_134_cast_fp16)[name = tensor("input_1021_cast_fp16")]; + tensor encoder_encoders_32_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_32_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(212843776)))]; + tensor encoder_encoders_32_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_32_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214940992)))]; + tensor linear_135_cast_fp16 = linear(bias = encoder_encoders_32_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_32_feed_forward_w_2_weight_to_fp16, x = input_1021_cast_fp16)[name = tensor("linear_135_cast_fp16")]; + tensor input_1027_cast_fp16 = add(x = input_1013_cast_fp16, y = linear_135_cast_fp16)[name = tensor("input_1027_cast_fp16")]; + tensor output_137_axes_0 = const()[name = tensor("output_137_axes_0"), val = tensor([-1])]; + tensor const_210_to_fp16 = const()[name = tensor("const_210_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214942080)))]; + tensor const_211_to_fp16 = const()[name = tensor("const_211_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214943168)))]; + tensor output_137_cast_fp16 = layer_norm(axes = output_137_axes_0, beta = const_211_to_fp16, epsilon = var_46_to_fp16, gamma = const_210_to_fp16, x = input_1027_cast_fp16)[name = tensor("output_137_cast_fp16")]; + tensor encoder_encoders_33_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_33_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214944256)))]; + tensor encoder_encoders_33_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_33_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216517184)))]; + tensor linear_136_cast_fp16 = linear(bias = encoder_encoders_33_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_33_self_attn_linear_q_k_v_weight_to_fp16, x = output_137_cast_fp16)[name = tensor("linear_136_cast_fp16")]; + tensor tile_34 = const()[name = tensor("tile_34"), val = tensor([512, 512, 512])]; + tensor var_3751_axis_0 = const()[name = tensor("op_3751_axis_0"), val = tensor(-1)]; + tensor var_3751_cast_fp16_0, tensor var_3751_cast_fp16_1, tensor var_3751_cast_fp16_2 = split(axis = var_3751_axis_0, split_sizes = tile_34, x = linear_136_cast_fp16)[name = tensor("op_3751_cast_fp16")]; + tensor concat_102x = const()[name = tensor("concat_102x"), val = tensor([1, -1, 4, 128])]; + tensor var_3756_cast_fp16 = reshape(shape = concat_102x, x = var_3751_cast_fp16_0)[name = tensor("op_3756_cast_fp16")]; + tensor concat_103x = const()[name = tensor("concat_103x"), val = tensor([1, -1, 4, 128])]; + tensor var_3759_cast_fp16 = reshape(shape = concat_103x, x = var_3751_cast_fp16_1)[name = tensor("op_3759_cast_fp16")]; + tensor concat_104x = const()[name = tensor("concat_104x"), val = tensor([1, -1, 4, 128])]; + tensor var_3762_cast_fp16 = reshape(shape = concat_104x, x = var_3751_cast_fp16_2)[name = tensor("op_3762_cast_fp16")]; + tensor value_69_perm_0 = const()[name = tensor("value_69_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_69_cast_fp16 = mul(x = var_3751_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_69_cast_fp16")]; + tensor input_1031_perm_0 = const()[name = tensor("input_1031_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1033_pad_0 = const()[name = tensor("input_1033_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1033_mode_0 = const()[name = tensor("input_1033_mode_0"), val = tensor("constant")]; + tensor const_213_to_fp16 = const()[name = tensor("const_213_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1031_cast_fp16 = transpose(perm = input_1031_perm_0, x = inputs_69_cast_fp16)[name = tensor("transpose_564")]; + tensor input_1033_cast_fp16 = pad(constant_val = const_213_to_fp16, mode = input_1033_mode_0, pad = input_1033_pad_0, x = input_1031_cast_fp16)[name = tensor("input_1033_cast_fp16")]; + tensor x_345_pad_type_0 = const()[name = tensor("x_345_pad_type_0"), val = tensor("valid")]; + tensor x_345_groups_0 = const()[name = tensor("x_345_groups_0"), val = tensor(512)]; + tensor x_345_strides_0 = const()[name = tensor("x_345_strides_0"), val = tensor([1])]; + tensor x_345_pad_0 = const()[name = tensor("x_345_pad_0"), val = tensor([0, 0])]; + tensor x_345_dilations_0 = const()[name = tensor("x_345_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_33_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_33_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216520320)))]; + tensor x_345_cast_fp16 = conv(dilations = x_345_dilations_0, groups = x_345_groups_0, pad = x_345_pad_0, pad_type = x_345_pad_type_0, strides = x_345_strides_0, weight = encoder_encoders_33_self_attn_fsmn_block_weight_to_fp16, x = input_1033_cast_fp16)[name = tensor("x_345_cast_fp16")]; + tensor x_347_perm_0 = const()[name = tensor("x_347_perm_0"), val = tensor([0, 2, 1])]; + tensor x_347_cast_fp16 = transpose(perm = x_347_perm_0, x = x_345_cast_fp16)[name = tensor("transpose_563")]; + tensor input_1035_cast_fp16 = add(x = x_347_cast_fp16, y = inputs_69_cast_fp16)[name = tensor("input_1035_cast_fp16")]; + tensor fsmn_memory_69_cast_fp16 = mul(x = input_1035_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_69_cast_fp16")]; + tensor var_3781_to_fp16 = const()[name = tensor("op_3781_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_139_cast_fp16 = mul(x = var_3756_cast_fp16, y = var_3781_to_fp16)[name = tensor("q_h_139_cast_fp16")]; + tensor scores_137_transpose_x_0 = const()[name = tensor("scores_137_transpose_x_0"), val = tensor(false)]; + tensor scores_137_transpose_y_0 = const()[name = tensor("scores_137_transpose_y_0"), val = tensor(false)]; + tensor transpose_278_perm_0 = const()[name = tensor("transpose_278_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_279_perm_0 = const()[name = tensor("transpose_279_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_279 = transpose(perm = transpose_279_perm_0, x = var_3759_cast_fp16)[name = tensor("transpose_561")]; + tensor transpose_278 = transpose(perm = transpose_278_perm_0, x = q_h_139_cast_fp16)[name = tensor("transpose_562")]; + tensor scores_137_cast_fp16 = matmul(transpose_x = scores_137_transpose_x_0, transpose_y = scores_137_transpose_y_0, x = transpose_278, y = transpose_279)[name = tensor("scores_137_cast_fp16")]; + tensor scores_139_cast_fp16 = select(a = var_48_to_fp16, b = scores_137_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_139_cast_fp16")]; + tensor var_3789_cast_fp16 = softmax(axis = var_61, x = scores_139_cast_fp16)[name = tensor("op_3789_cast_fp16")]; + tensor input_1037_cast_fp16 = select(a = var_53_to_fp16, b = var_3789_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1037_cast_fp16")]; + tensor x_351_transpose_x_0 = const()[name = tensor("x_351_transpose_x_0"), val = tensor(false)]; + tensor x_351_transpose_y_0 = const()[name = tensor("x_351_transpose_y_0"), val = tensor(false)]; + tensor value_69_cast_fp16 = transpose(perm = value_69_perm_0, x = var_3762_cast_fp16)[name = tensor("transpose_565")]; + tensor x_351_cast_fp16 = matmul(transpose_x = x_351_transpose_x_0, transpose_y = x_351_transpose_y_0, x = input_1037_cast_fp16, y = value_69_cast_fp16)[name = tensor("x_351_cast_fp16")]; + tensor var_3793_perm_0 = const()[name = tensor("op_3793_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3795 = const()[name = tensor("op_3795"), val = tensor([1, -1, 512])]; + tensor var_3793_cast_fp16 = transpose(perm = var_3793_perm_0, x = x_351_cast_fp16)[name = tensor("transpose_560")]; + tensor input_1039_cast_fp16 = reshape(shape = var_3795, x = var_3793_cast_fp16)[name = tensor("input_1039_cast_fp16")]; + tensor encoder_encoders_33_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_33_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216531648)))]; + tensor encoder_encoders_33_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_33_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217056000)))]; + tensor linear_137_cast_fp16 = linear(bias = encoder_encoders_33_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_33_self_attn_linear_out_weight_to_fp16, x = input_1039_cast_fp16)[name = tensor("linear_137_cast_fp16")]; + tensor input_1041_cast_fp16 = add(x = linear_137_cast_fp16, y = fsmn_memory_69_cast_fp16)[name = tensor("input_1041_cast_fp16")]; + tensor input_1043_cast_fp16 = add(x = input_1027_cast_fp16, y = input_1041_cast_fp16)[name = tensor("input_1043_cast_fp16")]; + tensor output_139_axes_0 = const()[name = tensor("output_139_axes_0"), val = tensor([-1])]; + tensor const_214_to_fp16 = const()[name = tensor("const_214_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217057088)))]; + tensor const_215_to_fp16 = const()[name = tensor("const_215_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217058176)))]; + tensor output_139_cast_fp16 = layer_norm(axes = output_139_axes_0, beta = const_215_to_fp16, epsilon = var_46_to_fp16, gamma = const_214_to_fp16, x = input_1043_cast_fp16)[name = tensor("output_139_cast_fp16")]; + tensor encoder_encoders_33_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_33_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217059264)))]; + tensor encoder_encoders_33_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_33_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(219156480)))]; + tensor linear_138_cast_fp16 = linear(bias = encoder_encoders_33_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_33_feed_forward_w_1_weight_to_fp16, x = output_139_cast_fp16)[name = tensor("linear_138_cast_fp16")]; + tensor input_1051_cast_fp16 = relu(x = linear_138_cast_fp16)[name = tensor("input_1051_cast_fp16")]; + tensor encoder_encoders_33_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_33_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(219160640)))]; + tensor encoder_encoders_33_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_33_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221257856)))]; + tensor linear_139_cast_fp16 = linear(bias = encoder_encoders_33_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_33_feed_forward_w_2_weight_to_fp16, x = input_1051_cast_fp16)[name = tensor("linear_139_cast_fp16")]; + tensor input_1057_cast_fp16 = add(x = input_1043_cast_fp16, y = linear_139_cast_fp16)[name = tensor("input_1057_cast_fp16")]; + tensor output_141_axes_0 = const()[name = tensor("output_141_axes_0"), val = tensor([-1])]; + tensor const_216_to_fp16 = const()[name = tensor("const_216_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221258944)))]; + tensor const_217_to_fp16 = const()[name = tensor("const_217_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221260032)))]; + tensor output_141_cast_fp16 = layer_norm(axes = output_141_axes_0, beta = const_217_to_fp16, epsilon = var_46_to_fp16, gamma = const_216_to_fp16, x = input_1057_cast_fp16)[name = tensor("output_141_cast_fp16")]; + tensor encoder_encoders_34_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_34_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221261120)))]; + tensor encoder_encoders_34_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_34_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222834048)))]; + tensor linear_140_cast_fp16 = linear(bias = encoder_encoders_34_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_34_self_attn_linear_q_k_v_weight_to_fp16, x = output_141_cast_fp16)[name = tensor("linear_140_cast_fp16")]; + tensor tile_35 = const()[name = tensor("tile_35"), val = tensor([512, 512, 512])]; + tensor var_3853_axis_0 = const()[name = tensor("op_3853_axis_0"), val = tensor(-1)]; + tensor var_3853_cast_fp16_0, tensor var_3853_cast_fp16_1, tensor var_3853_cast_fp16_2 = split(axis = var_3853_axis_0, split_sizes = tile_35, x = linear_140_cast_fp16)[name = tensor("op_3853_cast_fp16")]; + tensor concat_105x = const()[name = tensor("concat_105x"), val = tensor([1, -1, 4, 128])]; + tensor var_3858_cast_fp16 = reshape(shape = concat_105x, x = var_3853_cast_fp16_0)[name = tensor("op_3858_cast_fp16")]; + tensor concat_106x = const()[name = tensor("concat_106x"), val = tensor([1, -1, 4, 128])]; + tensor var_3861_cast_fp16 = reshape(shape = concat_106x, x = var_3853_cast_fp16_1)[name = tensor("op_3861_cast_fp16")]; + tensor concat_107x = const()[name = tensor("concat_107x"), val = tensor([1, -1, 4, 128])]; + tensor var_3864_cast_fp16 = reshape(shape = concat_107x, x = var_3853_cast_fp16_2)[name = tensor("op_3864_cast_fp16")]; + tensor value_71_perm_0 = const()[name = tensor("value_71_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_71_cast_fp16 = mul(x = var_3853_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_71_cast_fp16")]; + tensor input_1061_perm_0 = const()[name = tensor("input_1061_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1063_pad_0 = const()[name = tensor("input_1063_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1063_mode_0 = const()[name = tensor("input_1063_mode_0"), val = tensor("constant")]; + tensor const_219_to_fp16 = const()[name = tensor("const_219_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1061_cast_fp16 = transpose(perm = input_1061_perm_0, x = inputs_71_cast_fp16)[name = tensor("transpose_558")]; + tensor input_1063_cast_fp16 = pad(constant_val = const_219_to_fp16, mode = input_1063_mode_0, pad = input_1063_pad_0, x = input_1061_cast_fp16)[name = tensor("input_1063_cast_fp16")]; + tensor x_355_pad_type_0 = const()[name = tensor("x_355_pad_type_0"), val = tensor("valid")]; + tensor x_355_groups_0 = const()[name = tensor("x_355_groups_0"), val = tensor(512)]; + tensor x_355_strides_0 = const()[name = tensor("x_355_strides_0"), val = tensor([1])]; + tensor x_355_pad_0 = const()[name = tensor("x_355_pad_0"), val = tensor([0, 0])]; + tensor x_355_dilations_0 = const()[name = tensor("x_355_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_34_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_34_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222837184)))]; + tensor x_355_cast_fp16 = conv(dilations = x_355_dilations_0, groups = x_355_groups_0, pad = x_355_pad_0, pad_type = x_355_pad_type_0, strides = x_355_strides_0, weight = encoder_encoders_34_self_attn_fsmn_block_weight_to_fp16, x = input_1063_cast_fp16)[name = tensor("x_355_cast_fp16")]; + tensor x_357_perm_0 = const()[name = tensor("x_357_perm_0"), val = tensor([0, 2, 1])]; + tensor x_357_cast_fp16 = transpose(perm = x_357_perm_0, x = x_355_cast_fp16)[name = tensor("transpose_557")]; + tensor input_1065_cast_fp16 = add(x = x_357_cast_fp16, y = inputs_71_cast_fp16)[name = tensor("input_1065_cast_fp16")]; + tensor fsmn_memory_71_cast_fp16 = mul(x = input_1065_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_71_cast_fp16")]; + tensor var_3883_to_fp16 = const()[name = tensor("op_3883_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_143_cast_fp16 = mul(x = var_3858_cast_fp16, y = var_3883_to_fp16)[name = tensor("q_h_143_cast_fp16")]; + tensor scores_141_transpose_x_0 = const()[name = tensor("scores_141_transpose_x_0"), val = tensor(false)]; + tensor scores_141_transpose_y_0 = const()[name = tensor("scores_141_transpose_y_0"), val = tensor(false)]; + tensor transpose_280_perm_0 = const()[name = tensor("transpose_280_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_281_perm_0 = const()[name = tensor("transpose_281_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_281 = transpose(perm = transpose_281_perm_0, x = var_3861_cast_fp16)[name = tensor("transpose_555")]; + tensor transpose_280 = transpose(perm = transpose_280_perm_0, x = q_h_143_cast_fp16)[name = tensor("transpose_556")]; + tensor scores_141_cast_fp16 = matmul(transpose_x = scores_141_transpose_x_0, transpose_y = scores_141_transpose_y_0, x = transpose_280, y = transpose_281)[name = tensor("scores_141_cast_fp16")]; + tensor scores_143_cast_fp16 = select(a = var_48_to_fp16, b = scores_141_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_143_cast_fp16")]; + tensor var_3891_cast_fp16 = softmax(axis = var_61, x = scores_143_cast_fp16)[name = tensor("op_3891_cast_fp16")]; + tensor input_1067_cast_fp16 = select(a = var_53_to_fp16, b = var_3891_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1067_cast_fp16")]; + tensor x_361_transpose_x_0 = const()[name = tensor("x_361_transpose_x_0"), val = tensor(false)]; + tensor x_361_transpose_y_0 = const()[name = tensor("x_361_transpose_y_0"), val = tensor(false)]; + tensor value_71_cast_fp16 = transpose(perm = value_71_perm_0, x = var_3864_cast_fp16)[name = tensor("transpose_559")]; + tensor x_361_cast_fp16 = matmul(transpose_x = x_361_transpose_x_0, transpose_y = x_361_transpose_y_0, x = input_1067_cast_fp16, y = value_71_cast_fp16)[name = tensor("x_361_cast_fp16")]; + tensor var_3895_perm_0 = const()[name = tensor("op_3895_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3897 = const()[name = tensor("op_3897"), val = tensor([1, -1, 512])]; + tensor var_3895_cast_fp16 = transpose(perm = var_3895_perm_0, x = x_361_cast_fp16)[name = tensor("transpose_554")]; + tensor input_1069_cast_fp16 = reshape(shape = var_3897, x = var_3895_cast_fp16)[name = tensor("input_1069_cast_fp16")]; + tensor encoder_encoders_34_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_34_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222848512)))]; + tensor encoder_encoders_34_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_34_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(223372864)))]; + tensor linear_141_cast_fp16 = linear(bias = encoder_encoders_34_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_34_self_attn_linear_out_weight_to_fp16, x = input_1069_cast_fp16)[name = tensor("linear_141_cast_fp16")]; + tensor input_1071_cast_fp16 = add(x = linear_141_cast_fp16, y = fsmn_memory_71_cast_fp16)[name = tensor("input_1071_cast_fp16")]; + tensor input_1073_cast_fp16 = add(x = input_1057_cast_fp16, y = input_1071_cast_fp16)[name = tensor("input_1073_cast_fp16")]; + tensor output_143_axes_0 = const()[name = tensor("output_143_axes_0"), val = tensor([-1])]; + tensor const_220_to_fp16 = const()[name = tensor("const_220_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(223373952)))]; + tensor const_221_to_fp16 = const()[name = tensor("const_221_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(223375040)))]; + tensor output_143_cast_fp16 = layer_norm(axes = output_143_axes_0, beta = const_221_to_fp16, epsilon = var_46_to_fp16, gamma = const_220_to_fp16, x = input_1073_cast_fp16)[name = tensor("output_143_cast_fp16")]; + tensor encoder_encoders_34_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_34_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(223376128)))]; + tensor encoder_encoders_34_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_34_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225473344)))]; + tensor linear_142_cast_fp16 = linear(bias = encoder_encoders_34_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_34_feed_forward_w_1_weight_to_fp16, x = output_143_cast_fp16)[name = tensor("linear_142_cast_fp16")]; + tensor input_1081_cast_fp16 = relu(x = linear_142_cast_fp16)[name = tensor("input_1081_cast_fp16")]; + tensor encoder_encoders_34_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_34_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225477504)))]; + tensor encoder_encoders_34_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_34_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227574720)))]; + tensor linear_143_cast_fp16 = linear(bias = encoder_encoders_34_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_34_feed_forward_w_2_weight_to_fp16, x = input_1081_cast_fp16)[name = tensor("linear_143_cast_fp16")]; + tensor input_1087_cast_fp16 = add(x = input_1073_cast_fp16, y = linear_143_cast_fp16)[name = tensor("input_1087_cast_fp16")]; + tensor output_145_axes_0 = const()[name = tensor("output_145_axes_0"), val = tensor([-1])]; + tensor const_222_to_fp16 = const()[name = tensor("const_222_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227575808)))]; + tensor const_223_to_fp16 = const()[name = tensor("const_223_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227576896)))]; + tensor output_145_cast_fp16 = layer_norm(axes = output_145_axes_0, beta = const_223_to_fp16, epsilon = var_46_to_fp16, gamma = const_222_to_fp16, x = input_1087_cast_fp16)[name = tensor("output_145_cast_fp16")]; + tensor encoder_encoders_35_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_35_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227577984)))]; + tensor encoder_encoders_35_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_35_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229150912)))]; + tensor linear_144_cast_fp16 = linear(bias = encoder_encoders_35_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_35_self_attn_linear_q_k_v_weight_to_fp16, x = output_145_cast_fp16)[name = tensor("linear_144_cast_fp16")]; + tensor tile_36 = const()[name = tensor("tile_36"), val = tensor([512, 512, 512])]; + tensor var_3955_axis_0 = const()[name = tensor("op_3955_axis_0"), val = tensor(-1)]; + tensor var_3955_cast_fp16_0, tensor var_3955_cast_fp16_1, tensor var_3955_cast_fp16_2 = split(axis = var_3955_axis_0, split_sizes = tile_36, x = linear_144_cast_fp16)[name = tensor("op_3955_cast_fp16")]; + tensor concat_108x = const()[name = tensor("concat_108x"), val = tensor([1, -1, 4, 128])]; + tensor var_3960_cast_fp16 = reshape(shape = concat_108x, x = var_3955_cast_fp16_0)[name = tensor("op_3960_cast_fp16")]; + tensor concat_109x = const()[name = tensor("concat_109x"), val = tensor([1, -1, 4, 128])]; + tensor var_3963_cast_fp16 = reshape(shape = concat_109x, x = var_3955_cast_fp16_1)[name = tensor("op_3963_cast_fp16")]; + tensor concat_110x = const()[name = tensor("concat_110x"), val = tensor([1, -1, 4, 128])]; + tensor var_3966_cast_fp16 = reshape(shape = concat_110x, x = var_3955_cast_fp16_2)[name = tensor("op_3966_cast_fp16")]; + tensor value_73_perm_0 = const()[name = tensor("value_73_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_73_cast_fp16 = mul(x = var_3955_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_73_cast_fp16")]; + tensor input_1091_perm_0 = const()[name = tensor("input_1091_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1093_pad_0 = const()[name = tensor("input_1093_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1093_mode_0 = const()[name = tensor("input_1093_mode_0"), val = tensor("constant")]; + tensor const_225_to_fp16 = const()[name = tensor("const_225_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1091_cast_fp16 = transpose(perm = input_1091_perm_0, x = inputs_73_cast_fp16)[name = tensor("transpose_552")]; + tensor input_1093_cast_fp16 = pad(constant_val = const_225_to_fp16, mode = input_1093_mode_0, pad = input_1093_pad_0, x = input_1091_cast_fp16)[name = tensor("input_1093_cast_fp16")]; + tensor x_365_pad_type_0 = const()[name = tensor("x_365_pad_type_0"), val = tensor("valid")]; + tensor x_365_groups_0 = const()[name = tensor("x_365_groups_0"), val = tensor(512)]; + tensor x_365_strides_0 = const()[name = tensor("x_365_strides_0"), val = tensor([1])]; + tensor x_365_pad_0 = const()[name = tensor("x_365_pad_0"), val = tensor([0, 0])]; + tensor x_365_dilations_0 = const()[name = tensor("x_365_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_35_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_35_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229154048)))]; + tensor x_365_cast_fp16 = conv(dilations = x_365_dilations_0, groups = x_365_groups_0, pad = x_365_pad_0, pad_type = x_365_pad_type_0, strides = x_365_strides_0, weight = encoder_encoders_35_self_attn_fsmn_block_weight_to_fp16, x = input_1093_cast_fp16)[name = tensor("x_365_cast_fp16")]; + tensor x_367_perm_0 = const()[name = tensor("x_367_perm_0"), val = tensor([0, 2, 1])]; + tensor x_367_cast_fp16 = transpose(perm = x_367_perm_0, x = x_365_cast_fp16)[name = tensor("transpose_551")]; + tensor input_1095_cast_fp16 = add(x = x_367_cast_fp16, y = inputs_73_cast_fp16)[name = tensor("input_1095_cast_fp16")]; + tensor fsmn_memory_73_cast_fp16 = mul(x = input_1095_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_73_cast_fp16")]; + tensor var_3985_to_fp16 = const()[name = tensor("op_3985_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_147_cast_fp16 = mul(x = var_3960_cast_fp16, y = var_3985_to_fp16)[name = tensor("q_h_147_cast_fp16")]; + tensor scores_145_transpose_x_0 = const()[name = tensor("scores_145_transpose_x_0"), val = tensor(false)]; + tensor scores_145_transpose_y_0 = const()[name = tensor("scores_145_transpose_y_0"), val = tensor(false)]; + tensor transpose_282_perm_0 = const()[name = tensor("transpose_282_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_283_perm_0 = const()[name = tensor("transpose_283_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_283 = transpose(perm = transpose_283_perm_0, x = var_3963_cast_fp16)[name = tensor("transpose_549")]; + tensor transpose_282 = transpose(perm = transpose_282_perm_0, x = q_h_147_cast_fp16)[name = tensor("transpose_550")]; + tensor scores_145_cast_fp16 = matmul(transpose_x = scores_145_transpose_x_0, transpose_y = scores_145_transpose_y_0, x = transpose_282, y = transpose_283)[name = tensor("scores_145_cast_fp16")]; + tensor scores_147_cast_fp16 = select(a = var_48_to_fp16, b = scores_145_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_147_cast_fp16")]; + tensor var_3993_cast_fp16 = softmax(axis = var_61, x = scores_147_cast_fp16)[name = tensor("op_3993_cast_fp16")]; + tensor input_1097_cast_fp16 = select(a = var_53_to_fp16, b = var_3993_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1097_cast_fp16")]; + tensor x_371_transpose_x_0 = const()[name = tensor("x_371_transpose_x_0"), val = tensor(false)]; + tensor x_371_transpose_y_0 = const()[name = tensor("x_371_transpose_y_0"), val = tensor(false)]; + tensor value_73_cast_fp16 = transpose(perm = value_73_perm_0, x = var_3966_cast_fp16)[name = tensor("transpose_553")]; + tensor x_371_cast_fp16 = matmul(transpose_x = x_371_transpose_x_0, transpose_y = x_371_transpose_y_0, x = input_1097_cast_fp16, y = value_73_cast_fp16)[name = tensor("x_371_cast_fp16")]; + tensor var_3997_perm_0 = const()[name = tensor("op_3997_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_3999 = const()[name = tensor("op_3999"), val = tensor([1, -1, 512])]; + tensor var_3997_cast_fp16 = transpose(perm = var_3997_perm_0, x = x_371_cast_fp16)[name = tensor("transpose_548")]; + tensor input_1099_cast_fp16 = reshape(shape = var_3999, x = var_3997_cast_fp16)[name = tensor("input_1099_cast_fp16")]; + tensor encoder_encoders_35_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_35_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229165376)))]; + tensor encoder_encoders_35_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_35_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229689728)))]; + tensor linear_145_cast_fp16 = linear(bias = encoder_encoders_35_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_35_self_attn_linear_out_weight_to_fp16, x = input_1099_cast_fp16)[name = tensor("linear_145_cast_fp16")]; + tensor input_1101_cast_fp16 = add(x = linear_145_cast_fp16, y = fsmn_memory_73_cast_fp16)[name = tensor("input_1101_cast_fp16")]; + tensor input_1103_cast_fp16 = add(x = input_1087_cast_fp16, y = input_1101_cast_fp16)[name = tensor("input_1103_cast_fp16")]; + tensor output_147_axes_0 = const()[name = tensor("output_147_axes_0"), val = tensor([-1])]; + tensor const_226_to_fp16 = const()[name = tensor("const_226_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229690816)))]; + tensor const_227_to_fp16 = const()[name = tensor("const_227_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229691904)))]; + tensor output_147_cast_fp16 = layer_norm(axes = output_147_axes_0, beta = const_227_to_fp16, epsilon = var_46_to_fp16, gamma = const_226_to_fp16, x = input_1103_cast_fp16)[name = tensor("output_147_cast_fp16")]; + tensor encoder_encoders_35_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_35_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229692992)))]; + tensor encoder_encoders_35_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_35_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(231790208)))]; + tensor linear_146_cast_fp16 = linear(bias = encoder_encoders_35_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_35_feed_forward_w_1_weight_to_fp16, x = output_147_cast_fp16)[name = tensor("linear_146_cast_fp16")]; + tensor input_1111_cast_fp16 = relu(x = linear_146_cast_fp16)[name = tensor("input_1111_cast_fp16")]; + tensor encoder_encoders_35_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_35_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(231794368)))]; + tensor encoder_encoders_35_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_35_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233891584)))]; + tensor linear_147_cast_fp16 = linear(bias = encoder_encoders_35_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_35_feed_forward_w_2_weight_to_fp16, x = input_1111_cast_fp16)[name = tensor("linear_147_cast_fp16")]; + tensor input_1117_cast_fp16 = add(x = input_1103_cast_fp16, y = linear_147_cast_fp16)[name = tensor("input_1117_cast_fp16")]; + tensor output_149_axes_0 = const()[name = tensor("output_149_axes_0"), val = tensor([-1])]; + tensor const_228_to_fp16 = const()[name = tensor("const_228_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233892672)))]; + tensor const_229_to_fp16 = const()[name = tensor("const_229_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233893760)))]; + tensor output_149_cast_fp16 = layer_norm(axes = output_149_axes_0, beta = const_229_to_fp16, epsilon = var_46_to_fp16, gamma = const_228_to_fp16, x = input_1117_cast_fp16)[name = tensor("output_149_cast_fp16")]; + tensor encoder_encoders_36_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_36_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233894848)))]; + tensor encoder_encoders_36_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_36_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235467776)))]; + tensor linear_148_cast_fp16 = linear(bias = encoder_encoders_36_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_36_self_attn_linear_q_k_v_weight_to_fp16, x = output_149_cast_fp16)[name = tensor("linear_148_cast_fp16")]; + tensor tile_37 = const()[name = tensor("tile_37"), val = tensor([512, 512, 512])]; + tensor var_4057_axis_0 = const()[name = tensor("op_4057_axis_0"), val = tensor(-1)]; + tensor var_4057_cast_fp16_0, tensor var_4057_cast_fp16_1, tensor var_4057_cast_fp16_2 = split(axis = var_4057_axis_0, split_sizes = tile_37, x = linear_148_cast_fp16)[name = tensor("op_4057_cast_fp16")]; + tensor concat_111x = const()[name = tensor("concat_111x"), val = tensor([1, -1, 4, 128])]; + tensor var_4062_cast_fp16 = reshape(shape = concat_111x, x = var_4057_cast_fp16_0)[name = tensor("op_4062_cast_fp16")]; + tensor concat_112x = const()[name = tensor("concat_112x"), val = tensor([1, -1, 4, 128])]; + tensor var_4065_cast_fp16 = reshape(shape = concat_112x, x = var_4057_cast_fp16_1)[name = tensor("op_4065_cast_fp16")]; + tensor concat_113x = const()[name = tensor("concat_113x"), val = tensor([1, -1, 4, 128])]; + tensor var_4068_cast_fp16 = reshape(shape = concat_113x, x = var_4057_cast_fp16_2)[name = tensor("op_4068_cast_fp16")]; + tensor value_75_perm_0 = const()[name = tensor("value_75_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_75_cast_fp16 = mul(x = var_4057_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_75_cast_fp16")]; + tensor input_1121_perm_0 = const()[name = tensor("input_1121_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1123_pad_0 = const()[name = tensor("input_1123_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1123_mode_0 = const()[name = tensor("input_1123_mode_0"), val = tensor("constant")]; + tensor const_231_to_fp16 = const()[name = tensor("const_231_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1121_cast_fp16 = transpose(perm = input_1121_perm_0, x = inputs_75_cast_fp16)[name = tensor("transpose_546")]; + tensor input_1123_cast_fp16 = pad(constant_val = const_231_to_fp16, mode = input_1123_mode_0, pad = input_1123_pad_0, x = input_1121_cast_fp16)[name = tensor("input_1123_cast_fp16")]; + tensor x_375_pad_type_0 = const()[name = tensor("x_375_pad_type_0"), val = tensor("valid")]; + tensor x_375_groups_0 = const()[name = tensor("x_375_groups_0"), val = tensor(512)]; + tensor x_375_strides_0 = const()[name = tensor("x_375_strides_0"), val = tensor([1])]; + tensor x_375_pad_0 = const()[name = tensor("x_375_pad_0"), val = tensor([0, 0])]; + tensor x_375_dilations_0 = const()[name = tensor("x_375_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_36_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_36_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235470912)))]; + tensor x_375_cast_fp16 = conv(dilations = x_375_dilations_0, groups = x_375_groups_0, pad = x_375_pad_0, pad_type = x_375_pad_type_0, strides = x_375_strides_0, weight = encoder_encoders_36_self_attn_fsmn_block_weight_to_fp16, x = input_1123_cast_fp16)[name = tensor("x_375_cast_fp16")]; + tensor x_377_perm_0 = const()[name = tensor("x_377_perm_0"), val = tensor([0, 2, 1])]; + tensor x_377_cast_fp16 = transpose(perm = x_377_perm_0, x = x_375_cast_fp16)[name = tensor("transpose_545")]; + tensor input_1125_cast_fp16 = add(x = x_377_cast_fp16, y = inputs_75_cast_fp16)[name = tensor("input_1125_cast_fp16")]; + tensor fsmn_memory_75_cast_fp16 = mul(x = input_1125_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_75_cast_fp16")]; + tensor var_4087_to_fp16 = const()[name = tensor("op_4087_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_151_cast_fp16 = mul(x = var_4062_cast_fp16, y = var_4087_to_fp16)[name = tensor("q_h_151_cast_fp16")]; + tensor scores_149_transpose_x_0 = const()[name = tensor("scores_149_transpose_x_0"), val = tensor(false)]; + tensor scores_149_transpose_y_0 = const()[name = tensor("scores_149_transpose_y_0"), val = tensor(false)]; + tensor transpose_284_perm_0 = const()[name = tensor("transpose_284_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_285_perm_0 = const()[name = tensor("transpose_285_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_285 = transpose(perm = transpose_285_perm_0, x = var_4065_cast_fp16)[name = tensor("transpose_543")]; + tensor transpose_284 = transpose(perm = transpose_284_perm_0, x = q_h_151_cast_fp16)[name = tensor("transpose_544")]; + tensor scores_149_cast_fp16 = matmul(transpose_x = scores_149_transpose_x_0, transpose_y = scores_149_transpose_y_0, x = transpose_284, y = transpose_285)[name = tensor("scores_149_cast_fp16")]; + tensor scores_151_cast_fp16 = select(a = var_48_to_fp16, b = scores_149_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_151_cast_fp16")]; + tensor var_4095_cast_fp16 = softmax(axis = var_61, x = scores_151_cast_fp16)[name = tensor("op_4095_cast_fp16")]; + tensor input_1127_cast_fp16 = select(a = var_53_to_fp16, b = var_4095_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1127_cast_fp16")]; + tensor x_381_transpose_x_0 = const()[name = tensor("x_381_transpose_x_0"), val = tensor(false)]; + tensor x_381_transpose_y_0 = const()[name = tensor("x_381_transpose_y_0"), val = tensor(false)]; + tensor value_75_cast_fp16 = transpose(perm = value_75_perm_0, x = var_4068_cast_fp16)[name = tensor("transpose_547")]; + tensor x_381_cast_fp16 = matmul(transpose_x = x_381_transpose_x_0, transpose_y = x_381_transpose_y_0, x = input_1127_cast_fp16, y = value_75_cast_fp16)[name = tensor("x_381_cast_fp16")]; + tensor var_4099_perm_0 = const()[name = tensor("op_4099_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_4101 = const()[name = tensor("op_4101"), val = tensor([1, -1, 512])]; + tensor var_4099_cast_fp16 = transpose(perm = var_4099_perm_0, x = x_381_cast_fp16)[name = tensor("transpose_542")]; + tensor input_1129_cast_fp16 = reshape(shape = var_4101, x = var_4099_cast_fp16)[name = tensor("input_1129_cast_fp16")]; + tensor encoder_encoders_36_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_36_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235482240)))]; + tensor encoder_encoders_36_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_36_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236006592)))]; + tensor linear_149_cast_fp16 = linear(bias = encoder_encoders_36_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_36_self_attn_linear_out_weight_to_fp16, x = input_1129_cast_fp16)[name = tensor("linear_149_cast_fp16")]; + tensor input_1131_cast_fp16 = add(x = linear_149_cast_fp16, y = fsmn_memory_75_cast_fp16)[name = tensor("input_1131_cast_fp16")]; + tensor input_1133_cast_fp16 = add(x = input_1117_cast_fp16, y = input_1131_cast_fp16)[name = tensor("input_1133_cast_fp16")]; + tensor output_151_axes_0 = const()[name = tensor("output_151_axes_0"), val = tensor([-1])]; + tensor const_232_to_fp16 = const()[name = tensor("const_232_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236007680)))]; + tensor const_233_to_fp16 = const()[name = tensor("const_233_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236008768)))]; + tensor output_151_cast_fp16 = layer_norm(axes = output_151_axes_0, beta = const_233_to_fp16, epsilon = var_46_to_fp16, gamma = const_232_to_fp16, x = input_1133_cast_fp16)[name = tensor("output_151_cast_fp16")]; + tensor encoder_encoders_36_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_36_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236009856)))]; + tensor encoder_encoders_36_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_36_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(238107072)))]; + tensor linear_150_cast_fp16 = linear(bias = encoder_encoders_36_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_36_feed_forward_w_1_weight_to_fp16, x = output_151_cast_fp16)[name = tensor("linear_150_cast_fp16")]; + tensor input_1141_cast_fp16 = relu(x = linear_150_cast_fp16)[name = tensor("input_1141_cast_fp16")]; + tensor encoder_encoders_36_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_36_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(238111232)))]; + tensor encoder_encoders_36_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_36_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240208448)))]; + tensor linear_151_cast_fp16 = linear(bias = encoder_encoders_36_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_36_feed_forward_w_2_weight_to_fp16, x = input_1141_cast_fp16)[name = tensor("linear_151_cast_fp16")]; + tensor input_1147_cast_fp16 = add(x = input_1133_cast_fp16, y = linear_151_cast_fp16)[name = tensor("input_1147_cast_fp16")]; + tensor output_153_axes_0 = const()[name = tensor("output_153_axes_0"), val = tensor([-1])]; + tensor const_234_to_fp16 = const()[name = tensor("const_234_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240209536)))]; + tensor const_235_to_fp16 = const()[name = tensor("const_235_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240210624)))]; + tensor output_153_cast_fp16 = layer_norm(axes = output_153_axes_0, beta = const_235_to_fp16, epsilon = var_46_to_fp16, gamma = const_234_to_fp16, x = input_1147_cast_fp16)[name = tensor("output_153_cast_fp16")]; + tensor encoder_encoders_37_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_37_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240211712)))]; + tensor encoder_encoders_37_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_37_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241784640)))]; + tensor linear_152_cast_fp16 = linear(bias = encoder_encoders_37_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_37_self_attn_linear_q_k_v_weight_to_fp16, x = output_153_cast_fp16)[name = tensor("linear_152_cast_fp16")]; + tensor tile_38 = const()[name = tensor("tile_38"), val = tensor([512, 512, 512])]; + tensor var_4159_axis_0 = const()[name = tensor("op_4159_axis_0"), val = tensor(-1)]; + tensor var_4159_cast_fp16_0, tensor var_4159_cast_fp16_1, tensor var_4159_cast_fp16_2 = split(axis = var_4159_axis_0, split_sizes = tile_38, x = linear_152_cast_fp16)[name = tensor("op_4159_cast_fp16")]; + tensor concat_114x = const()[name = tensor("concat_114x"), val = tensor([1, -1, 4, 128])]; + tensor var_4164_cast_fp16 = reshape(shape = concat_114x, x = var_4159_cast_fp16_0)[name = tensor("op_4164_cast_fp16")]; + tensor concat_115x = const()[name = tensor("concat_115x"), val = tensor([1, -1, 4, 128])]; + tensor var_4167_cast_fp16 = reshape(shape = concat_115x, x = var_4159_cast_fp16_1)[name = tensor("op_4167_cast_fp16")]; + tensor concat_116x = const()[name = tensor("concat_116x"), val = tensor([1, -1, 4, 128])]; + tensor var_4170_cast_fp16 = reshape(shape = concat_116x, x = var_4159_cast_fp16_2)[name = tensor("op_4170_cast_fp16")]; + tensor value_77_perm_0 = const()[name = tensor("value_77_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_77_cast_fp16 = mul(x = var_4159_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_77_cast_fp16")]; + tensor input_1151_perm_0 = const()[name = tensor("input_1151_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1153_pad_0 = const()[name = tensor("input_1153_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1153_mode_0 = const()[name = tensor("input_1153_mode_0"), val = tensor("constant")]; + tensor const_237_to_fp16 = const()[name = tensor("const_237_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1151_cast_fp16 = transpose(perm = input_1151_perm_0, x = inputs_77_cast_fp16)[name = tensor("transpose_540")]; + tensor input_1153_cast_fp16 = pad(constant_val = const_237_to_fp16, mode = input_1153_mode_0, pad = input_1153_pad_0, x = input_1151_cast_fp16)[name = tensor("input_1153_cast_fp16")]; + tensor x_385_pad_type_0 = const()[name = tensor("x_385_pad_type_0"), val = tensor("valid")]; + tensor x_385_groups_0 = const()[name = tensor("x_385_groups_0"), val = tensor(512)]; + tensor x_385_strides_0 = const()[name = tensor("x_385_strides_0"), val = tensor([1])]; + tensor x_385_pad_0 = const()[name = tensor("x_385_pad_0"), val = tensor([0, 0])]; + tensor x_385_dilations_0 = const()[name = tensor("x_385_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_37_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_37_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241787776)))]; + tensor x_385_cast_fp16 = conv(dilations = x_385_dilations_0, groups = x_385_groups_0, pad = x_385_pad_0, pad_type = x_385_pad_type_0, strides = x_385_strides_0, weight = encoder_encoders_37_self_attn_fsmn_block_weight_to_fp16, x = input_1153_cast_fp16)[name = tensor("x_385_cast_fp16")]; + tensor x_387_perm_0 = const()[name = tensor("x_387_perm_0"), val = tensor([0, 2, 1])]; + tensor x_387_cast_fp16 = transpose(perm = x_387_perm_0, x = x_385_cast_fp16)[name = tensor("transpose_539")]; + tensor input_1155_cast_fp16 = add(x = x_387_cast_fp16, y = inputs_77_cast_fp16)[name = tensor("input_1155_cast_fp16")]; + tensor fsmn_memory_77_cast_fp16 = mul(x = input_1155_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_77_cast_fp16")]; + tensor var_4189_to_fp16 = const()[name = tensor("op_4189_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_155_cast_fp16 = mul(x = var_4164_cast_fp16, y = var_4189_to_fp16)[name = tensor("q_h_155_cast_fp16")]; + tensor scores_153_transpose_x_0 = const()[name = tensor("scores_153_transpose_x_0"), val = tensor(false)]; + tensor scores_153_transpose_y_0 = const()[name = tensor("scores_153_transpose_y_0"), val = tensor(false)]; + tensor transpose_286_perm_0 = const()[name = tensor("transpose_286_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_287_perm_0 = const()[name = tensor("transpose_287_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_287 = transpose(perm = transpose_287_perm_0, x = var_4167_cast_fp16)[name = tensor("transpose_537")]; + tensor transpose_286 = transpose(perm = transpose_286_perm_0, x = q_h_155_cast_fp16)[name = tensor("transpose_538")]; + tensor scores_153_cast_fp16 = matmul(transpose_x = scores_153_transpose_x_0, transpose_y = scores_153_transpose_y_0, x = transpose_286, y = transpose_287)[name = tensor("scores_153_cast_fp16")]; + tensor scores_155_cast_fp16 = select(a = var_48_to_fp16, b = scores_153_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_155_cast_fp16")]; + tensor var_4197_cast_fp16 = softmax(axis = var_61, x = scores_155_cast_fp16)[name = tensor("op_4197_cast_fp16")]; + tensor input_1157_cast_fp16 = select(a = var_53_to_fp16, b = var_4197_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1157_cast_fp16")]; + tensor x_391_transpose_x_0 = const()[name = tensor("x_391_transpose_x_0"), val = tensor(false)]; + tensor x_391_transpose_y_0 = const()[name = tensor("x_391_transpose_y_0"), val = tensor(false)]; + tensor value_77_cast_fp16 = transpose(perm = value_77_perm_0, x = var_4170_cast_fp16)[name = tensor("transpose_541")]; + tensor x_391_cast_fp16 = matmul(transpose_x = x_391_transpose_x_0, transpose_y = x_391_transpose_y_0, x = input_1157_cast_fp16, y = value_77_cast_fp16)[name = tensor("x_391_cast_fp16")]; + tensor var_4201_perm_0 = const()[name = tensor("op_4201_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_4203 = const()[name = tensor("op_4203"), val = tensor([1, -1, 512])]; + tensor var_4201_cast_fp16 = transpose(perm = var_4201_perm_0, x = x_391_cast_fp16)[name = tensor("transpose_536")]; + tensor input_1159_cast_fp16 = reshape(shape = var_4203, x = var_4201_cast_fp16)[name = tensor("input_1159_cast_fp16")]; + tensor encoder_encoders_37_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_37_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241799104)))]; + tensor encoder_encoders_37_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_37_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242323456)))]; + tensor linear_153_cast_fp16 = linear(bias = encoder_encoders_37_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_37_self_attn_linear_out_weight_to_fp16, x = input_1159_cast_fp16)[name = tensor("linear_153_cast_fp16")]; + tensor input_1161_cast_fp16 = add(x = linear_153_cast_fp16, y = fsmn_memory_77_cast_fp16)[name = tensor("input_1161_cast_fp16")]; + tensor input_1163_cast_fp16 = add(x = input_1147_cast_fp16, y = input_1161_cast_fp16)[name = tensor("input_1163_cast_fp16")]; + tensor output_155_axes_0 = const()[name = tensor("output_155_axes_0"), val = tensor([-1])]; + tensor const_238_to_fp16 = const()[name = tensor("const_238_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242324544)))]; + tensor const_239_to_fp16 = const()[name = tensor("const_239_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242325632)))]; + tensor output_155_cast_fp16 = layer_norm(axes = output_155_axes_0, beta = const_239_to_fp16, epsilon = var_46_to_fp16, gamma = const_238_to_fp16, x = input_1163_cast_fp16)[name = tensor("output_155_cast_fp16")]; + tensor encoder_encoders_37_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_37_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242326720)))]; + tensor encoder_encoders_37_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_37_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244423936)))]; + tensor linear_154_cast_fp16 = linear(bias = encoder_encoders_37_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_37_feed_forward_w_1_weight_to_fp16, x = output_155_cast_fp16)[name = tensor("linear_154_cast_fp16")]; + tensor input_1171_cast_fp16 = relu(x = linear_154_cast_fp16)[name = tensor("input_1171_cast_fp16")]; + tensor encoder_encoders_37_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_37_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244428096)))]; + tensor encoder_encoders_37_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_37_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246525312)))]; + tensor linear_155_cast_fp16 = linear(bias = encoder_encoders_37_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_37_feed_forward_w_2_weight_to_fp16, x = input_1171_cast_fp16)[name = tensor("linear_155_cast_fp16")]; + tensor input_1177_cast_fp16 = add(x = input_1163_cast_fp16, y = linear_155_cast_fp16)[name = tensor("input_1177_cast_fp16")]; + tensor output_157_axes_0 = const()[name = tensor("output_157_axes_0"), val = tensor([-1])]; + tensor const_240_to_fp16 = const()[name = tensor("const_240_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246526400)))]; + tensor const_241_to_fp16 = const()[name = tensor("const_241_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246527488)))]; + tensor output_157_cast_fp16 = layer_norm(axes = output_157_axes_0, beta = const_241_to_fp16, epsilon = var_46_to_fp16, gamma = const_240_to_fp16, x = input_1177_cast_fp16)[name = tensor("output_157_cast_fp16")]; + tensor encoder_encoders_38_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_38_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246528576)))]; + tensor encoder_encoders_38_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_38_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248101504)))]; + tensor linear_156_cast_fp16 = linear(bias = encoder_encoders_38_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_38_self_attn_linear_q_k_v_weight_to_fp16, x = output_157_cast_fp16)[name = tensor("linear_156_cast_fp16")]; + tensor tile_39 = const()[name = tensor("tile_39"), val = tensor([512, 512, 512])]; + tensor var_4261_axis_0 = const()[name = tensor("op_4261_axis_0"), val = tensor(-1)]; + tensor var_4261_cast_fp16_0, tensor var_4261_cast_fp16_1, tensor var_4261_cast_fp16_2 = split(axis = var_4261_axis_0, split_sizes = tile_39, x = linear_156_cast_fp16)[name = tensor("op_4261_cast_fp16")]; + tensor concat_117x = const()[name = tensor("concat_117x"), val = tensor([1, -1, 4, 128])]; + tensor var_4266_cast_fp16 = reshape(shape = concat_117x, x = var_4261_cast_fp16_0)[name = tensor("op_4266_cast_fp16")]; + tensor concat_118x = const()[name = tensor("concat_118x"), val = tensor([1, -1, 4, 128])]; + tensor var_4269_cast_fp16 = reshape(shape = concat_118x, x = var_4261_cast_fp16_1)[name = tensor("op_4269_cast_fp16")]; + tensor concat_119x = const()[name = tensor("concat_119x"), val = tensor([1, -1, 4, 128])]; + tensor var_4272_cast_fp16 = reshape(shape = concat_119x, x = var_4261_cast_fp16_2)[name = tensor("op_4272_cast_fp16")]; + tensor value_79_perm_0 = const()[name = tensor("value_79_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_79_cast_fp16 = mul(x = var_4261_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_79_cast_fp16")]; + tensor input_1181_perm_0 = const()[name = tensor("input_1181_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1183_pad_0 = const()[name = tensor("input_1183_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1183_mode_0 = const()[name = tensor("input_1183_mode_0"), val = tensor("constant")]; + tensor const_243_to_fp16 = const()[name = tensor("const_243_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1181_cast_fp16 = transpose(perm = input_1181_perm_0, x = inputs_79_cast_fp16)[name = tensor("transpose_534")]; + tensor input_1183_cast_fp16 = pad(constant_val = const_243_to_fp16, mode = input_1183_mode_0, pad = input_1183_pad_0, x = input_1181_cast_fp16)[name = tensor("input_1183_cast_fp16")]; + tensor x_395_pad_type_0 = const()[name = tensor("x_395_pad_type_0"), val = tensor("valid")]; + tensor x_395_groups_0 = const()[name = tensor("x_395_groups_0"), val = tensor(512)]; + tensor x_395_strides_0 = const()[name = tensor("x_395_strides_0"), val = tensor([1])]; + tensor x_395_pad_0 = const()[name = tensor("x_395_pad_0"), val = tensor([0, 0])]; + tensor x_395_dilations_0 = const()[name = tensor("x_395_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_38_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_38_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248104640)))]; + tensor x_395_cast_fp16 = conv(dilations = x_395_dilations_0, groups = x_395_groups_0, pad = x_395_pad_0, pad_type = x_395_pad_type_0, strides = x_395_strides_0, weight = encoder_encoders_38_self_attn_fsmn_block_weight_to_fp16, x = input_1183_cast_fp16)[name = tensor("x_395_cast_fp16")]; + tensor x_397_perm_0 = const()[name = tensor("x_397_perm_0"), val = tensor([0, 2, 1])]; + tensor x_397_cast_fp16 = transpose(perm = x_397_perm_0, x = x_395_cast_fp16)[name = tensor("transpose_533")]; + tensor input_1185_cast_fp16 = add(x = x_397_cast_fp16, y = inputs_79_cast_fp16)[name = tensor("input_1185_cast_fp16")]; + tensor fsmn_memory_79_cast_fp16 = mul(x = input_1185_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_79_cast_fp16")]; + tensor var_4291_to_fp16 = const()[name = tensor("op_4291_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_159_cast_fp16 = mul(x = var_4266_cast_fp16, y = var_4291_to_fp16)[name = tensor("q_h_159_cast_fp16")]; + tensor scores_157_transpose_x_0 = const()[name = tensor("scores_157_transpose_x_0"), val = tensor(false)]; + tensor scores_157_transpose_y_0 = const()[name = tensor("scores_157_transpose_y_0"), val = tensor(false)]; + tensor transpose_288_perm_0 = const()[name = tensor("transpose_288_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_289_perm_0 = const()[name = tensor("transpose_289_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_289 = transpose(perm = transpose_289_perm_0, x = var_4269_cast_fp16)[name = tensor("transpose_531")]; + tensor transpose_288 = transpose(perm = transpose_288_perm_0, x = q_h_159_cast_fp16)[name = tensor("transpose_532")]; + tensor scores_157_cast_fp16 = matmul(transpose_x = scores_157_transpose_x_0, transpose_y = scores_157_transpose_y_0, x = transpose_288, y = transpose_289)[name = tensor("scores_157_cast_fp16")]; + tensor scores_159_cast_fp16 = select(a = var_48_to_fp16, b = scores_157_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_159_cast_fp16")]; + tensor var_4299_cast_fp16 = softmax(axis = var_61, x = scores_159_cast_fp16)[name = tensor("op_4299_cast_fp16")]; + tensor input_1187_cast_fp16 = select(a = var_53_to_fp16, b = var_4299_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1187_cast_fp16")]; + tensor x_401_transpose_x_0 = const()[name = tensor("x_401_transpose_x_0"), val = tensor(false)]; + tensor x_401_transpose_y_0 = const()[name = tensor("x_401_transpose_y_0"), val = tensor(false)]; + tensor value_79_cast_fp16 = transpose(perm = value_79_perm_0, x = var_4272_cast_fp16)[name = tensor("transpose_535")]; + tensor x_401_cast_fp16 = matmul(transpose_x = x_401_transpose_x_0, transpose_y = x_401_transpose_y_0, x = input_1187_cast_fp16, y = value_79_cast_fp16)[name = tensor("x_401_cast_fp16")]; + tensor var_4303_perm_0 = const()[name = tensor("op_4303_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_4305 = const()[name = tensor("op_4305"), val = tensor([1, -1, 512])]; + tensor var_4303_cast_fp16 = transpose(perm = var_4303_perm_0, x = x_401_cast_fp16)[name = tensor("transpose_530")]; + tensor input_1189_cast_fp16 = reshape(shape = var_4305, x = var_4303_cast_fp16)[name = tensor("input_1189_cast_fp16")]; + tensor encoder_encoders_38_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_38_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248115968)))]; + tensor encoder_encoders_38_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_38_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248640320)))]; + tensor linear_157_cast_fp16 = linear(bias = encoder_encoders_38_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_38_self_attn_linear_out_weight_to_fp16, x = input_1189_cast_fp16)[name = tensor("linear_157_cast_fp16")]; + tensor input_1191_cast_fp16 = add(x = linear_157_cast_fp16, y = fsmn_memory_79_cast_fp16)[name = tensor("input_1191_cast_fp16")]; + tensor input_1193_cast_fp16 = add(x = input_1177_cast_fp16, y = input_1191_cast_fp16)[name = tensor("input_1193_cast_fp16")]; + tensor output_159_axes_0 = const()[name = tensor("output_159_axes_0"), val = tensor([-1])]; + tensor const_244_to_fp16 = const()[name = tensor("const_244_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248641408)))]; + tensor const_245_to_fp16 = const()[name = tensor("const_245_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248642496)))]; + tensor output_159_cast_fp16 = layer_norm(axes = output_159_axes_0, beta = const_245_to_fp16, epsilon = var_46_to_fp16, gamma = const_244_to_fp16, x = input_1193_cast_fp16)[name = tensor("output_159_cast_fp16")]; + tensor encoder_encoders_38_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_38_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(248643584)))]; + tensor encoder_encoders_38_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_38_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(250740800)))]; + tensor linear_158_cast_fp16 = linear(bias = encoder_encoders_38_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_38_feed_forward_w_1_weight_to_fp16, x = output_159_cast_fp16)[name = tensor("linear_158_cast_fp16")]; + tensor input_1201_cast_fp16 = relu(x = linear_158_cast_fp16)[name = tensor("input_1201_cast_fp16")]; + tensor encoder_encoders_38_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_38_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(250744960)))]; + tensor encoder_encoders_38_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_38_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252842176)))]; + tensor linear_159_cast_fp16 = linear(bias = encoder_encoders_38_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_38_feed_forward_w_2_weight_to_fp16, x = input_1201_cast_fp16)[name = tensor("linear_159_cast_fp16")]; + tensor input_1207_cast_fp16 = add(x = input_1193_cast_fp16, y = linear_159_cast_fp16)[name = tensor("input_1207_cast_fp16")]; + tensor output_161_axes_0 = const()[name = tensor("output_161_axes_0"), val = tensor([-1])]; + tensor const_246_to_fp16 = const()[name = tensor("const_246_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252843264)))]; + tensor const_247_to_fp16 = const()[name = tensor("const_247_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252844352)))]; + tensor output_161_cast_fp16 = layer_norm(axes = output_161_axes_0, beta = const_247_to_fp16, epsilon = var_46_to_fp16, gamma = const_246_to_fp16, x = input_1207_cast_fp16)[name = tensor("output_161_cast_fp16")]; + tensor encoder_encoders_39_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_39_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252845440)))]; + tensor encoder_encoders_39_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_39_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254418368)))]; + tensor linear_160_cast_fp16 = linear(bias = encoder_encoders_39_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_39_self_attn_linear_q_k_v_weight_to_fp16, x = output_161_cast_fp16)[name = tensor("linear_160_cast_fp16")]; + tensor tile_40 = const()[name = tensor("tile_40"), val = tensor([512, 512, 512])]; + tensor var_4363_axis_0 = const()[name = tensor("op_4363_axis_0"), val = tensor(-1)]; + tensor var_4363_cast_fp16_0, tensor var_4363_cast_fp16_1, tensor var_4363_cast_fp16_2 = split(axis = var_4363_axis_0, split_sizes = tile_40, x = linear_160_cast_fp16)[name = tensor("op_4363_cast_fp16")]; + tensor concat_120x = const()[name = tensor("concat_120x"), val = tensor([1, -1, 4, 128])]; + tensor var_4368_cast_fp16 = reshape(shape = concat_120x, x = var_4363_cast_fp16_0)[name = tensor("op_4368_cast_fp16")]; + tensor concat_121x = const()[name = tensor("concat_121x"), val = tensor([1, -1, 4, 128])]; + tensor var_4371_cast_fp16 = reshape(shape = concat_121x, x = var_4363_cast_fp16_1)[name = tensor("op_4371_cast_fp16")]; + tensor concat_122x = const()[name = tensor("concat_122x"), val = tensor([1, -1, 4, 128])]; + tensor var_4374_cast_fp16 = reshape(shape = concat_122x, x = var_4363_cast_fp16_2)[name = tensor("op_4374_cast_fp16")]; + tensor value_81_perm_0 = const()[name = tensor("value_81_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_81_cast_fp16 = mul(x = var_4363_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_81_cast_fp16")]; + tensor input_1211_perm_0 = const()[name = tensor("input_1211_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1213_pad_0 = const()[name = tensor("input_1213_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1213_mode_0 = const()[name = tensor("input_1213_mode_0"), val = tensor("constant")]; + tensor const_249_to_fp16 = const()[name = tensor("const_249_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1211_cast_fp16 = transpose(perm = input_1211_perm_0, x = inputs_81_cast_fp16)[name = tensor("transpose_528")]; + tensor input_1213_cast_fp16 = pad(constant_val = const_249_to_fp16, mode = input_1213_mode_0, pad = input_1213_pad_0, x = input_1211_cast_fp16)[name = tensor("input_1213_cast_fp16")]; + tensor x_405_pad_type_0 = const()[name = tensor("x_405_pad_type_0"), val = tensor("valid")]; + tensor x_405_groups_0 = const()[name = tensor("x_405_groups_0"), val = tensor(512)]; + tensor x_405_strides_0 = const()[name = tensor("x_405_strides_0"), val = tensor([1])]; + tensor x_405_pad_0 = const()[name = tensor("x_405_pad_0"), val = tensor([0, 0])]; + tensor x_405_dilations_0 = const()[name = tensor("x_405_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_39_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_39_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254421504)))]; + tensor x_405_cast_fp16 = conv(dilations = x_405_dilations_0, groups = x_405_groups_0, pad = x_405_pad_0, pad_type = x_405_pad_type_0, strides = x_405_strides_0, weight = encoder_encoders_39_self_attn_fsmn_block_weight_to_fp16, x = input_1213_cast_fp16)[name = tensor("x_405_cast_fp16")]; + tensor x_407_perm_0 = const()[name = tensor("x_407_perm_0"), val = tensor([0, 2, 1])]; + tensor x_407_cast_fp16 = transpose(perm = x_407_perm_0, x = x_405_cast_fp16)[name = tensor("transpose_527")]; + tensor input_1215_cast_fp16 = add(x = x_407_cast_fp16, y = inputs_81_cast_fp16)[name = tensor("input_1215_cast_fp16")]; + tensor fsmn_memory_81_cast_fp16 = mul(x = input_1215_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_81_cast_fp16")]; + tensor var_4393_to_fp16 = const()[name = tensor("op_4393_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_163_cast_fp16 = mul(x = var_4368_cast_fp16, y = var_4393_to_fp16)[name = tensor("q_h_163_cast_fp16")]; + tensor scores_161_transpose_x_0 = const()[name = tensor("scores_161_transpose_x_0"), val = tensor(false)]; + tensor scores_161_transpose_y_0 = const()[name = tensor("scores_161_transpose_y_0"), val = tensor(false)]; + tensor transpose_290_perm_0 = const()[name = tensor("transpose_290_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_291_perm_0 = const()[name = tensor("transpose_291_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_291 = transpose(perm = transpose_291_perm_0, x = var_4371_cast_fp16)[name = tensor("transpose_525")]; + tensor transpose_290 = transpose(perm = transpose_290_perm_0, x = q_h_163_cast_fp16)[name = tensor("transpose_526")]; + tensor scores_161_cast_fp16 = matmul(transpose_x = scores_161_transpose_x_0, transpose_y = scores_161_transpose_y_0, x = transpose_290, y = transpose_291)[name = tensor("scores_161_cast_fp16")]; + tensor scores_163_cast_fp16 = select(a = var_48_to_fp16, b = scores_161_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_163_cast_fp16")]; + tensor var_4401_cast_fp16 = softmax(axis = var_61, x = scores_163_cast_fp16)[name = tensor("op_4401_cast_fp16")]; + tensor input_1217_cast_fp16 = select(a = var_53_to_fp16, b = var_4401_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1217_cast_fp16")]; + tensor x_411_transpose_x_0 = const()[name = tensor("x_411_transpose_x_0"), val = tensor(false)]; + tensor x_411_transpose_y_0 = const()[name = tensor("x_411_transpose_y_0"), val = tensor(false)]; + tensor value_81_cast_fp16 = transpose(perm = value_81_perm_0, x = var_4374_cast_fp16)[name = tensor("transpose_529")]; + tensor x_411_cast_fp16 = matmul(transpose_x = x_411_transpose_x_0, transpose_y = x_411_transpose_y_0, x = input_1217_cast_fp16, y = value_81_cast_fp16)[name = tensor("x_411_cast_fp16")]; + tensor var_4405_perm_0 = const()[name = tensor("op_4405_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_4407 = const()[name = tensor("op_4407"), val = tensor([1, -1, 512])]; + tensor var_4405_cast_fp16 = transpose(perm = var_4405_perm_0, x = x_411_cast_fp16)[name = tensor("transpose_524")]; + tensor input_1219_cast_fp16 = reshape(shape = var_4407, x = var_4405_cast_fp16)[name = tensor("input_1219_cast_fp16")]; + tensor encoder_encoders_39_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_39_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254432832)))]; + tensor encoder_encoders_39_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_39_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254957184)))]; + tensor linear_161_cast_fp16 = linear(bias = encoder_encoders_39_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_39_self_attn_linear_out_weight_to_fp16, x = input_1219_cast_fp16)[name = tensor("linear_161_cast_fp16")]; + tensor input_1221_cast_fp16 = add(x = linear_161_cast_fp16, y = fsmn_memory_81_cast_fp16)[name = tensor("input_1221_cast_fp16")]; + tensor input_1223_cast_fp16 = add(x = input_1207_cast_fp16, y = input_1221_cast_fp16)[name = tensor("input_1223_cast_fp16")]; + tensor output_163_axes_0 = const()[name = tensor("output_163_axes_0"), val = tensor([-1])]; + tensor const_250_to_fp16 = const()[name = tensor("const_250_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254958272)))]; + tensor const_251_to_fp16 = const()[name = tensor("const_251_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254959360)))]; + tensor output_163_cast_fp16 = layer_norm(axes = output_163_axes_0, beta = const_251_to_fp16, epsilon = var_46_to_fp16, gamma = const_250_to_fp16, x = input_1223_cast_fp16)[name = tensor("output_163_cast_fp16")]; + tensor encoder_encoders_39_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_39_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254960448)))]; + tensor encoder_encoders_39_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_39_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(257057664)))]; + tensor linear_162_cast_fp16 = linear(bias = encoder_encoders_39_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_39_feed_forward_w_1_weight_to_fp16, x = output_163_cast_fp16)[name = tensor("linear_162_cast_fp16")]; + tensor input_1231_cast_fp16 = relu(x = linear_162_cast_fp16)[name = tensor("input_1231_cast_fp16")]; + tensor encoder_encoders_39_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_39_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(257061824)))]; + tensor encoder_encoders_39_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_39_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259159040)))]; + tensor linear_163_cast_fp16 = linear(bias = encoder_encoders_39_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_39_feed_forward_w_2_weight_to_fp16, x = input_1231_cast_fp16)[name = tensor("linear_163_cast_fp16")]; + tensor input_1237_cast_fp16 = add(x = input_1223_cast_fp16, y = linear_163_cast_fp16)[name = tensor("input_1237_cast_fp16")]; + tensor output_165_axes_0 = const()[name = tensor("output_165_axes_0"), val = tensor([-1])]; + tensor const_252_to_fp16 = const()[name = tensor("const_252_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259160128)))]; + tensor const_253_to_fp16 = const()[name = tensor("const_253_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259161216)))]; + tensor output_165_cast_fp16 = layer_norm(axes = output_165_axes_0, beta = const_253_to_fp16, epsilon = var_46_to_fp16, gamma = const_252_to_fp16, x = input_1237_cast_fp16)[name = tensor("output_165_cast_fp16")]; + tensor encoder_encoders_40_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_40_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259162304)))]; + tensor encoder_encoders_40_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_40_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(260735232)))]; + tensor linear_164_cast_fp16 = linear(bias = encoder_encoders_40_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_40_self_attn_linear_q_k_v_weight_to_fp16, x = output_165_cast_fp16)[name = tensor("linear_164_cast_fp16")]; + tensor tile_41 = const()[name = tensor("tile_41"), val = tensor([512, 512, 512])]; + tensor var_4465_axis_0 = const()[name = tensor("op_4465_axis_0"), val = tensor(-1)]; + tensor var_4465_cast_fp16_0, tensor var_4465_cast_fp16_1, tensor var_4465_cast_fp16_2 = split(axis = var_4465_axis_0, split_sizes = tile_41, x = linear_164_cast_fp16)[name = tensor("op_4465_cast_fp16")]; + tensor concat_123x = const()[name = tensor("concat_123x"), val = tensor([1, -1, 4, 128])]; + tensor var_4470_cast_fp16 = reshape(shape = concat_123x, x = var_4465_cast_fp16_0)[name = tensor("op_4470_cast_fp16")]; + tensor concat_124x = const()[name = tensor("concat_124x"), val = tensor([1, -1, 4, 128])]; + tensor var_4473_cast_fp16 = reshape(shape = concat_124x, x = var_4465_cast_fp16_1)[name = tensor("op_4473_cast_fp16")]; + tensor concat_125x = const()[name = tensor("concat_125x"), val = tensor([1, -1, 4, 128])]; + tensor var_4476_cast_fp16 = reshape(shape = concat_125x, x = var_4465_cast_fp16_2)[name = tensor("op_4476_cast_fp16")]; + tensor value_83_perm_0 = const()[name = tensor("value_83_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_83_cast_fp16 = mul(x = var_4465_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_83_cast_fp16")]; + tensor input_1241_perm_0 = const()[name = tensor("input_1241_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1243_pad_0 = const()[name = tensor("input_1243_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1243_mode_0 = const()[name = tensor("input_1243_mode_0"), val = tensor("constant")]; + tensor const_255_to_fp16 = const()[name = tensor("const_255_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1241_cast_fp16 = transpose(perm = input_1241_perm_0, x = inputs_83_cast_fp16)[name = tensor("transpose_522")]; + tensor input_1243_cast_fp16 = pad(constant_val = const_255_to_fp16, mode = input_1243_mode_0, pad = input_1243_pad_0, x = input_1241_cast_fp16)[name = tensor("input_1243_cast_fp16")]; + tensor x_415_pad_type_0 = const()[name = tensor("x_415_pad_type_0"), val = tensor("valid")]; + tensor x_415_groups_0 = const()[name = tensor("x_415_groups_0"), val = tensor(512)]; + tensor x_415_strides_0 = const()[name = tensor("x_415_strides_0"), val = tensor([1])]; + tensor x_415_pad_0 = const()[name = tensor("x_415_pad_0"), val = tensor([0, 0])]; + tensor x_415_dilations_0 = const()[name = tensor("x_415_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_40_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_40_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(260738368)))]; + tensor x_415_cast_fp16 = conv(dilations = x_415_dilations_0, groups = x_415_groups_0, pad = x_415_pad_0, pad_type = x_415_pad_type_0, strides = x_415_strides_0, weight = encoder_encoders_40_self_attn_fsmn_block_weight_to_fp16, x = input_1243_cast_fp16)[name = tensor("x_415_cast_fp16")]; + tensor x_417_perm_0 = const()[name = tensor("x_417_perm_0"), val = tensor([0, 2, 1])]; + tensor x_417_cast_fp16 = transpose(perm = x_417_perm_0, x = x_415_cast_fp16)[name = tensor("transpose_521")]; + tensor input_1245_cast_fp16 = add(x = x_417_cast_fp16, y = inputs_83_cast_fp16)[name = tensor("input_1245_cast_fp16")]; + tensor fsmn_memory_83_cast_fp16 = mul(x = input_1245_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_83_cast_fp16")]; + tensor var_4495_to_fp16 = const()[name = tensor("op_4495_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_167_cast_fp16 = mul(x = var_4470_cast_fp16, y = var_4495_to_fp16)[name = tensor("q_h_167_cast_fp16")]; + tensor scores_165_transpose_x_0 = const()[name = tensor("scores_165_transpose_x_0"), val = tensor(false)]; + tensor scores_165_transpose_y_0 = const()[name = tensor("scores_165_transpose_y_0"), val = tensor(false)]; + tensor transpose_292_perm_0 = const()[name = tensor("transpose_292_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_293_perm_0 = const()[name = tensor("transpose_293_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_293 = transpose(perm = transpose_293_perm_0, x = var_4473_cast_fp16)[name = tensor("transpose_519")]; + tensor transpose_292 = transpose(perm = transpose_292_perm_0, x = q_h_167_cast_fp16)[name = tensor("transpose_520")]; + tensor scores_165_cast_fp16 = matmul(transpose_x = scores_165_transpose_x_0, transpose_y = scores_165_transpose_y_0, x = transpose_292, y = transpose_293)[name = tensor("scores_165_cast_fp16")]; + tensor scores_167_cast_fp16 = select(a = var_48_to_fp16, b = scores_165_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_167_cast_fp16")]; + tensor var_4503_cast_fp16 = softmax(axis = var_61, x = scores_167_cast_fp16)[name = tensor("op_4503_cast_fp16")]; + tensor input_1247_cast_fp16 = select(a = var_53_to_fp16, b = var_4503_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1247_cast_fp16")]; + tensor x_421_transpose_x_0 = const()[name = tensor("x_421_transpose_x_0"), val = tensor(false)]; + tensor x_421_transpose_y_0 = const()[name = tensor("x_421_transpose_y_0"), val = tensor(false)]; + tensor value_83_cast_fp16 = transpose(perm = value_83_perm_0, x = var_4476_cast_fp16)[name = tensor("transpose_523")]; + tensor x_421_cast_fp16 = matmul(transpose_x = x_421_transpose_x_0, transpose_y = x_421_transpose_y_0, x = input_1247_cast_fp16, y = value_83_cast_fp16)[name = tensor("x_421_cast_fp16")]; + tensor var_4507_perm_0 = const()[name = tensor("op_4507_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_4509 = const()[name = tensor("op_4509"), val = tensor([1, -1, 512])]; + tensor var_4507_cast_fp16 = transpose(perm = var_4507_perm_0, x = x_421_cast_fp16)[name = tensor("transpose_518")]; + tensor input_1249_cast_fp16 = reshape(shape = var_4509, x = var_4507_cast_fp16)[name = tensor("input_1249_cast_fp16")]; + tensor encoder_encoders_40_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_40_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(260749696)))]; + tensor encoder_encoders_40_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_40_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(261274048)))]; + tensor linear_165_cast_fp16 = linear(bias = encoder_encoders_40_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_40_self_attn_linear_out_weight_to_fp16, x = input_1249_cast_fp16)[name = tensor("linear_165_cast_fp16")]; + tensor input_1251_cast_fp16 = add(x = linear_165_cast_fp16, y = fsmn_memory_83_cast_fp16)[name = tensor("input_1251_cast_fp16")]; + tensor input_1253_cast_fp16 = add(x = input_1237_cast_fp16, y = input_1251_cast_fp16)[name = tensor("input_1253_cast_fp16")]; + tensor output_167_axes_0 = const()[name = tensor("output_167_axes_0"), val = tensor([-1])]; + tensor const_256_to_fp16 = const()[name = tensor("const_256_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(261275136)))]; + tensor const_257_to_fp16 = const()[name = tensor("const_257_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(261276224)))]; + tensor output_167_cast_fp16 = layer_norm(axes = output_167_axes_0, beta = const_257_to_fp16, epsilon = var_46_to_fp16, gamma = const_256_to_fp16, x = input_1253_cast_fp16)[name = tensor("output_167_cast_fp16")]; + tensor encoder_encoders_40_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_40_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(261277312)))]; + tensor encoder_encoders_40_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_40_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263374528)))]; + tensor linear_166_cast_fp16 = linear(bias = encoder_encoders_40_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_40_feed_forward_w_1_weight_to_fp16, x = output_167_cast_fp16)[name = tensor("linear_166_cast_fp16")]; + tensor input_1261_cast_fp16 = relu(x = linear_166_cast_fp16)[name = tensor("input_1261_cast_fp16")]; + tensor encoder_encoders_40_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_40_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263378688)))]; + tensor encoder_encoders_40_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_40_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265475904)))]; + tensor linear_167_cast_fp16 = linear(bias = encoder_encoders_40_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_40_feed_forward_w_2_weight_to_fp16, x = input_1261_cast_fp16)[name = tensor("linear_167_cast_fp16")]; + tensor input_1267_cast_fp16 = add(x = input_1253_cast_fp16, y = linear_167_cast_fp16)[name = tensor("input_1267_cast_fp16")]; + tensor output_169_axes_0 = const()[name = tensor("output_169_axes_0"), val = tensor([-1])]; + tensor const_258_to_fp16 = const()[name = tensor("const_258_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265476992)))]; + tensor const_259_to_fp16 = const()[name = tensor("const_259_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265478080)))]; + tensor output_169_cast_fp16 = layer_norm(axes = output_169_axes_0, beta = const_259_to_fp16, epsilon = var_46_to_fp16, gamma = const_258_to_fp16, x = input_1267_cast_fp16)[name = tensor("output_169_cast_fp16")]; + tensor encoder_encoders_41_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_41_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265479168)))]; + tensor encoder_encoders_41_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_41_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267052096)))]; + tensor linear_168_cast_fp16 = linear(bias = encoder_encoders_41_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_41_self_attn_linear_q_k_v_weight_to_fp16, x = output_169_cast_fp16)[name = tensor("linear_168_cast_fp16")]; + tensor tile_42 = const()[name = tensor("tile_42"), val = tensor([512, 512, 512])]; + tensor var_4567_axis_0 = const()[name = tensor("op_4567_axis_0"), val = tensor(-1)]; + tensor var_4567_cast_fp16_0, tensor var_4567_cast_fp16_1, tensor var_4567_cast_fp16_2 = split(axis = var_4567_axis_0, split_sizes = tile_42, x = linear_168_cast_fp16)[name = tensor("op_4567_cast_fp16")]; + tensor concat_126x = const()[name = tensor("concat_126x"), val = tensor([1, -1, 4, 128])]; + tensor var_4572_cast_fp16 = reshape(shape = concat_126x, x = var_4567_cast_fp16_0)[name = tensor("op_4572_cast_fp16")]; + tensor concat_127x = const()[name = tensor("concat_127x"), val = tensor([1, -1, 4, 128])]; + tensor var_4575_cast_fp16 = reshape(shape = concat_127x, x = var_4567_cast_fp16_1)[name = tensor("op_4575_cast_fp16")]; + tensor concat_128x = const()[name = tensor("concat_128x"), val = tensor([1, -1, 4, 128])]; + tensor var_4578_cast_fp16 = reshape(shape = concat_128x, x = var_4567_cast_fp16_2)[name = tensor("op_4578_cast_fp16")]; + tensor value_85_perm_0 = const()[name = tensor("value_85_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_85_cast_fp16 = mul(x = var_4567_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_85_cast_fp16")]; + tensor input_1271_perm_0 = const()[name = tensor("input_1271_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1273_pad_0 = const()[name = tensor("input_1273_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1273_mode_0 = const()[name = tensor("input_1273_mode_0"), val = tensor("constant")]; + tensor const_261_to_fp16 = const()[name = tensor("const_261_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1271_cast_fp16 = transpose(perm = input_1271_perm_0, x = inputs_85_cast_fp16)[name = tensor("transpose_516")]; + tensor input_1273_cast_fp16 = pad(constant_val = const_261_to_fp16, mode = input_1273_mode_0, pad = input_1273_pad_0, x = input_1271_cast_fp16)[name = tensor("input_1273_cast_fp16")]; + tensor x_425_pad_type_0 = const()[name = tensor("x_425_pad_type_0"), val = tensor("valid")]; + tensor x_425_groups_0 = const()[name = tensor("x_425_groups_0"), val = tensor(512)]; + tensor x_425_strides_0 = const()[name = tensor("x_425_strides_0"), val = tensor([1])]; + tensor x_425_pad_0 = const()[name = tensor("x_425_pad_0"), val = tensor([0, 0])]; + tensor x_425_dilations_0 = const()[name = tensor("x_425_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_41_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_41_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267055232)))]; + tensor x_425_cast_fp16 = conv(dilations = x_425_dilations_0, groups = x_425_groups_0, pad = x_425_pad_0, pad_type = x_425_pad_type_0, strides = x_425_strides_0, weight = encoder_encoders_41_self_attn_fsmn_block_weight_to_fp16, x = input_1273_cast_fp16)[name = tensor("x_425_cast_fp16")]; + tensor x_427_perm_0 = const()[name = tensor("x_427_perm_0"), val = tensor([0, 2, 1])]; + tensor x_427_cast_fp16 = transpose(perm = x_427_perm_0, x = x_425_cast_fp16)[name = tensor("transpose_515")]; + tensor input_1275_cast_fp16 = add(x = x_427_cast_fp16, y = inputs_85_cast_fp16)[name = tensor("input_1275_cast_fp16")]; + tensor fsmn_memory_85_cast_fp16 = mul(x = input_1275_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_85_cast_fp16")]; + tensor var_4597_to_fp16 = const()[name = tensor("op_4597_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_171_cast_fp16 = mul(x = var_4572_cast_fp16, y = var_4597_to_fp16)[name = tensor("q_h_171_cast_fp16")]; + tensor scores_169_transpose_x_0 = const()[name = tensor("scores_169_transpose_x_0"), val = tensor(false)]; + tensor scores_169_transpose_y_0 = const()[name = tensor("scores_169_transpose_y_0"), val = tensor(false)]; + tensor transpose_294_perm_0 = const()[name = tensor("transpose_294_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_295_perm_0 = const()[name = tensor("transpose_295_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_295 = transpose(perm = transpose_295_perm_0, x = var_4575_cast_fp16)[name = tensor("transpose_513")]; + tensor transpose_294 = transpose(perm = transpose_294_perm_0, x = q_h_171_cast_fp16)[name = tensor("transpose_514")]; + tensor scores_169_cast_fp16 = matmul(transpose_x = scores_169_transpose_x_0, transpose_y = scores_169_transpose_y_0, x = transpose_294, y = transpose_295)[name = tensor("scores_169_cast_fp16")]; + tensor scores_171_cast_fp16 = select(a = var_48_to_fp16, b = scores_169_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_171_cast_fp16")]; + tensor var_4605_cast_fp16 = softmax(axis = var_61, x = scores_171_cast_fp16)[name = tensor("op_4605_cast_fp16")]; + tensor input_1277_cast_fp16 = select(a = var_53_to_fp16, b = var_4605_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1277_cast_fp16")]; + tensor x_431_transpose_x_0 = const()[name = tensor("x_431_transpose_x_0"), val = tensor(false)]; + tensor x_431_transpose_y_0 = const()[name = tensor("x_431_transpose_y_0"), val = tensor(false)]; + tensor value_85_cast_fp16 = transpose(perm = value_85_perm_0, x = var_4578_cast_fp16)[name = tensor("transpose_517")]; + tensor x_431_cast_fp16 = matmul(transpose_x = x_431_transpose_x_0, transpose_y = x_431_transpose_y_0, x = input_1277_cast_fp16, y = value_85_cast_fp16)[name = tensor("x_431_cast_fp16")]; + tensor var_4609_perm_0 = const()[name = tensor("op_4609_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_4611 = const()[name = tensor("op_4611"), val = tensor([1, -1, 512])]; + tensor var_4609_cast_fp16 = transpose(perm = var_4609_perm_0, x = x_431_cast_fp16)[name = tensor("transpose_512")]; + tensor input_1279_cast_fp16 = reshape(shape = var_4611, x = var_4609_cast_fp16)[name = tensor("input_1279_cast_fp16")]; + tensor encoder_encoders_41_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_41_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267066560)))]; + tensor encoder_encoders_41_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_41_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267590912)))]; + tensor linear_169_cast_fp16 = linear(bias = encoder_encoders_41_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_41_self_attn_linear_out_weight_to_fp16, x = input_1279_cast_fp16)[name = tensor("linear_169_cast_fp16")]; + tensor input_1281_cast_fp16 = add(x = linear_169_cast_fp16, y = fsmn_memory_85_cast_fp16)[name = tensor("input_1281_cast_fp16")]; + tensor input_1283_cast_fp16 = add(x = input_1267_cast_fp16, y = input_1281_cast_fp16)[name = tensor("input_1283_cast_fp16")]; + tensor output_171_axes_0 = const()[name = tensor("output_171_axes_0"), val = tensor([-1])]; + tensor const_262_to_fp16 = const()[name = tensor("const_262_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267592000)))]; + tensor const_263_to_fp16 = const()[name = tensor("const_263_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267593088)))]; + tensor output_171_cast_fp16 = layer_norm(axes = output_171_axes_0, beta = const_263_to_fp16, epsilon = var_46_to_fp16, gamma = const_262_to_fp16, x = input_1283_cast_fp16)[name = tensor("output_171_cast_fp16")]; + tensor encoder_encoders_41_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_41_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267594176)))]; + tensor encoder_encoders_41_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_41_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269691392)))]; + tensor linear_170_cast_fp16 = linear(bias = encoder_encoders_41_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_41_feed_forward_w_1_weight_to_fp16, x = output_171_cast_fp16)[name = tensor("linear_170_cast_fp16")]; + tensor input_1291_cast_fp16 = relu(x = linear_170_cast_fp16)[name = tensor("input_1291_cast_fp16")]; + tensor encoder_encoders_41_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_41_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(269695552)))]; + tensor encoder_encoders_41_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_41_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271792768)))]; + tensor linear_171_cast_fp16 = linear(bias = encoder_encoders_41_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_41_feed_forward_w_2_weight_to_fp16, x = input_1291_cast_fp16)[name = tensor("linear_171_cast_fp16")]; + tensor input_1297_cast_fp16 = add(x = input_1283_cast_fp16, y = linear_171_cast_fp16)[name = tensor("input_1297_cast_fp16")]; + tensor output_173_axes_0 = const()[name = tensor("output_173_axes_0"), val = tensor([-1])]; + tensor const_264_to_fp16 = const()[name = tensor("const_264_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271793856)))]; + tensor const_265_to_fp16 = const()[name = tensor("const_265_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271794944)))]; + tensor output_173_cast_fp16 = layer_norm(axes = output_173_axes_0, beta = const_265_to_fp16, epsilon = var_46_to_fp16, gamma = const_264_to_fp16, x = input_1297_cast_fp16)[name = tensor("output_173_cast_fp16")]; + tensor encoder_encoders_42_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_42_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271796032)))]; + tensor encoder_encoders_42_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_42_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273368960)))]; + tensor linear_172_cast_fp16 = linear(bias = encoder_encoders_42_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_42_self_attn_linear_q_k_v_weight_to_fp16, x = output_173_cast_fp16)[name = tensor("linear_172_cast_fp16")]; + tensor tile_43 = const()[name = tensor("tile_43"), val = tensor([512, 512, 512])]; + tensor var_4669_axis_0 = const()[name = tensor("op_4669_axis_0"), val = tensor(-1)]; + tensor var_4669_cast_fp16_0, tensor var_4669_cast_fp16_1, tensor var_4669_cast_fp16_2 = split(axis = var_4669_axis_0, split_sizes = tile_43, x = linear_172_cast_fp16)[name = tensor("op_4669_cast_fp16")]; + tensor concat_129x = const()[name = tensor("concat_129x"), val = tensor([1, -1, 4, 128])]; + tensor var_4674_cast_fp16 = reshape(shape = concat_129x, x = var_4669_cast_fp16_0)[name = tensor("op_4674_cast_fp16")]; + tensor concat_130x = const()[name = tensor("concat_130x"), val = tensor([1, -1, 4, 128])]; + tensor var_4677_cast_fp16 = reshape(shape = concat_130x, x = var_4669_cast_fp16_1)[name = tensor("op_4677_cast_fp16")]; + tensor concat_131x = const()[name = tensor("concat_131x"), val = tensor([1, -1, 4, 128])]; + tensor var_4680_cast_fp16 = reshape(shape = concat_131x, x = var_4669_cast_fp16_2)[name = tensor("op_4680_cast_fp16")]; + tensor value_87_perm_0 = const()[name = tensor("value_87_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_87_cast_fp16 = mul(x = var_4669_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_87_cast_fp16")]; + tensor input_1301_perm_0 = const()[name = tensor("input_1301_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1303_pad_0 = const()[name = tensor("input_1303_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1303_mode_0 = const()[name = tensor("input_1303_mode_0"), val = tensor("constant")]; + tensor const_267_to_fp16 = const()[name = tensor("const_267_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1301_cast_fp16 = transpose(perm = input_1301_perm_0, x = inputs_87_cast_fp16)[name = tensor("transpose_510")]; + tensor input_1303_cast_fp16 = pad(constant_val = const_267_to_fp16, mode = input_1303_mode_0, pad = input_1303_pad_0, x = input_1301_cast_fp16)[name = tensor("input_1303_cast_fp16")]; + tensor x_435_pad_type_0 = const()[name = tensor("x_435_pad_type_0"), val = tensor("valid")]; + tensor x_435_groups_0 = const()[name = tensor("x_435_groups_0"), val = tensor(512)]; + tensor x_435_strides_0 = const()[name = tensor("x_435_strides_0"), val = tensor([1])]; + tensor x_435_pad_0 = const()[name = tensor("x_435_pad_0"), val = tensor([0, 0])]; + tensor x_435_dilations_0 = const()[name = tensor("x_435_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_42_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_42_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273372096)))]; + tensor x_435_cast_fp16 = conv(dilations = x_435_dilations_0, groups = x_435_groups_0, pad = x_435_pad_0, pad_type = x_435_pad_type_0, strides = x_435_strides_0, weight = encoder_encoders_42_self_attn_fsmn_block_weight_to_fp16, x = input_1303_cast_fp16)[name = tensor("x_435_cast_fp16")]; + tensor x_437_perm_0 = const()[name = tensor("x_437_perm_0"), val = tensor([0, 2, 1])]; + tensor x_437_cast_fp16 = transpose(perm = x_437_perm_0, x = x_435_cast_fp16)[name = tensor("transpose_509")]; + tensor input_1305_cast_fp16 = add(x = x_437_cast_fp16, y = inputs_87_cast_fp16)[name = tensor("input_1305_cast_fp16")]; + tensor fsmn_memory_87_cast_fp16 = mul(x = input_1305_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_87_cast_fp16")]; + tensor var_4699_to_fp16 = const()[name = tensor("op_4699_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_175_cast_fp16 = mul(x = var_4674_cast_fp16, y = var_4699_to_fp16)[name = tensor("q_h_175_cast_fp16")]; + tensor scores_173_transpose_x_0 = const()[name = tensor("scores_173_transpose_x_0"), val = tensor(false)]; + tensor scores_173_transpose_y_0 = const()[name = tensor("scores_173_transpose_y_0"), val = tensor(false)]; + tensor transpose_296_perm_0 = const()[name = tensor("transpose_296_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_297_perm_0 = const()[name = tensor("transpose_297_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_297 = transpose(perm = transpose_297_perm_0, x = var_4677_cast_fp16)[name = tensor("transpose_507")]; + tensor transpose_296 = transpose(perm = transpose_296_perm_0, x = q_h_175_cast_fp16)[name = tensor("transpose_508")]; + tensor scores_173_cast_fp16 = matmul(transpose_x = scores_173_transpose_x_0, transpose_y = scores_173_transpose_y_0, x = transpose_296, y = transpose_297)[name = tensor("scores_173_cast_fp16")]; + tensor scores_175_cast_fp16 = select(a = var_48_to_fp16, b = scores_173_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_175_cast_fp16")]; + tensor var_4707_cast_fp16 = softmax(axis = var_61, x = scores_175_cast_fp16)[name = tensor("op_4707_cast_fp16")]; + tensor input_1307_cast_fp16 = select(a = var_53_to_fp16, b = var_4707_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1307_cast_fp16")]; + tensor x_441_transpose_x_0 = const()[name = tensor("x_441_transpose_x_0"), val = tensor(false)]; + tensor x_441_transpose_y_0 = const()[name = tensor("x_441_transpose_y_0"), val = tensor(false)]; + tensor value_87_cast_fp16 = transpose(perm = value_87_perm_0, x = var_4680_cast_fp16)[name = tensor("transpose_511")]; + tensor x_441_cast_fp16 = matmul(transpose_x = x_441_transpose_x_0, transpose_y = x_441_transpose_y_0, x = input_1307_cast_fp16, y = value_87_cast_fp16)[name = tensor("x_441_cast_fp16")]; + tensor var_4711_perm_0 = const()[name = tensor("op_4711_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_4713 = const()[name = tensor("op_4713"), val = tensor([1, -1, 512])]; + tensor var_4711_cast_fp16 = transpose(perm = var_4711_perm_0, x = x_441_cast_fp16)[name = tensor("transpose_506")]; + tensor input_1309_cast_fp16 = reshape(shape = var_4713, x = var_4711_cast_fp16)[name = tensor("input_1309_cast_fp16")]; + tensor encoder_encoders_42_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_42_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273383424)))]; + tensor encoder_encoders_42_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_42_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273907776)))]; + tensor linear_173_cast_fp16 = linear(bias = encoder_encoders_42_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_42_self_attn_linear_out_weight_to_fp16, x = input_1309_cast_fp16)[name = tensor("linear_173_cast_fp16")]; + tensor input_1311_cast_fp16 = add(x = linear_173_cast_fp16, y = fsmn_memory_87_cast_fp16)[name = tensor("input_1311_cast_fp16")]; + tensor input_1313_cast_fp16 = add(x = input_1297_cast_fp16, y = input_1311_cast_fp16)[name = tensor("input_1313_cast_fp16")]; + tensor output_175_axes_0 = const()[name = tensor("output_175_axes_0"), val = tensor([-1])]; + tensor const_268_to_fp16 = const()[name = tensor("const_268_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273908864)))]; + tensor const_269_to_fp16 = const()[name = tensor("const_269_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273909952)))]; + tensor output_175_cast_fp16 = layer_norm(axes = output_175_axes_0, beta = const_269_to_fp16, epsilon = var_46_to_fp16, gamma = const_268_to_fp16, x = input_1313_cast_fp16)[name = tensor("output_175_cast_fp16")]; + tensor encoder_encoders_42_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_42_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273911040)))]; + tensor encoder_encoders_42_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_42_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(276008256)))]; + tensor linear_174_cast_fp16 = linear(bias = encoder_encoders_42_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_42_feed_forward_w_1_weight_to_fp16, x = output_175_cast_fp16)[name = tensor("linear_174_cast_fp16")]; + tensor input_1321_cast_fp16 = relu(x = linear_174_cast_fp16)[name = tensor("input_1321_cast_fp16")]; + tensor encoder_encoders_42_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_42_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(276012416)))]; + tensor encoder_encoders_42_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_42_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278109632)))]; + tensor linear_175_cast_fp16 = linear(bias = encoder_encoders_42_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_42_feed_forward_w_2_weight_to_fp16, x = input_1321_cast_fp16)[name = tensor("linear_175_cast_fp16")]; + tensor input_1327_cast_fp16 = add(x = input_1313_cast_fp16, y = linear_175_cast_fp16)[name = tensor("input_1327_cast_fp16")]; + tensor output_177_axes_0 = const()[name = tensor("output_177_axes_0"), val = tensor([-1])]; + tensor const_270_to_fp16 = const()[name = tensor("const_270_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278110720)))]; + tensor const_271_to_fp16 = const()[name = tensor("const_271_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278111808)))]; + tensor output_177_cast_fp16 = layer_norm(axes = output_177_axes_0, beta = const_271_to_fp16, epsilon = var_46_to_fp16, gamma = const_270_to_fp16, x = input_1327_cast_fp16)[name = tensor("output_177_cast_fp16")]; + tensor encoder_encoders_43_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_43_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278112896)))]; + tensor encoder_encoders_43_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_43_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279685824)))]; + tensor linear_176_cast_fp16 = linear(bias = encoder_encoders_43_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_43_self_attn_linear_q_k_v_weight_to_fp16, x = output_177_cast_fp16)[name = tensor("linear_176_cast_fp16")]; + tensor tile_44 = const()[name = tensor("tile_44"), val = tensor([512, 512, 512])]; + tensor var_4771_axis_0 = const()[name = tensor("op_4771_axis_0"), val = tensor(-1)]; + tensor var_4771_cast_fp16_0, tensor var_4771_cast_fp16_1, tensor var_4771_cast_fp16_2 = split(axis = var_4771_axis_0, split_sizes = tile_44, x = linear_176_cast_fp16)[name = tensor("op_4771_cast_fp16")]; + tensor concat_132x = const()[name = tensor("concat_132x"), val = tensor([1, -1, 4, 128])]; + tensor var_4776_cast_fp16 = reshape(shape = concat_132x, x = var_4771_cast_fp16_0)[name = tensor("op_4776_cast_fp16")]; + tensor concat_133x = const()[name = tensor("concat_133x"), val = tensor([1, -1, 4, 128])]; + tensor var_4779_cast_fp16 = reshape(shape = concat_133x, x = var_4771_cast_fp16_1)[name = tensor("op_4779_cast_fp16")]; + tensor concat_134x = const()[name = tensor("concat_134x"), val = tensor([1, -1, 4, 128])]; + tensor var_4782_cast_fp16 = reshape(shape = concat_134x, x = var_4771_cast_fp16_2)[name = tensor("op_4782_cast_fp16")]; + tensor value_89_perm_0 = const()[name = tensor("value_89_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_89_cast_fp16 = mul(x = var_4771_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_89_cast_fp16")]; + tensor input_1331_perm_0 = const()[name = tensor("input_1331_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1333_pad_0 = const()[name = tensor("input_1333_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1333_mode_0 = const()[name = tensor("input_1333_mode_0"), val = tensor("constant")]; + tensor const_273_to_fp16 = const()[name = tensor("const_273_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1331_cast_fp16 = transpose(perm = input_1331_perm_0, x = inputs_89_cast_fp16)[name = tensor("transpose_504")]; + tensor input_1333_cast_fp16 = pad(constant_val = const_273_to_fp16, mode = input_1333_mode_0, pad = input_1333_pad_0, x = input_1331_cast_fp16)[name = tensor("input_1333_cast_fp16")]; + tensor x_445_pad_type_0 = const()[name = tensor("x_445_pad_type_0"), val = tensor("valid")]; + tensor x_445_groups_0 = const()[name = tensor("x_445_groups_0"), val = tensor(512)]; + tensor x_445_strides_0 = const()[name = tensor("x_445_strides_0"), val = tensor([1])]; + tensor x_445_pad_0 = const()[name = tensor("x_445_pad_0"), val = tensor([0, 0])]; + tensor x_445_dilations_0 = const()[name = tensor("x_445_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_43_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_43_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279688960)))]; + tensor x_445_cast_fp16 = conv(dilations = x_445_dilations_0, groups = x_445_groups_0, pad = x_445_pad_0, pad_type = x_445_pad_type_0, strides = x_445_strides_0, weight = encoder_encoders_43_self_attn_fsmn_block_weight_to_fp16, x = input_1333_cast_fp16)[name = tensor("x_445_cast_fp16")]; + tensor x_447_perm_0 = const()[name = tensor("x_447_perm_0"), val = tensor([0, 2, 1])]; + tensor x_447_cast_fp16 = transpose(perm = x_447_perm_0, x = x_445_cast_fp16)[name = tensor("transpose_503")]; + tensor input_1335_cast_fp16 = add(x = x_447_cast_fp16, y = inputs_89_cast_fp16)[name = tensor("input_1335_cast_fp16")]; + tensor fsmn_memory_89_cast_fp16 = mul(x = input_1335_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_89_cast_fp16")]; + tensor var_4801_to_fp16 = const()[name = tensor("op_4801_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_179_cast_fp16 = mul(x = var_4776_cast_fp16, y = var_4801_to_fp16)[name = tensor("q_h_179_cast_fp16")]; + tensor scores_177_transpose_x_0 = const()[name = tensor("scores_177_transpose_x_0"), val = tensor(false)]; + tensor scores_177_transpose_y_0 = const()[name = tensor("scores_177_transpose_y_0"), val = tensor(false)]; + tensor transpose_298_perm_0 = const()[name = tensor("transpose_298_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_299_perm_0 = const()[name = tensor("transpose_299_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_299 = transpose(perm = transpose_299_perm_0, x = var_4779_cast_fp16)[name = tensor("transpose_501")]; + tensor transpose_298 = transpose(perm = transpose_298_perm_0, x = q_h_179_cast_fp16)[name = tensor("transpose_502")]; + tensor scores_177_cast_fp16 = matmul(transpose_x = scores_177_transpose_x_0, transpose_y = scores_177_transpose_y_0, x = transpose_298, y = transpose_299)[name = tensor("scores_177_cast_fp16")]; + tensor scores_179_cast_fp16 = select(a = var_48_to_fp16, b = scores_177_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_179_cast_fp16")]; + tensor var_4809_cast_fp16 = softmax(axis = var_61, x = scores_179_cast_fp16)[name = tensor("op_4809_cast_fp16")]; + tensor input_1337_cast_fp16 = select(a = var_53_to_fp16, b = var_4809_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1337_cast_fp16")]; + tensor x_451_transpose_x_0 = const()[name = tensor("x_451_transpose_x_0"), val = tensor(false)]; + tensor x_451_transpose_y_0 = const()[name = tensor("x_451_transpose_y_0"), val = tensor(false)]; + tensor value_89_cast_fp16 = transpose(perm = value_89_perm_0, x = var_4782_cast_fp16)[name = tensor("transpose_505")]; + tensor x_451_cast_fp16 = matmul(transpose_x = x_451_transpose_x_0, transpose_y = x_451_transpose_y_0, x = input_1337_cast_fp16, y = value_89_cast_fp16)[name = tensor("x_451_cast_fp16")]; + tensor var_4813_perm_0 = const()[name = tensor("op_4813_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_4815 = const()[name = tensor("op_4815"), val = tensor([1, -1, 512])]; + tensor var_4813_cast_fp16 = transpose(perm = var_4813_perm_0, x = x_451_cast_fp16)[name = tensor("transpose_500")]; + tensor input_1339_cast_fp16 = reshape(shape = var_4815, x = var_4813_cast_fp16)[name = tensor("input_1339_cast_fp16")]; + tensor encoder_encoders_43_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_43_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279700288)))]; + tensor encoder_encoders_43_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_43_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280224640)))]; + tensor linear_177_cast_fp16 = linear(bias = encoder_encoders_43_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_43_self_attn_linear_out_weight_to_fp16, x = input_1339_cast_fp16)[name = tensor("linear_177_cast_fp16")]; + tensor input_1341_cast_fp16 = add(x = linear_177_cast_fp16, y = fsmn_memory_89_cast_fp16)[name = tensor("input_1341_cast_fp16")]; + tensor input_1343_cast_fp16 = add(x = input_1327_cast_fp16, y = input_1341_cast_fp16)[name = tensor("input_1343_cast_fp16")]; + tensor output_179_axes_0 = const()[name = tensor("output_179_axes_0"), val = tensor([-1])]; + tensor const_274_to_fp16 = const()[name = tensor("const_274_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280225728)))]; + tensor const_275_to_fp16 = const()[name = tensor("const_275_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280226816)))]; + tensor output_179_cast_fp16 = layer_norm(axes = output_179_axes_0, beta = const_275_to_fp16, epsilon = var_46_to_fp16, gamma = const_274_to_fp16, x = input_1343_cast_fp16)[name = tensor("output_179_cast_fp16")]; + tensor encoder_encoders_43_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_43_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280227904)))]; + tensor encoder_encoders_43_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_43_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(282325120)))]; + tensor linear_178_cast_fp16 = linear(bias = encoder_encoders_43_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_43_feed_forward_w_1_weight_to_fp16, x = output_179_cast_fp16)[name = tensor("linear_178_cast_fp16")]; + tensor input_1351_cast_fp16 = relu(x = linear_178_cast_fp16)[name = tensor("input_1351_cast_fp16")]; + tensor encoder_encoders_43_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_43_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(282329280)))]; + tensor encoder_encoders_43_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_43_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284426496)))]; + tensor linear_179_cast_fp16 = linear(bias = encoder_encoders_43_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_43_feed_forward_w_2_weight_to_fp16, x = input_1351_cast_fp16)[name = tensor("linear_179_cast_fp16")]; + tensor input_1357_cast_fp16 = add(x = input_1343_cast_fp16, y = linear_179_cast_fp16)[name = tensor("input_1357_cast_fp16")]; + tensor output_181_axes_0 = const()[name = tensor("output_181_axes_0"), val = tensor([-1])]; + tensor const_276_to_fp16 = const()[name = tensor("const_276_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284427584)))]; + tensor const_277_to_fp16 = const()[name = tensor("const_277_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284428672)))]; + tensor output_181_cast_fp16 = layer_norm(axes = output_181_axes_0, beta = const_277_to_fp16, epsilon = var_46_to_fp16, gamma = const_276_to_fp16, x = input_1357_cast_fp16)[name = tensor("output_181_cast_fp16")]; + tensor encoder_encoders_44_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_44_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284429760)))]; + tensor encoder_encoders_44_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_44_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286002688)))]; + tensor linear_180_cast_fp16 = linear(bias = encoder_encoders_44_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_44_self_attn_linear_q_k_v_weight_to_fp16, x = output_181_cast_fp16)[name = tensor("linear_180_cast_fp16")]; + tensor tile_45 = const()[name = tensor("tile_45"), val = tensor([512, 512, 512])]; + tensor var_4873_axis_0 = const()[name = tensor("op_4873_axis_0"), val = tensor(-1)]; + tensor var_4873_cast_fp16_0, tensor var_4873_cast_fp16_1, tensor var_4873_cast_fp16_2 = split(axis = var_4873_axis_0, split_sizes = tile_45, x = linear_180_cast_fp16)[name = tensor("op_4873_cast_fp16")]; + tensor concat_135x = const()[name = tensor("concat_135x"), val = tensor([1, -1, 4, 128])]; + tensor var_4878_cast_fp16 = reshape(shape = concat_135x, x = var_4873_cast_fp16_0)[name = tensor("op_4878_cast_fp16")]; + tensor concat_136x = const()[name = tensor("concat_136x"), val = tensor([1, -1, 4, 128])]; + tensor var_4881_cast_fp16 = reshape(shape = concat_136x, x = var_4873_cast_fp16_1)[name = tensor("op_4881_cast_fp16")]; + tensor concat_137x = const()[name = tensor("concat_137x"), val = tensor([1, -1, 4, 128])]; + tensor var_4884_cast_fp16 = reshape(shape = concat_137x, x = var_4873_cast_fp16_2)[name = tensor("op_4884_cast_fp16")]; + tensor value_91_perm_0 = const()[name = tensor("value_91_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_91_cast_fp16 = mul(x = var_4873_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_91_cast_fp16")]; + tensor input_1361_perm_0 = const()[name = tensor("input_1361_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1363_pad_0 = const()[name = tensor("input_1363_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1363_mode_0 = const()[name = tensor("input_1363_mode_0"), val = tensor("constant")]; + tensor const_279_to_fp16 = const()[name = tensor("const_279_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1361_cast_fp16 = transpose(perm = input_1361_perm_0, x = inputs_91_cast_fp16)[name = tensor("transpose_498")]; + tensor input_1363_cast_fp16 = pad(constant_val = const_279_to_fp16, mode = input_1363_mode_0, pad = input_1363_pad_0, x = input_1361_cast_fp16)[name = tensor("input_1363_cast_fp16")]; + tensor x_455_pad_type_0 = const()[name = tensor("x_455_pad_type_0"), val = tensor("valid")]; + tensor x_455_groups_0 = const()[name = tensor("x_455_groups_0"), val = tensor(512)]; + tensor x_455_strides_0 = const()[name = tensor("x_455_strides_0"), val = tensor([1])]; + tensor x_455_pad_0 = const()[name = tensor("x_455_pad_0"), val = tensor([0, 0])]; + tensor x_455_dilations_0 = const()[name = tensor("x_455_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_44_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_44_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286005824)))]; + tensor x_455_cast_fp16 = conv(dilations = x_455_dilations_0, groups = x_455_groups_0, pad = x_455_pad_0, pad_type = x_455_pad_type_0, strides = x_455_strides_0, weight = encoder_encoders_44_self_attn_fsmn_block_weight_to_fp16, x = input_1363_cast_fp16)[name = tensor("x_455_cast_fp16")]; + tensor x_457_perm_0 = const()[name = tensor("x_457_perm_0"), val = tensor([0, 2, 1])]; + tensor x_457_cast_fp16 = transpose(perm = x_457_perm_0, x = x_455_cast_fp16)[name = tensor("transpose_497")]; + tensor input_1365_cast_fp16 = add(x = x_457_cast_fp16, y = inputs_91_cast_fp16)[name = tensor("input_1365_cast_fp16")]; + tensor fsmn_memory_91_cast_fp16 = mul(x = input_1365_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_91_cast_fp16")]; + tensor var_4903_to_fp16 = const()[name = tensor("op_4903_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_183_cast_fp16 = mul(x = var_4878_cast_fp16, y = var_4903_to_fp16)[name = tensor("q_h_183_cast_fp16")]; + tensor scores_181_transpose_x_0 = const()[name = tensor("scores_181_transpose_x_0"), val = tensor(false)]; + tensor scores_181_transpose_y_0 = const()[name = tensor("scores_181_transpose_y_0"), val = tensor(false)]; + tensor transpose_300_perm_0 = const()[name = tensor("transpose_300_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_301_perm_0 = const()[name = tensor("transpose_301_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_301 = transpose(perm = transpose_301_perm_0, x = var_4881_cast_fp16)[name = tensor("transpose_495")]; + tensor transpose_300 = transpose(perm = transpose_300_perm_0, x = q_h_183_cast_fp16)[name = tensor("transpose_496")]; + tensor scores_181_cast_fp16 = matmul(transpose_x = scores_181_transpose_x_0, transpose_y = scores_181_transpose_y_0, x = transpose_300, y = transpose_301)[name = tensor("scores_181_cast_fp16")]; + tensor scores_183_cast_fp16 = select(a = var_48_to_fp16, b = scores_181_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_183_cast_fp16")]; + tensor var_4911_cast_fp16 = softmax(axis = var_61, x = scores_183_cast_fp16)[name = tensor("op_4911_cast_fp16")]; + tensor input_1367_cast_fp16 = select(a = var_53_to_fp16, b = var_4911_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1367_cast_fp16")]; + tensor x_461_transpose_x_0 = const()[name = tensor("x_461_transpose_x_0"), val = tensor(false)]; + tensor x_461_transpose_y_0 = const()[name = tensor("x_461_transpose_y_0"), val = tensor(false)]; + tensor value_91_cast_fp16 = transpose(perm = value_91_perm_0, x = var_4884_cast_fp16)[name = tensor("transpose_499")]; + tensor x_461_cast_fp16 = matmul(transpose_x = x_461_transpose_x_0, transpose_y = x_461_transpose_y_0, x = input_1367_cast_fp16, y = value_91_cast_fp16)[name = tensor("x_461_cast_fp16")]; + tensor var_4915_perm_0 = const()[name = tensor("op_4915_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_4917 = const()[name = tensor("op_4917"), val = tensor([1, -1, 512])]; + tensor var_4915_cast_fp16 = transpose(perm = var_4915_perm_0, x = x_461_cast_fp16)[name = tensor("transpose_494")]; + tensor input_1369_cast_fp16 = reshape(shape = var_4917, x = var_4915_cast_fp16)[name = tensor("input_1369_cast_fp16")]; + tensor encoder_encoders_44_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_44_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286017152)))]; + tensor encoder_encoders_44_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_44_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286541504)))]; + tensor linear_181_cast_fp16 = linear(bias = encoder_encoders_44_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_44_self_attn_linear_out_weight_to_fp16, x = input_1369_cast_fp16)[name = tensor("linear_181_cast_fp16")]; + tensor input_1371_cast_fp16 = add(x = linear_181_cast_fp16, y = fsmn_memory_91_cast_fp16)[name = tensor("input_1371_cast_fp16")]; + tensor input_1373_cast_fp16 = add(x = input_1357_cast_fp16, y = input_1371_cast_fp16)[name = tensor("input_1373_cast_fp16")]; + tensor output_183_axes_0 = const()[name = tensor("output_183_axes_0"), val = tensor([-1])]; + tensor const_280_to_fp16 = const()[name = tensor("const_280_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286542592)))]; + tensor const_281_to_fp16 = const()[name = tensor("const_281_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286543680)))]; + tensor output_183_cast_fp16 = layer_norm(axes = output_183_axes_0, beta = const_281_to_fp16, epsilon = var_46_to_fp16, gamma = const_280_to_fp16, x = input_1373_cast_fp16)[name = tensor("output_183_cast_fp16")]; + tensor encoder_encoders_44_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_44_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286544768)))]; + tensor encoder_encoders_44_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_44_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(288641984)))]; + tensor linear_182_cast_fp16 = linear(bias = encoder_encoders_44_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_44_feed_forward_w_1_weight_to_fp16, x = output_183_cast_fp16)[name = tensor("linear_182_cast_fp16")]; + tensor input_1381_cast_fp16 = relu(x = linear_182_cast_fp16)[name = tensor("input_1381_cast_fp16")]; + tensor encoder_encoders_44_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_44_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(288646144)))]; + tensor encoder_encoders_44_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_44_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290743360)))]; + tensor linear_183_cast_fp16 = linear(bias = encoder_encoders_44_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_44_feed_forward_w_2_weight_to_fp16, x = input_1381_cast_fp16)[name = tensor("linear_183_cast_fp16")]; + tensor input_1387_cast_fp16 = add(x = input_1373_cast_fp16, y = linear_183_cast_fp16)[name = tensor("input_1387_cast_fp16")]; + tensor output_185_axes_0 = const()[name = tensor("output_185_axes_0"), val = tensor([-1])]; + tensor const_282_to_fp16 = const()[name = tensor("const_282_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290744448)))]; + tensor const_283_to_fp16 = const()[name = tensor("const_283_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290745536)))]; + tensor output_185_cast_fp16 = layer_norm(axes = output_185_axes_0, beta = const_283_to_fp16, epsilon = var_46_to_fp16, gamma = const_282_to_fp16, x = input_1387_cast_fp16)[name = tensor("output_185_cast_fp16")]; + tensor encoder_encoders_45_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_45_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290746624)))]; + tensor encoder_encoders_45_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_45_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292319552)))]; + tensor linear_184_cast_fp16 = linear(bias = encoder_encoders_45_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_45_self_attn_linear_q_k_v_weight_to_fp16, x = output_185_cast_fp16)[name = tensor("linear_184_cast_fp16")]; + tensor tile_46 = const()[name = tensor("tile_46"), val = tensor([512, 512, 512])]; + tensor var_4975_axis_0 = const()[name = tensor("op_4975_axis_0"), val = tensor(-1)]; + tensor var_4975_cast_fp16_0, tensor var_4975_cast_fp16_1, tensor var_4975_cast_fp16_2 = split(axis = var_4975_axis_0, split_sizes = tile_46, x = linear_184_cast_fp16)[name = tensor("op_4975_cast_fp16")]; + tensor concat_138x = const()[name = tensor("concat_138x"), val = tensor([1, -1, 4, 128])]; + tensor var_4980_cast_fp16 = reshape(shape = concat_138x, x = var_4975_cast_fp16_0)[name = tensor("op_4980_cast_fp16")]; + tensor concat_139x = const()[name = tensor("concat_139x"), val = tensor([1, -1, 4, 128])]; + tensor var_4983_cast_fp16 = reshape(shape = concat_139x, x = var_4975_cast_fp16_1)[name = tensor("op_4983_cast_fp16")]; + tensor concat_140x = const()[name = tensor("concat_140x"), val = tensor([1, -1, 4, 128])]; + tensor var_4986_cast_fp16 = reshape(shape = concat_140x, x = var_4975_cast_fp16_2)[name = tensor("op_4986_cast_fp16")]; + tensor value_93_perm_0 = const()[name = tensor("value_93_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_93_cast_fp16 = mul(x = var_4975_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_93_cast_fp16")]; + tensor input_1391_perm_0 = const()[name = tensor("input_1391_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1393_pad_0 = const()[name = tensor("input_1393_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1393_mode_0 = const()[name = tensor("input_1393_mode_0"), val = tensor("constant")]; + tensor const_285_to_fp16 = const()[name = tensor("const_285_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1391_cast_fp16 = transpose(perm = input_1391_perm_0, x = inputs_93_cast_fp16)[name = tensor("transpose_492")]; + tensor input_1393_cast_fp16 = pad(constant_val = const_285_to_fp16, mode = input_1393_mode_0, pad = input_1393_pad_0, x = input_1391_cast_fp16)[name = tensor("input_1393_cast_fp16")]; + tensor x_465_pad_type_0 = const()[name = tensor("x_465_pad_type_0"), val = tensor("valid")]; + tensor x_465_groups_0 = const()[name = tensor("x_465_groups_0"), val = tensor(512)]; + tensor x_465_strides_0 = const()[name = tensor("x_465_strides_0"), val = tensor([1])]; + tensor x_465_pad_0 = const()[name = tensor("x_465_pad_0"), val = tensor([0, 0])]; + tensor x_465_dilations_0 = const()[name = tensor("x_465_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_45_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_45_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292322688)))]; + tensor x_465_cast_fp16 = conv(dilations = x_465_dilations_0, groups = x_465_groups_0, pad = x_465_pad_0, pad_type = x_465_pad_type_0, strides = x_465_strides_0, weight = encoder_encoders_45_self_attn_fsmn_block_weight_to_fp16, x = input_1393_cast_fp16)[name = tensor("x_465_cast_fp16")]; + tensor x_467_perm_0 = const()[name = tensor("x_467_perm_0"), val = tensor([0, 2, 1])]; + tensor x_467_cast_fp16 = transpose(perm = x_467_perm_0, x = x_465_cast_fp16)[name = tensor("transpose_491")]; + tensor input_1395_cast_fp16 = add(x = x_467_cast_fp16, y = inputs_93_cast_fp16)[name = tensor("input_1395_cast_fp16")]; + tensor fsmn_memory_93_cast_fp16 = mul(x = input_1395_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_93_cast_fp16")]; + tensor var_5005_to_fp16 = const()[name = tensor("op_5005_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_187_cast_fp16 = mul(x = var_4980_cast_fp16, y = var_5005_to_fp16)[name = tensor("q_h_187_cast_fp16")]; + tensor scores_185_transpose_x_0 = const()[name = tensor("scores_185_transpose_x_0"), val = tensor(false)]; + tensor scores_185_transpose_y_0 = const()[name = tensor("scores_185_transpose_y_0"), val = tensor(false)]; + tensor transpose_302_perm_0 = const()[name = tensor("transpose_302_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_303_perm_0 = const()[name = tensor("transpose_303_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_303 = transpose(perm = transpose_303_perm_0, x = var_4983_cast_fp16)[name = tensor("transpose_489")]; + tensor transpose_302 = transpose(perm = transpose_302_perm_0, x = q_h_187_cast_fp16)[name = tensor("transpose_490")]; + tensor scores_185_cast_fp16 = matmul(transpose_x = scores_185_transpose_x_0, transpose_y = scores_185_transpose_y_0, x = transpose_302, y = transpose_303)[name = tensor("scores_185_cast_fp16")]; + tensor scores_187_cast_fp16 = select(a = var_48_to_fp16, b = scores_185_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_187_cast_fp16")]; + tensor var_5013_cast_fp16 = softmax(axis = var_61, x = scores_187_cast_fp16)[name = tensor("op_5013_cast_fp16")]; + tensor input_1397_cast_fp16 = select(a = var_53_to_fp16, b = var_5013_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1397_cast_fp16")]; + tensor x_471_transpose_x_0 = const()[name = tensor("x_471_transpose_x_0"), val = tensor(false)]; + tensor x_471_transpose_y_0 = const()[name = tensor("x_471_transpose_y_0"), val = tensor(false)]; + tensor value_93_cast_fp16 = transpose(perm = value_93_perm_0, x = var_4986_cast_fp16)[name = tensor("transpose_493")]; + tensor x_471_cast_fp16 = matmul(transpose_x = x_471_transpose_x_0, transpose_y = x_471_transpose_y_0, x = input_1397_cast_fp16, y = value_93_cast_fp16)[name = tensor("x_471_cast_fp16")]; + tensor var_5017_perm_0 = const()[name = tensor("op_5017_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_5019 = const()[name = tensor("op_5019"), val = tensor([1, -1, 512])]; + tensor var_5017_cast_fp16 = transpose(perm = var_5017_perm_0, x = x_471_cast_fp16)[name = tensor("transpose_488")]; + tensor input_1399_cast_fp16 = reshape(shape = var_5019, x = var_5017_cast_fp16)[name = tensor("input_1399_cast_fp16")]; + tensor encoder_encoders_45_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_45_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292334016)))]; + tensor encoder_encoders_45_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_45_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292858368)))]; + tensor linear_185_cast_fp16 = linear(bias = encoder_encoders_45_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_45_self_attn_linear_out_weight_to_fp16, x = input_1399_cast_fp16)[name = tensor("linear_185_cast_fp16")]; + tensor input_1401_cast_fp16 = add(x = linear_185_cast_fp16, y = fsmn_memory_93_cast_fp16)[name = tensor("input_1401_cast_fp16")]; + tensor input_1403_cast_fp16 = add(x = input_1387_cast_fp16, y = input_1401_cast_fp16)[name = tensor("input_1403_cast_fp16")]; + tensor output_187_axes_0 = const()[name = tensor("output_187_axes_0"), val = tensor([-1])]; + tensor const_286_to_fp16 = const()[name = tensor("const_286_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292859456)))]; + tensor const_287_to_fp16 = const()[name = tensor("const_287_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292860544)))]; + tensor output_187_cast_fp16 = layer_norm(axes = output_187_axes_0, beta = const_287_to_fp16, epsilon = var_46_to_fp16, gamma = const_286_to_fp16, x = input_1403_cast_fp16)[name = tensor("output_187_cast_fp16")]; + tensor encoder_encoders_45_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_45_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292861632)))]; + tensor encoder_encoders_45_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_45_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(294958848)))]; + tensor linear_186_cast_fp16 = linear(bias = encoder_encoders_45_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_45_feed_forward_w_1_weight_to_fp16, x = output_187_cast_fp16)[name = tensor("linear_186_cast_fp16")]; + tensor input_1411_cast_fp16 = relu(x = linear_186_cast_fp16)[name = tensor("input_1411_cast_fp16")]; + tensor encoder_encoders_45_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_45_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(294963008)))]; + tensor encoder_encoders_45_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_45_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297060224)))]; + tensor linear_187_cast_fp16 = linear(bias = encoder_encoders_45_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_45_feed_forward_w_2_weight_to_fp16, x = input_1411_cast_fp16)[name = tensor("linear_187_cast_fp16")]; + tensor input_1417_cast_fp16 = add(x = input_1403_cast_fp16, y = linear_187_cast_fp16)[name = tensor("input_1417_cast_fp16")]; + tensor output_189_axes_0 = const()[name = tensor("output_189_axes_0"), val = tensor([-1])]; + tensor const_288_to_fp16 = const()[name = tensor("const_288_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297061312)))]; + tensor const_289_to_fp16 = const()[name = tensor("const_289_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297062400)))]; + tensor output_189_cast_fp16 = layer_norm(axes = output_189_axes_0, beta = const_289_to_fp16, epsilon = var_46_to_fp16, gamma = const_288_to_fp16, x = input_1417_cast_fp16)[name = tensor("output_189_cast_fp16")]; + tensor encoder_encoders_46_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_46_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297063488)))]; + tensor encoder_encoders_46_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_46_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(298636416)))]; + tensor linear_188_cast_fp16 = linear(bias = encoder_encoders_46_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_46_self_attn_linear_q_k_v_weight_to_fp16, x = output_189_cast_fp16)[name = tensor("linear_188_cast_fp16")]; + tensor tile_47 = const()[name = tensor("tile_47"), val = tensor([512, 512, 512])]; + tensor var_5077_axis_0 = const()[name = tensor("op_5077_axis_0"), val = tensor(-1)]; + tensor var_5077_cast_fp16_0, tensor var_5077_cast_fp16_1, tensor var_5077_cast_fp16_2 = split(axis = var_5077_axis_0, split_sizes = tile_47, x = linear_188_cast_fp16)[name = tensor("op_5077_cast_fp16")]; + tensor concat_141x = const()[name = tensor("concat_141x"), val = tensor([1, -1, 4, 128])]; + tensor var_5082_cast_fp16 = reshape(shape = concat_141x, x = var_5077_cast_fp16_0)[name = tensor("op_5082_cast_fp16")]; + tensor concat_142x = const()[name = tensor("concat_142x"), val = tensor([1, -1, 4, 128])]; + tensor var_5085_cast_fp16 = reshape(shape = concat_142x, x = var_5077_cast_fp16_1)[name = tensor("op_5085_cast_fp16")]; + tensor concat_143x = const()[name = tensor("concat_143x"), val = tensor([1, -1, 4, 128])]; + tensor var_5088_cast_fp16 = reshape(shape = concat_143x, x = var_5077_cast_fp16_2)[name = tensor("op_5088_cast_fp16")]; + tensor value_95_perm_0 = const()[name = tensor("value_95_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_95_cast_fp16 = mul(x = var_5077_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_95_cast_fp16")]; + tensor input_1421_perm_0 = const()[name = tensor("input_1421_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1423_pad_0 = const()[name = tensor("input_1423_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1423_mode_0 = const()[name = tensor("input_1423_mode_0"), val = tensor("constant")]; + tensor const_291_to_fp16 = const()[name = tensor("const_291_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1421_cast_fp16 = transpose(perm = input_1421_perm_0, x = inputs_95_cast_fp16)[name = tensor("transpose_486")]; + tensor input_1423_cast_fp16 = pad(constant_val = const_291_to_fp16, mode = input_1423_mode_0, pad = input_1423_pad_0, x = input_1421_cast_fp16)[name = tensor("input_1423_cast_fp16")]; + tensor x_475_pad_type_0 = const()[name = tensor("x_475_pad_type_0"), val = tensor("valid")]; + tensor x_475_groups_0 = const()[name = tensor("x_475_groups_0"), val = tensor(512)]; + tensor x_475_strides_0 = const()[name = tensor("x_475_strides_0"), val = tensor([1])]; + tensor x_475_pad_0 = const()[name = tensor("x_475_pad_0"), val = tensor([0, 0])]; + tensor x_475_dilations_0 = const()[name = tensor("x_475_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_46_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_46_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(298639552)))]; + tensor x_475_cast_fp16 = conv(dilations = x_475_dilations_0, groups = x_475_groups_0, pad = x_475_pad_0, pad_type = x_475_pad_type_0, strides = x_475_strides_0, weight = encoder_encoders_46_self_attn_fsmn_block_weight_to_fp16, x = input_1423_cast_fp16)[name = tensor("x_475_cast_fp16")]; + tensor x_477_perm_0 = const()[name = tensor("x_477_perm_0"), val = tensor([0, 2, 1])]; + tensor x_477_cast_fp16 = transpose(perm = x_477_perm_0, x = x_475_cast_fp16)[name = tensor("transpose_485")]; + tensor input_1425_cast_fp16 = add(x = x_477_cast_fp16, y = inputs_95_cast_fp16)[name = tensor("input_1425_cast_fp16")]; + tensor fsmn_memory_95_cast_fp16 = mul(x = input_1425_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_95_cast_fp16")]; + tensor var_5107_to_fp16 = const()[name = tensor("op_5107_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_191_cast_fp16 = mul(x = var_5082_cast_fp16, y = var_5107_to_fp16)[name = tensor("q_h_191_cast_fp16")]; + tensor scores_189_transpose_x_0 = const()[name = tensor("scores_189_transpose_x_0"), val = tensor(false)]; + tensor scores_189_transpose_y_0 = const()[name = tensor("scores_189_transpose_y_0"), val = tensor(false)]; + tensor transpose_304_perm_0 = const()[name = tensor("transpose_304_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_305_perm_0 = const()[name = tensor("transpose_305_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_305 = transpose(perm = transpose_305_perm_0, x = var_5085_cast_fp16)[name = tensor("transpose_483")]; + tensor transpose_304 = transpose(perm = transpose_304_perm_0, x = q_h_191_cast_fp16)[name = tensor("transpose_484")]; + tensor scores_189_cast_fp16 = matmul(transpose_x = scores_189_transpose_x_0, transpose_y = scores_189_transpose_y_0, x = transpose_304, y = transpose_305)[name = tensor("scores_189_cast_fp16")]; + tensor scores_191_cast_fp16 = select(a = var_48_to_fp16, b = scores_189_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_191_cast_fp16")]; + tensor var_5115_cast_fp16 = softmax(axis = var_61, x = scores_191_cast_fp16)[name = tensor("op_5115_cast_fp16")]; + tensor input_1427_cast_fp16 = select(a = var_53_to_fp16, b = var_5115_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1427_cast_fp16")]; + tensor x_481_transpose_x_0 = const()[name = tensor("x_481_transpose_x_0"), val = tensor(false)]; + tensor x_481_transpose_y_0 = const()[name = tensor("x_481_transpose_y_0"), val = tensor(false)]; + tensor value_95_cast_fp16 = transpose(perm = value_95_perm_0, x = var_5088_cast_fp16)[name = tensor("transpose_487")]; + tensor x_481_cast_fp16 = matmul(transpose_x = x_481_transpose_x_0, transpose_y = x_481_transpose_y_0, x = input_1427_cast_fp16, y = value_95_cast_fp16)[name = tensor("x_481_cast_fp16")]; + tensor var_5119_perm_0 = const()[name = tensor("op_5119_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_5121 = const()[name = tensor("op_5121"), val = tensor([1, -1, 512])]; + tensor var_5119_cast_fp16 = transpose(perm = var_5119_perm_0, x = x_481_cast_fp16)[name = tensor("transpose_482")]; + tensor input_1429_cast_fp16 = reshape(shape = var_5121, x = var_5119_cast_fp16)[name = tensor("input_1429_cast_fp16")]; + tensor encoder_encoders_46_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_46_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(298650880)))]; + tensor encoder_encoders_46_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_46_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(299175232)))]; + tensor linear_189_cast_fp16 = linear(bias = encoder_encoders_46_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_46_self_attn_linear_out_weight_to_fp16, x = input_1429_cast_fp16)[name = tensor("linear_189_cast_fp16")]; + tensor input_1431_cast_fp16 = add(x = linear_189_cast_fp16, y = fsmn_memory_95_cast_fp16)[name = tensor("input_1431_cast_fp16")]; + tensor input_1433_cast_fp16 = add(x = input_1417_cast_fp16, y = input_1431_cast_fp16)[name = tensor("input_1433_cast_fp16")]; + tensor output_191_axes_0 = const()[name = tensor("output_191_axes_0"), val = tensor([-1])]; + tensor const_292_to_fp16 = const()[name = tensor("const_292_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(299176320)))]; + tensor const_293_to_fp16 = const()[name = tensor("const_293_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(299177408)))]; + tensor output_191_cast_fp16 = layer_norm(axes = output_191_axes_0, beta = const_293_to_fp16, epsilon = var_46_to_fp16, gamma = const_292_to_fp16, x = input_1433_cast_fp16)[name = tensor("output_191_cast_fp16")]; + tensor encoder_encoders_46_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_46_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(299178496)))]; + tensor encoder_encoders_46_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_46_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(301275712)))]; + tensor linear_190_cast_fp16 = linear(bias = encoder_encoders_46_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_46_feed_forward_w_1_weight_to_fp16, x = output_191_cast_fp16)[name = tensor("linear_190_cast_fp16")]; + tensor input_1441_cast_fp16 = relu(x = linear_190_cast_fp16)[name = tensor("input_1441_cast_fp16")]; + tensor encoder_encoders_46_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_46_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(301279872)))]; + tensor encoder_encoders_46_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_46_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303377088)))]; + tensor linear_191_cast_fp16 = linear(bias = encoder_encoders_46_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_46_feed_forward_w_2_weight_to_fp16, x = input_1441_cast_fp16)[name = tensor("linear_191_cast_fp16")]; + tensor input_1447_cast_fp16 = add(x = input_1433_cast_fp16, y = linear_191_cast_fp16)[name = tensor("input_1447_cast_fp16")]; + tensor output_193_axes_0 = const()[name = tensor("output_193_axes_0"), val = tensor([-1])]; + tensor const_294_to_fp16 = const()[name = tensor("const_294_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303378176)))]; + tensor const_295_to_fp16 = const()[name = tensor("const_295_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303379264)))]; + tensor output_193_cast_fp16 = layer_norm(axes = output_193_axes_0, beta = const_295_to_fp16, epsilon = var_46_to_fp16, gamma = const_294_to_fp16, x = input_1447_cast_fp16)[name = tensor("output_193_cast_fp16")]; + tensor encoder_encoders_47_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_47_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303380352)))]; + tensor encoder_encoders_47_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_47_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(304953280)))]; + tensor linear_192_cast_fp16 = linear(bias = encoder_encoders_47_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_47_self_attn_linear_q_k_v_weight_to_fp16, x = output_193_cast_fp16)[name = tensor("linear_192_cast_fp16")]; + tensor tile_48 = const()[name = tensor("tile_48"), val = tensor([512, 512, 512])]; + tensor var_5179_axis_0 = const()[name = tensor("op_5179_axis_0"), val = tensor(-1)]; + tensor var_5179_cast_fp16_0, tensor var_5179_cast_fp16_1, tensor var_5179_cast_fp16_2 = split(axis = var_5179_axis_0, split_sizes = tile_48, x = linear_192_cast_fp16)[name = tensor("op_5179_cast_fp16")]; + tensor concat_144x = const()[name = tensor("concat_144x"), val = tensor([1, -1, 4, 128])]; + tensor var_5184_cast_fp16 = reshape(shape = concat_144x, x = var_5179_cast_fp16_0)[name = tensor("op_5184_cast_fp16")]; + tensor concat_145x = const()[name = tensor("concat_145x"), val = tensor([1, -1, 4, 128])]; + tensor var_5187_cast_fp16 = reshape(shape = concat_145x, x = var_5179_cast_fp16_1)[name = tensor("op_5187_cast_fp16")]; + tensor concat_146x = const()[name = tensor("concat_146x"), val = tensor([1, -1, 4, 128])]; + tensor var_5190_cast_fp16 = reshape(shape = concat_146x, x = var_5179_cast_fp16_2)[name = tensor("op_5190_cast_fp16")]; + tensor value_97_perm_0 = const()[name = tensor("value_97_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_97_cast_fp16 = mul(x = var_5179_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_97_cast_fp16")]; + tensor input_1451_perm_0 = const()[name = tensor("input_1451_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1453_pad_0 = const()[name = tensor("input_1453_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1453_mode_0 = const()[name = tensor("input_1453_mode_0"), val = tensor("constant")]; + tensor const_297_to_fp16 = const()[name = tensor("const_297_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1451_cast_fp16 = transpose(perm = input_1451_perm_0, x = inputs_97_cast_fp16)[name = tensor("transpose_480")]; + tensor input_1453_cast_fp16 = pad(constant_val = const_297_to_fp16, mode = input_1453_mode_0, pad = input_1453_pad_0, x = input_1451_cast_fp16)[name = tensor("input_1453_cast_fp16")]; + tensor x_485_pad_type_0 = const()[name = tensor("x_485_pad_type_0"), val = tensor("valid")]; + tensor x_485_groups_0 = const()[name = tensor("x_485_groups_0"), val = tensor(512)]; + tensor x_485_strides_0 = const()[name = tensor("x_485_strides_0"), val = tensor([1])]; + tensor x_485_pad_0 = const()[name = tensor("x_485_pad_0"), val = tensor([0, 0])]; + tensor x_485_dilations_0 = const()[name = tensor("x_485_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_47_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_47_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(304956416)))]; + tensor x_485_cast_fp16 = conv(dilations = x_485_dilations_0, groups = x_485_groups_0, pad = x_485_pad_0, pad_type = x_485_pad_type_0, strides = x_485_strides_0, weight = encoder_encoders_47_self_attn_fsmn_block_weight_to_fp16, x = input_1453_cast_fp16)[name = tensor("x_485_cast_fp16")]; + tensor x_487_perm_0 = const()[name = tensor("x_487_perm_0"), val = tensor([0, 2, 1])]; + tensor x_487_cast_fp16 = transpose(perm = x_487_perm_0, x = x_485_cast_fp16)[name = tensor("transpose_479")]; + tensor input_1455_cast_fp16 = add(x = x_487_cast_fp16, y = inputs_97_cast_fp16)[name = tensor("input_1455_cast_fp16")]; + tensor fsmn_memory_97_cast_fp16 = mul(x = input_1455_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_97_cast_fp16")]; + tensor var_5209_to_fp16 = const()[name = tensor("op_5209_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_195_cast_fp16 = mul(x = var_5184_cast_fp16, y = var_5209_to_fp16)[name = tensor("q_h_195_cast_fp16")]; + tensor scores_193_transpose_x_0 = const()[name = tensor("scores_193_transpose_x_0"), val = tensor(false)]; + tensor scores_193_transpose_y_0 = const()[name = tensor("scores_193_transpose_y_0"), val = tensor(false)]; + tensor transpose_306_perm_0 = const()[name = tensor("transpose_306_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_307_perm_0 = const()[name = tensor("transpose_307_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_307 = transpose(perm = transpose_307_perm_0, x = var_5187_cast_fp16)[name = tensor("transpose_477")]; + tensor transpose_306 = transpose(perm = transpose_306_perm_0, x = q_h_195_cast_fp16)[name = tensor("transpose_478")]; + tensor scores_193_cast_fp16 = matmul(transpose_x = scores_193_transpose_x_0, transpose_y = scores_193_transpose_y_0, x = transpose_306, y = transpose_307)[name = tensor("scores_193_cast_fp16")]; + tensor scores_195_cast_fp16 = select(a = var_48_to_fp16, b = scores_193_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_195_cast_fp16")]; + tensor var_5217_cast_fp16 = softmax(axis = var_61, x = scores_195_cast_fp16)[name = tensor("op_5217_cast_fp16")]; + tensor input_1457_cast_fp16 = select(a = var_53_to_fp16, b = var_5217_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1457_cast_fp16")]; + tensor x_491_transpose_x_0 = const()[name = tensor("x_491_transpose_x_0"), val = tensor(false)]; + tensor x_491_transpose_y_0 = const()[name = tensor("x_491_transpose_y_0"), val = tensor(false)]; + tensor value_97_cast_fp16 = transpose(perm = value_97_perm_0, x = var_5190_cast_fp16)[name = tensor("transpose_481")]; + tensor x_491_cast_fp16 = matmul(transpose_x = x_491_transpose_x_0, transpose_y = x_491_transpose_y_0, x = input_1457_cast_fp16, y = value_97_cast_fp16)[name = tensor("x_491_cast_fp16")]; + tensor var_5221_perm_0 = const()[name = tensor("op_5221_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_5223 = const()[name = tensor("op_5223"), val = tensor([1, -1, 512])]; + tensor var_5221_cast_fp16 = transpose(perm = var_5221_perm_0, x = x_491_cast_fp16)[name = tensor("transpose_476")]; + tensor input_1459_cast_fp16 = reshape(shape = var_5223, x = var_5221_cast_fp16)[name = tensor("input_1459_cast_fp16")]; + tensor encoder_encoders_47_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_47_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(304967744)))]; + tensor encoder_encoders_47_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_47_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305492096)))]; + tensor linear_193_cast_fp16 = linear(bias = encoder_encoders_47_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_47_self_attn_linear_out_weight_to_fp16, x = input_1459_cast_fp16)[name = tensor("linear_193_cast_fp16")]; + tensor input_1461_cast_fp16 = add(x = linear_193_cast_fp16, y = fsmn_memory_97_cast_fp16)[name = tensor("input_1461_cast_fp16")]; + tensor input_1463_cast_fp16 = add(x = input_1447_cast_fp16, y = input_1461_cast_fp16)[name = tensor("input_1463_cast_fp16")]; + tensor output_195_axes_0 = const()[name = tensor("output_195_axes_0"), val = tensor([-1])]; + tensor const_298_to_fp16 = const()[name = tensor("const_298_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305493184)))]; + tensor const_299_to_fp16 = const()[name = tensor("const_299_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305494272)))]; + tensor output_195_cast_fp16 = layer_norm(axes = output_195_axes_0, beta = const_299_to_fp16, epsilon = var_46_to_fp16, gamma = const_298_to_fp16, x = input_1463_cast_fp16)[name = tensor("output_195_cast_fp16")]; + tensor encoder_encoders_47_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_47_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305495360)))]; + tensor encoder_encoders_47_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_47_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307592576)))]; + tensor linear_194_cast_fp16 = linear(bias = encoder_encoders_47_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_47_feed_forward_w_1_weight_to_fp16, x = output_195_cast_fp16)[name = tensor("linear_194_cast_fp16")]; + tensor input_1471_cast_fp16 = relu(x = linear_194_cast_fp16)[name = tensor("input_1471_cast_fp16")]; + tensor encoder_encoders_47_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_47_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(307596736)))]; + tensor encoder_encoders_47_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_47_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(309693952)))]; + tensor linear_195_cast_fp16 = linear(bias = encoder_encoders_47_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_47_feed_forward_w_2_weight_to_fp16, x = input_1471_cast_fp16)[name = tensor("linear_195_cast_fp16")]; + tensor input_1477_cast_fp16 = add(x = input_1463_cast_fp16, y = linear_195_cast_fp16)[name = tensor("input_1477_cast_fp16")]; + tensor output_197_axes_0 = const()[name = tensor("output_197_axes_0"), val = tensor([-1])]; + tensor const_300_to_fp16 = const()[name = tensor("const_300_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(309695040)))]; + tensor const_301_to_fp16 = const()[name = tensor("const_301_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(309696128)))]; + tensor output_197_cast_fp16 = layer_norm(axes = output_197_axes_0, beta = const_301_to_fp16, epsilon = var_46_to_fp16, gamma = const_300_to_fp16, x = input_1477_cast_fp16)[name = tensor("output_197_cast_fp16")]; + tensor encoder_encoders_48_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_encoders_48_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(309697216)))]; + tensor encoder_encoders_48_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_encoders_48_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311270144)))]; + tensor linear_196_cast_fp16 = linear(bias = encoder_encoders_48_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_encoders_48_self_attn_linear_q_k_v_weight_to_fp16, x = output_197_cast_fp16)[name = tensor("linear_196_cast_fp16")]; + tensor tile_49 = const()[name = tensor("tile_49"), val = tensor([512, 512, 512])]; + tensor var_5281_axis_0 = const()[name = tensor("op_5281_axis_0"), val = tensor(-1)]; + tensor var_5281_cast_fp16_0, tensor var_5281_cast_fp16_1, tensor var_5281_cast_fp16_2 = split(axis = var_5281_axis_0, split_sizes = tile_49, x = linear_196_cast_fp16)[name = tensor("op_5281_cast_fp16")]; + tensor concat_147x = const()[name = tensor("concat_147x"), val = tensor([1, -1, 4, 128])]; + tensor var_5286_cast_fp16 = reshape(shape = concat_147x, x = var_5281_cast_fp16_0)[name = tensor("op_5286_cast_fp16")]; + tensor concat_148x = const()[name = tensor("concat_148x"), val = tensor([1, -1, 4, 128])]; + tensor var_5289_cast_fp16 = reshape(shape = concat_148x, x = var_5281_cast_fp16_1)[name = tensor("op_5289_cast_fp16")]; + tensor concat_149x = const()[name = tensor("concat_149x"), val = tensor([1, -1, 4, 128])]; + tensor var_5292_cast_fp16 = reshape(shape = concat_149x, x = var_5281_cast_fp16_2)[name = tensor("op_5292_cast_fp16")]; + tensor value_99_perm_0 = const()[name = tensor("value_99_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_99_cast_fp16 = mul(x = var_5281_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_99_cast_fp16")]; + tensor input_1481_perm_0 = const()[name = tensor("input_1481_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1483_pad_0 = const()[name = tensor("input_1483_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1483_mode_0 = const()[name = tensor("input_1483_mode_0"), val = tensor("constant")]; + tensor const_303_to_fp16 = const()[name = tensor("const_303_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1481_cast_fp16 = transpose(perm = input_1481_perm_0, x = inputs_99_cast_fp16)[name = tensor("transpose_474")]; + tensor input_1483_cast_fp16 = pad(constant_val = const_303_to_fp16, mode = input_1483_mode_0, pad = input_1483_pad_0, x = input_1481_cast_fp16)[name = tensor("input_1483_cast_fp16")]; + tensor x_495_pad_type_0 = const()[name = tensor("x_495_pad_type_0"), val = tensor("valid")]; + tensor x_495_groups_0 = const()[name = tensor("x_495_groups_0"), val = tensor(512)]; + tensor x_495_strides_0 = const()[name = tensor("x_495_strides_0"), val = tensor([1])]; + tensor x_495_pad_0 = const()[name = tensor("x_495_pad_0"), val = tensor([0, 0])]; + tensor x_495_dilations_0 = const()[name = tensor("x_495_dilations_0"), val = tensor([1])]; + tensor encoder_encoders_48_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_encoders_48_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311273280)))]; + tensor x_495_cast_fp16 = conv(dilations = x_495_dilations_0, groups = x_495_groups_0, pad = x_495_pad_0, pad_type = x_495_pad_type_0, strides = x_495_strides_0, weight = encoder_encoders_48_self_attn_fsmn_block_weight_to_fp16, x = input_1483_cast_fp16)[name = tensor("x_495_cast_fp16")]; + tensor x_497_perm_0 = const()[name = tensor("x_497_perm_0"), val = tensor([0, 2, 1])]; + tensor x_497_cast_fp16 = transpose(perm = x_497_perm_0, x = x_495_cast_fp16)[name = tensor("transpose_473")]; + tensor input_1485_cast_fp16 = add(x = x_497_cast_fp16, y = inputs_99_cast_fp16)[name = tensor("input_1485_cast_fp16")]; + tensor fsmn_memory_99_cast_fp16 = mul(x = input_1485_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_99_cast_fp16")]; + tensor var_5311_to_fp16 = const()[name = tensor("op_5311_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_199_cast_fp16 = mul(x = var_5286_cast_fp16, y = var_5311_to_fp16)[name = tensor("q_h_199_cast_fp16")]; + tensor scores_197_transpose_x_0 = const()[name = tensor("scores_197_transpose_x_0"), val = tensor(false)]; + tensor scores_197_transpose_y_0 = const()[name = tensor("scores_197_transpose_y_0"), val = tensor(false)]; + tensor transpose_308_perm_0 = const()[name = tensor("transpose_308_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_309_perm_0 = const()[name = tensor("transpose_309_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_309 = transpose(perm = transpose_309_perm_0, x = var_5289_cast_fp16)[name = tensor("transpose_471")]; + tensor transpose_308 = transpose(perm = transpose_308_perm_0, x = q_h_199_cast_fp16)[name = tensor("transpose_472")]; + tensor scores_197_cast_fp16 = matmul(transpose_x = scores_197_transpose_x_0, transpose_y = scores_197_transpose_y_0, x = transpose_308, y = transpose_309)[name = tensor("scores_197_cast_fp16")]; + tensor scores_199_cast_fp16 = select(a = var_48_to_fp16, b = scores_197_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_199_cast_fp16")]; + tensor var_5319_cast_fp16 = softmax(axis = var_61, x = scores_199_cast_fp16)[name = tensor("op_5319_cast_fp16")]; + tensor input_1487_cast_fp16 = select(a = var_53_to_fp16, b = var_5319_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1487_cast_fp16")]; + tensor x_501_transpose_x_0 = const()[name = tensor("x_501_transpose_x_0"), val = tensor(false)]; + tensor x_501_transpose_y_0 = const()[name = tensor("x_501_transpose_y_0"), val = tensor(false)]; + tensor value_99_cast_fp16 = transpose(perm = value_99_perm_0, x = var_5292_cast_fp16)[name = tensor("transpose_475")]; + tensor x_501_cast_fp16 = matmul(transpose_x = x_501_transpose_x_0, transpose_y = x_501_transpose_y_0, x = input_1487_cast_fp16, y = value_99_cast_fp16)[name = tensor("x_501_cast_fp16")]; + tensor var_5323_perm_0 = const()[name = tensor("op_5323_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_5325 = const()[name = tensor("op_5325"), val = tensor([1, -1, 512])]; + tensor var_5323_cast_fp16 = transpose(perm = var_5323_perm_0, x = x_501_cast_fp16)[name = tensor("transpose_470")]; + tensor input_1489_cast_fp16 = reshape(shape = var_5325, x = var_5323_cast_fp16)[name = tensor("input_1489_cast_fp16")]; + tensor encoder_encoders_48_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_encoders_48_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311284608)))]; + tensor encoder_encoders_48_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_encoders_48_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311808960)))]; + tensor linear_197_cast_fp16 = linear(bias = encoder_encoders_48_self_attn_linear_out_bias_to_fp16, weight = encoder_encoders_48_self_attn_linear_out_weight_to_fp16, x = input_1489_cast_fp16)[name = tensor("linear_197_cast_fp16")]; + tensor input_1491_cast_fp16 = add(x = linear_197_cast_fp16, y = fsmn_memory_99_cast_fp16)[name = tensor("input_1491_cast_fp16")]; + tensor input_1493_cast_fp16 = add(x = input_1477_cast_fp16, y = input_1491_cast_fp16)[name = tensor("input_1493_cast_fp16")]; + tensor output_199_axes_0 = const()[name = tensor("output_199_axes_0"), val = tensor([-1])]; + tensor const_304_to_fp16 = const()[name = tensor("const_304_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311810048)))]; + tensor const_305_to_fp16 = const()[name = tensor("const_305_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311811136)))]; + tensor output_199_cast_fp16 = layer_norm(axes = output_199_axes_0, beta = const_305_to_fp16, epsilon = var_46_to_fp16, gamma = const_304_to_fp16, x = input_1493_cast_fp16)[name = tensor("output_199_cast_fp16")]; + tensor encoder_encoders_48_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_encoders_48_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311812224)))]; + tensor encoder_encoders_48_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_encoders_48_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(313909440)))]; + tensor linear_198_cast_fp16 = linear(bias = encoder_encoders_48_feed_forward_w_1_bias_to_fp16, weight = encoder_encoders_48_feed_forward_w_1_weight_to_fp16, x = output_199_cast_fp16)[name = tensor("linear_198_cast_fp16")]; + tensor input_1501_cast_fp16 = relu(x = linear_198_cast_fp16)[name = tensor("input_1501_cast_fp16")]; + tensor encoder_encoders_48_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_encoders_48_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(313913600)))]; + tensor encoder_encoders_48_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_encoders_48_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(316010816)))]; + tensor linear_199_cast_fp16 = linear(bias = encoder_encoders_48_feed_forward_w_2_bias_to_fp16, weight = encoder_encoders_48_feed_forward_w_2_weight_to_fp16, x = input_1501_cast_fp16)[name = tensor("linear_199_cast_fp16")]; + tensor input_1507_cast_fp16 = add(x = input_1493_cast_fp16, y = linear_199_cast_fp16)[name = tensor("input_1507_cast_fp16")]; + tensor output_201_axes_0 = const()[name = tensor("output_201_axes_0"), val = tensor([-1])]; + tensor const_306_to_fp16 = const()[name = tensor("const_306_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(316011904)))]; + tensor const_307_to_fp16 = const()[name = tensor("const_307_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(316012992)))]; + tensor output_201_cast_fp16 = layer_norm(axes = output_201_axes_0, beta = const_307_to_fp16, epsilon = var_46_to_fp16, gamma = const_306_to_fp16, x = input_1507_cast_fp16)[name = tensor("output_201_cast_fp16")]; + tensor output_203_axes_0 = const()[name = tensor("output_203_axes_0"), val = tensor([-1])]; + tensor const_308_to_fp16 = const()[name = tensor("const_308_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(316014080)))]; + tensor const_309_to_fp16 = const()[name = tensor("const_309_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(316015168)))]; + tensor output_203_cast_fp16 = layer_norm(axes = output_203_axes_0, beta = const_309_to_fp16, epsilon = var_46_to_fp16, gamma = const_308_to_fp16, x = output_201_cast_fp16)[name = tensor("output_203_cast_fp16")]; + tensor encoder_tp_encoders_0_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_0_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(316016256)))]; + tensor encoder_tp_encoders_0_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_0_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(317589184)))]; + tensor linear_200_cast_fp16 = linear(bias = encoder_tp_encoders_0_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_0_self_attn_linear_q_k_v_weight_to_fp16, x = output_203_cast_fp16)[name = tensor("linear_200_cast_fp16")]; + tensor tile_50 = const()[name = tensor("tile_50"), val = tensor([512, 512, 512])]; + tensor var_5391_axis_0 = const()[name = tensor("op_5391_axis_0"), val = tensor(-1)]; + tensor var_5391_cast_fp16_0, tensor var_5391_cast_fp16_1, tensor var_5391_cast_fp16_2 = split(axis = var_5391_axis_0, split_sizes = tile_50, x = linear_200_cast_fp16)[name = tensor("op_5391_cast_fp16")]; + tensor concat_150x = const()[name = tensor("concat_150x"), val = tensor([1, -1, 4, 128])]; + tensor var_5396_cast_fp16 = reshape(shape = concat_150x, x = var_5391_cast_fp16_0)[name = tensor("op_5396_cast_fp16")]; + tensor concat_151x = const()[name = tensor("concat_151x"), val = tensor([1, -1, 4, 128])]; + tensor var_5399_cast_fp16 = reshape(shape = concat_151x, x = var_5391_cast_fp16_1)[name = tensor("op_5399_cast_fp16")]; + tensor concat_152x = const()[name = tensor("concat_152x"), val = tensor([1, -1, 4, 128])]; + tensor var_5402_cast_fp16 = reshape(shape = concat_152x, x = var_5391_cast_fp16_2)[name = tensor("op_5402_cast_fp16")]; + tensor value_101_perm_0 = const()[name = tensor("value_101_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_101_cast_fp16 = mul(x = var_5391_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_101_cast_fp16")]; + tensor input_1515_perm_0 = const()[name = tensor("input_1515_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1517_pad_0 = const()[name = tensor("input_1517_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1517_mode_0 = const()[name = tensor("input_1517_mode_0"), val = tensor("constant")]; + tensor const_311_to_fp16 = const()[name = tensor("const_311_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1515_cast_fp16 = transpose(perm = input_1515_perm_0, x = inputs_101_cast_fp16)[name = tensor("transpose_468")]; + tensor input_1517_cast_fp16 = pad(constant_val = const_311_to_fp16, mode = input_1517_mode_0, pad = input_1517_pad_0, x = input_1515_cast_fp16)[name = tensor("input_1517_cast_fp16")]; + tensor x_505_pad_type_0 = const()[name = tensor("x_505_pad_type_0"), val = tensor("valid")]; + tensor x_505_groups_0 = const()[name = tensor("x_505_groups_0"), val = tensor(512)]; + tensor x_505_strides_0 = const()[name = tensor("x_505_strides_0"), val = tensor([1])]; + tensor x_505_pad_0 = const()[name = tensor("x_505_pad_0"), val = tensor([0, 0])]; + tensor x_505_dilations_0 = const()[name = tensor("x_505_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_0_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_0_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(317592320)))]; + tensor x_505_cast_fp16 = conv(dilations = x_505_dilations_0, groups = x_505_groups_0, pad = x_505_pad_0, pad_type = x_505_pad_type_0, strides = x_505_strides_0, weight = encoder_tp_encoders_0_self_attn_fsmn_block_weight_to_fp16, x = input_1517_cast_fp16)[name = tensor("x_505_cast_fp16")]; + tensor x_507_perm_0 = const()[name = tensor("x_507_perm_0"), val = tensor([0, 2, 1])]; + tensor x_507_cast_fp16 = transpose(perm = x_507_perm_0, x = x_505_cast_fp16)[name = tensor("transpose_467")]; + tensor input_1519_cast_fp16 = add(x = x_507_cast_fp16, y = inputs_101_cast_fp16)[name = tensor("input_1519_cast_fp16")]; + tensor fsmn_memory_101_cast_fp16 = mul(x = input_1519_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_101_cast_fp16")]; + tensor var_5421_to_fp16 = const()[name = tensor("op_5421_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_203_cast_fp16 = mul(x = var_5396_cast_fp16, y = var_5421_to_fp16)[name = tensor("q_h_203_cast_fp16")]; + tensor scores_201_transpose_x_0 = const()[name = tensor("scores_201_transpose_x_0"), val = tensor(false)]; + tensor scores_201_transpose_y_0 = const()[name = tensor("scores_201_transpose_y_0"), val = tensor(false)]; + tensor transpose_310_perm_0 = const()[name = tensor("transpose_310_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_311_perm_0 = const()[name = tensor("transpose_311_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_311 = transpose(perm = transpose_311_perm_0, x = var_5399_cast_fp16)[name = tensor("transpose_465")]; + tensor transpose_310 = transpose(perm = transpose_310_perm_0, x = q_h_203_cast_fp16)[name = tensor("transpose_466")]; + tensor scores_201_cast_fp16 = matmul(transpose_x = scores_201_transpose_x_0, transpose_y = scores_201_transpose_y_0, x = transpose_310, y = transpose_311)[name = tensor("scores_201_cast_fp16")]; + tensor scores_203_cast_fp16 = select(a = var_48_to_fp16, b = scores_201_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_203_cast_fp16")]; + tensor var_5429_cast_fp16 = softmax(axis = var_61, x = scores_203_cast_fp16)[name = tensor("op_5429_cast_fp16")]; + tensor input_1521_cast_fp16 = select(a = var_53_to_fp16, b = var_5429_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1521_cast_fp16")]; + tensor x_511_transpose_x_0 = const()[name = tensor("x_511_transpose_x_0"), val = tensor(false)]; + tensor x_511_transpose_y_0 = const()[name = tensor("x_511_transpose_y_0"), val = tensor(false)]; + tensor value_101_cast_fp16 = transpose(perm = value_101_perm_0, x = var_5402_cast_fp16)[name = tensor("transpose_469")]; + tensor x_511_cast_fp16 = matmul(transpose_x = x_511_transpose_x_0, transpose_y = x_511_transpose_y_0, x = input_1521_cast_fp16, y = value_101_cast_fp16)[name = tensor("x_511_cast_fp16")]; + tensor var_5433_perm_0 = const()[name = tensor("op_5433_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_5435 = const()[name = tensor("op_5435"), val = tensor([1, -1, 512])]; + tensor var_5433_cast_fp16 = transpose(perm = var_5433_perm_0, x = x_511_cast_fp16)[name = tensor("transpose_464")]; + tensor input_1523_cast_fp16 = reshape(shape = var_5435, x = var_5433_cast_fp16)[name = tensor("input_1523_cast_fp16")]; + tensor encoder_tp_encoders_0_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_0_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(317603648)))]; + tensor encoder_tp_encoders_0_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_0_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318128000)))]; + tensor linear_201_cast_fp16 = linear(bias = encoder_tp_encoders_0_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_0_self_attn_linear_out_weight_to_fp16, x = input_1523_cast_fp16)[name = tensor("linear_201_cast_fp16")]; + tensor input_1525_cast_fp16 = add(x = linear_201_cast_fp16, y = fsmn_memory_101_cast_fp16)[name = tensor("input_1525_cast_fp16")]; + tensor input_1527_cast_fp16 = add(x = output_201_cast_fp16, y = input_1525_cast_fp16)[name = tensor("input_1527_cast_fp16")]; + tensor output_205_axes_0 = const()[name = tensor("output_205_axes_0"), val = tensor([-1])]; + tensor const_312_to_fp16 = const()[name = tensor("const_312_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318129088)))]; + tensor const_313_to_fp16 = const()[name = tensor("const_313_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318130176)))]; + tensor output_205_cast_fp16 = layer_norm(axes = output_205_axes_0, beta = const_313_to_fp16, epsilon = var_46_to_fp16, gamma = const_312_to_fp16, x = input_1527_cast_fp16)[name = tensor("output_205_cast_fp16")]; + tensor encoder_tp_encoders_0_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_0_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318131264)))]; + tensor encoder_tp_encoders_0_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_0_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(320228480)))]; + tensor linear_202_cast_fp16 = linear(bias = encoder_tp_encoders_0_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_0_feed_forward_w_1_weight_to_fp16, x = output_205_cast_fp16)[name = tensor("linear_202_cast_fp16")]; + tensor input_1535_cast_fp16 = relu(x = linear_202_cast_fp16)[name = tensor("input_1535_cast_fp16")]; + tensor encoder_tp_encoders_0_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_0_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(320232640)))]; + tensor encoder_tp_encoders_0_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_0_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(322329856)))]; + tensor linear_203_cast_fp16 = linear(bias = encoder_tp_encoders_0_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_0_feed_forward_w_2_weight_to_fp16, x = input_1535_cast_fp16)[name = tensor("linear_203_cast_fp16")]; + tensor input_1541_cast_fp16 = add(x = input_1527_cast_fp16, y = linear_203_cast_fp16)[name = tensor("input_1541_cast_fp16")]; + tensor output_207_axes_0 = const()[name = tensor("output_207_axes_0"), val = tensor([-1])]; + tensor const_314_to_fp16 = const()[name = tensor("const_314_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(322330944)))]; + tensor const_315_to_fp16 = const()[name = tensor("const_315_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(322332032)))]; + tensor output_207_cast_fp16 = layer_norm(axes = output_207_axes_0, beta = const_315_to_fp16, epsilon = var_46_to_fp16, gamma = const_314_to_fp16, x = input_1541_cast_fp16)[name = tensor("output_207_cast_fp16")]; + tensor encoder_tp_encoders_1_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_1_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(322333120)))]; + tensor encoder_tp_encoders_1_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_1_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(323906048)))]; + tensor linear_204_cast_fp16 = linear(bias = encoder_tp_encoders_1_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_1_self_attn_linear_q_k_v_weight_to_fp16, x = output_207_cast_fp16)[name = tensor("linear_204_cast_fp16")]; + tensor tile_51 = const()[name = tensor("tile_51"), val = tensor([512, 512, 512])]; + tensor var_5493_axis_0 = const()[name = tensor("op_5493_axis_0"), val = tensor(-1)]; + tensor var_5493_cast_fp16_0, tensor var_5493_cast_fp16_1, tensor var_5493_cast_fp16_2 = split(axis = var_5493_axis_0, split_sizes = tile_51, x = linear_204_cast_fp16)[name = tensor("op_5493_cast_fp16")]; + tensor concat_153x = const()[name = tensor("concat_153x"), val = tensor([1, -1, 4, 128])]; + tensor var_5498_cast_fp16 = reshape(shape = concat_153x, x = var_5493_cast_fp16_0)[name = tensor("op_5498_cast_fp16")]; + tensor concat_154x = const()[name = tensor("concat_154x"), val = tensor([1, -1, 4, 128])]; + tensor var_5501_cast_fp16 = reshape(shape = concat_154x, x = var_5493_cast_fp16_1)[name = tensor("op_5501_cast_fp16")]; + tensor concat_155x = const()[name = tensor("concat_155x"), val = tensor([1, -1, 4, 128])]; + tensor var_5504_cast_fp16 = reshape(shape = concat_155x, x = var_5493_cast_fp16_2)[name = tensor("op_5504_cast_fp16")]; + tensor value_103_perm_0 = const()[name = tensor("value_103_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_103_cast_fp16 = mul(x = var_5493_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_103_cast_fp16")]; + tensor input_1545_perm_0 = const()[name = tensor("input_1545_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1547_pad_0 = const()[name = tensor("input_1547_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1547_mode_0 = const()[name = tensor("input_1547_mode_0"), val = tensor("constant")]; + tensor const_317_to_fp16 = const()[name = tensor("const_317_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1545_cast_fp16 = transpose(perm = input_1545_perm_0, x = inputs_103_cast_fp16)[name = tensor("transpose_462")]; + tensor input_1547_cast_fp16 = pad(constant_val = const_317_to_fp16, mode = input_1547_mode_0, pad = input_1547_pad_0, x = input_1545_cast_fp16)[name = tensor("input_1547_cast_fp16")]; + tensor x_515_pad_type_0 = const()[name = tensor("x_515_pad_type_0"), val = tensor("valid")]; + tensor x_515_groups_0 = const()[name = tensor("x_515_groups_0"), val = tensor(512)]; + tensor x_515_strides_0 = const()[name = tensor("x_515_strides_0"), val = tensor([1])]; + tensor x_515_pad_0 = const()[name = tensor("x_515_pad_0"), val = tensor([0, 0])]; + tensor x_515_dilations_0 = const()[name = tensor("x_515_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_1_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_1_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(323909184)))]; + tensor x_515_cast_fp16 = conv(dilations = x_515_dilations_0, groups = x_515_groups_0, pad = x_515_pad_0, pad_type = x_515_pad_type_0, strides = x_515_strides_0, weight = encoder_tp_encoders_1_self_attn_fsmn_block_weight_to_fp16, x = input_1547_cast_fp16)[name = tensor("x_515_cast_fp16")]; + tensor x_517_perm_0 = const()[name = tensor("x_517_perm_0"), val = tensor([0, 2, 1])]; + tensor x_517_cast_fp16 = transpose(perm = x_517_perm_0, x = x_515_cast_fp16)[name = tensor("transpose_461")]; + tensor input_1549_cast_fp16 = add(x = x_517_cast_fp16, y = inputs_103_cast_fp16)[name = tensor("input_1549_cast_fp16")]; + tensor fsmn_memory_103_cast_fp16 = mul(x = input_1549_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_103_cast_fp16")]; + tensor var_5523_to_fp16 = const()[name = tensor("op_5523_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_207_cast_fp16 = mul(x = var_5498_cast_fp16, y = var_5523_to_fp16)[name = tensor("q_h_207_cast_fp16")]; + tensor scores_205_transpose_x_0 = const()[name = tensor("scores_205_transpose_x_0"), val = tensor(false)]; + tensor scores_205_transpose_y_0 = const()[name = tensor("scores_205_transpose_y_0"), val = tensor(false)]; + tensor transpose_312_perm_0 = const()[name = tensor("transpose_312_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_313_perm_0 = const()[name = tensor("transpose_313_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_313 = transpose(perm = transpose_313_perm_0, x = var_5501_cast_fp16)[name = tensor("transpose_459")]; + tensor transpose_312 = transpose(perm = transpose_312_perm_0, x = q_h_207_cast_fp16)[name = tensor("transpose_460")]; + tensor scores_205_cast_fp16 = matmul(transpose_x = scores_205_transpose_x_0, transpose_y = scores_205_transpose_y_0, x = transpose_312, y = transpose_313)[name = tensor("scores_205_cast_fp16")]; + tensor scores_207_cast_fp16 = select(a = var_48_to_fp16, b = scores_205_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_207_cast_fp16")]; + tensor var_5531_cast_fp16 = softmax(axis = var_61, x = scores_207_cast_fp16)[name = tensor("op_5531_cast_fp16")]; + tensor input_1551_cast_fp16 = select(a = var_53_to_fp16, b = var_5531_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1551_cast_fp16")]; + tensor x_521_transpose_x_0 = const()[name = tensor("x_521_transpose_x_0"), val = tensor(false)]; + tensor x_521_transpose_y_0 = const()[name = tensor("x_521_transpose_y_0"), val = tensor(false)]; + tensor value_103_cast_fp16 = transpose(perm = value_103_perm_0, x = var_5504_cast_fp16)[name = tensor("transpose_463")]; + tensor x_521_cast_fp16 = matmul(transpose_x = x_521_transpose_x_0, transpose_y = x_521_transpose_y_0, x = input_1551_cast_fp16, y = value_103_cast_fp16)[name = tensor("x_521_cast_fp16")]; + tensor var_5535_perm_0 = const()[name = tensor("op_5535_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_5537 = const()[name = tensor("op_5537"), val = tensor([1, -1, 512])]; + tensor var_5535_cast_fp16 = transpose(perm = var_5535_perm_0, x = x_521_cast_fp16)[name = tensor("transpose_458")]; + tensor input_1553_cast_fp16 = reshape(shape = var_5537, x = var_5535_cast_fp16)[name = tensor("input_1553_cast_fp16")]; + tensor encoder_tp_encoders_1_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_1_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(323920512)))]; + tensor encoder_tp_encoders_1_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_1_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(324444864)))]; + tensor linear_205_cast_fp16 = linear(bias = encoder_tp_encoders_1_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_1_self_attn_linear_out_weight_to_fp16, x = input_1553_cast_fp16)[name = tensor("linear_205_cast_fp16")]; + tensor input_1555_cast_fp16 = add(x = linear_205_cast_fp16, y = fsmn_memory_103_cast_fp16)[name = tensor("input_1555_cast_fp16")]; + tensor input_1557_cast_fp16 = add(x = input_1541_cast_fp16, y = input_1555_cast_fp16)[name = tensor("input_1557_cast_fp16")]; + tensor output_209_axes_0 = const()[name = tensor("output_209_axes_0"), val = tensor([-1])]; + tensor const_318_to_fp16 = const()[name = tensor("const_318_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(324445952)))]; + tensor const_319_to_fp16 = const()[name = tensor("const_319_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(324447040)))]; + tensor output_209_cast_fp16 = layer_norm(axes = output_209_axes_0, beta = const_319_to_fp16, epsilon = var_46_to_fp16, gamma = const_318_to_fp16, x = input_1557_cast_fp16)[name = tensor("output_209_cast_fp16")]; + tensor encoder_tp_encoders_1_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_1_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(324448128)))]; + tensor encoder_tp_encoders_1_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_1_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(326545344)))]; + tensor linear_206_cast_fp16 = linear(bias = encoder_tp_encoders_1_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_1_feed_forward_w_1_weight_to_fp16, x = output_209_cast_fp16)[name = tensor("linear_206_cast_fp16")]; + tensor input_1565_cast_fp16 = relu(x = linear_206_cast_fp16)[name = tensor("input_1565_cast_fp16")]; + tensor encoder_tp_encoders_1_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_1_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(326549504)))]; + tensor encoder_tp_encoders_1_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_1_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(328646720)))]; + tensor linear_207_cast_fp16 = linear(bias = encoder_tp_encoders_1_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_1_feed_forward_w_2_weight_to_fp16, x = input_1565_cast_fp16)[name = tensor("linear_207_cast_fp16")]; + tensor input_1571_cast_fp16 = add(x = input_1557_cast_fp16, y = linear_207_cast_fp16)[name = tensor("input_1571_cast_fp16")]; + tensor output_211_axes_0 = const()[name = tensor("output_211_axes_0"), val = tensor([-1])]; + tensor const_320_to_fp16 = const()[name = tensor("const_320_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(328647808)))]; + tensor const_321_to_fp16 = const()[name = tensor("const_321_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(328648896)))]; + tensor output_211_cast_fp16 = layer_norm(axes = output_211_axes_0, beta = const_321_to_fp16, epsilon = var_46_to_fp16, gamma = const_320_to_fp16, x = input_1571_cast_fp16)[name = tensor("output_211_cast_fp16")]; + tensor encoder_tp_encoders_2_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_2_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(328649984)))]; + tensor encoder_tp_encoders_2_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_2_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(330222912)))]; + tensor linear_208_cast_fp16 = linear(bias = encoder_tp_encoders_2_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_2_self_attn_linear_q_k_v_weight_to_fp16, x = output_211_cast_fp16)[name = tensor("linear_208_cast_fp16")]; + tensor tile_52 = const()[name = tensor("tile_52"), val = tensor([512, 512, 512])]; + tensor var_5595_axis_0 = const()[name = tensor("op_5595_axis_0"), val = tensor(-1)]; + tensor var_5595_cast_fp16_0, tensor var_5595_cast_fp16_1, tensor var_5595_cast_fp16_2 = split(axis = var_5595_axis_0, split_sizes = tile_52, x = linear_208_cast_fp16)[name = tensor("op_5595_cast_fp16")]; + tensor concat_156x = const()[name = tensor("concat_156x"), val = tensor([1, -1, 4, 128])]; + tensor var_5600_cast_fp16 = reshape(shape = concat_156x, x = var_5595_cast_fp16_0)[name = tensor("op_5600_cast_fp16")]; + tensor concat_157x = const()[name = tensor("concat_157x"), val = tensor([1, -1, 4, 128])]; + tensor var_5603_cast_fp16 = reshape(shape = concat_157x, x = var_5595_cast_fp16_1)[name = tensor("op_5603_cast_fp16")]; + tensor concat_158x = const()[name = tensor("concat_158x"), val = tensor([1, -1, 4, 128])]; + tensor var_5606_cast_fp16 = reshape(shape = concat_158x, x = var_5595_cast_fp16_2)[name = tensor("op_5606_cast_fp16")]; + tensor value_105_perm_0 = const()[name = tensor("value_105_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_105_cast_fp16 = mul(x = var_5595_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_105_cast_fp16")]; + tensor input_1575_perm_0 = const()[name = tensor("input_1575_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1577_pad_0 = const()[name = tensor("input_1577_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1577_mode_0 = const()[name = tensor("input_1577_mode_0"), val = tensor("constant")]; + tensor const_323_to_fp16 = const()[name = tensor("const_323_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1575_cast_fp16 = transpose(perm = input_1575_perm_0, x = inputs_105_cast_fp16)[name = tensor("transpose_456")]; + tensor input_1577_cast_fp16 = pad(constant_val = const_323_to_fp16, mode = input_1577_mode_0, pad = input_1577_pad_0, x = input_1575_cast_fp16)[name = tensor("input_1577_cast_fp16")]; + tensor x_525_pad_type_0 = const()[name = tensor("x_525_pad_type_0"), val = tensor("valid")]; + tensor x_525_groups_0 = const()[name = tensor("x_525_groups_0"), val = tensor(512)]; + tensor x_525_strides_0 = const()[name = tensor("x_525_strides_0"), val = tensor([1])]; + tensor x_525_pad_0 = const()[name = tensor("x_525_pad_0"), val = tensor([0, 0])]; + tensor x_525_dilations_0 = const()[name = tensor("x_525_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_2_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_2_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(330226048)))]; + tensor x_525_cast_fp16 = conv(dilations = x_525_dilations_0, groups = x_525_groups_0, pad = x_525_pad_0, pad_type = x_525_pad_type_0, strides = x_525_strides_0, weight = encoder_tp_encoders_2_self_attn_fsmn_block_weight_to_fp16, x = input_1577_cast_fp16)[name = tensor("x_525_cast_fp16")]; + tensor x_527_perm_0 = const()[name = tensor("x_527_perm_0"), val = tensor([0, 2, 1])]; + tensor x_527_cast_fp16 = transpose(perm = x_527_perm_0, x = x_525_cast_fp16)[name = tensor("transpose_455")]; + tensor input_1579_cast_fp16 = add(x = x_527_cast_fp16, y = inputs_105_cast_fp16)[name = tensor("input_1579_cast_fp16")]; + tensor fsmn_memory_105_cast_fp16 = mul(x = input_1579_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_105_cast_fp16")]; + tensor var_5625_to_fp16 = const()[name = tensor("op_5625_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_211_cast_fp16 = mul(x = var_5600_cast_fp16, y = var_5625_to_fp16)[name = tensor("q_h_211_cast_fp16")]; + tensor scores_209_transpose_x_0 = const()[name = tensor("scores_209_transpose_x_0"), val = tensor(false)]; + tensor scores_209_transpose_y_0 = const()[name = tensor("scores_209_transpose_y_0"), val = tensor(false)]; + tensor transpose_314_perm_0 = const()[name = tensor("transpose_314_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_315_perm_0 = const()[name = tensor("transpose_315_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_315 = transpose(perm = transpose_315_perm_0, x = var_5603_cast_fp16)[name = tensor("transpose_453")]; + tensor transpose_314 = transpose(perm = transpose_314_perm_0, x = q_h_211_cast_fp16)[name = tensor("transpose_454")]; + tensor scores_209_cast_fp16 = matmul(transpose_x = scores_209_transpose_x_0, transpose_y = scores_209_transpose_y_0, x = transpose_314, y = transpose_315)[name = tensor("scores_209_cast_fp16")]; + tensor scores_211_cast_fp16 = select(a = var_48_to_fp16, b = scores_209_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_211_cast_fp16")]; + tensor var_5633_cast_fp16 = softmax(axis = var_61, x = scores_211_cast_fp16)[name = tensor("op_5633_cast_fp16")]; + tensor input_1581_cast_fp16 = select(a = var_53_to_fp16, b = var_5633_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1581_cast_fp16")]; + tensor x_531_transpose_x_0 = const()[name = tensor("x_531_transpose_x_0"), val = tensor(false)]; + tensor x_531_transpose_y_0 = const()[name = tensor("x_531_transpose_y_0"), val = tensor(false)]; + tensor value_105_cast_fp16 = transpose(perm = value_105_perm_0, x = var_5606_cast_fp16)[name = tensor("transpose_457")]; + tensor x_531_cast_fp16 = matmul(transpose_x = x_531_transpose_x_0, transpose_y = x_531_transpose_y_0, x = input_1581_cast_fp16, y = value_105_cast_fp16)[name = tensor("x_531_cast_fp16")]; + tensor var_5637_perm_0 = const()[name = tensor("op_5637_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_5639 = const()[name = tensor("op_5639"), val = tensor([1, -1, 512])]; + tensor var_5637_cast_fp16 = transpose(perm = var_5637_perm_0, x = x_531_cast_fp16)[name = tensor("transpose_452")]; + tensor input_1583_cast_fp16 = reshape(shape = var_5639, x = var_5637_cast_fp16)[name = tensor("input_1583_cast_fp16")]; + tensor encoder_tp_encoders_2_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_2_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(330237376)))]; + tensor encoder_tp_encoders_2_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_2_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(330761728)))]; + tensor linear_209_cast_fp16 = linear(bias = encoder_tp_encoders_2_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_2_self_attn_linear_out_weight_to_fp16, x = input_1583_cast_fp16)[name = tensor("linear_209_cast_fp16")]; + tensor input_1585_cast_fp16 = add(x = linear_209_cast_fp16, y = fsmn_memory_105_cast_fp16)[name = tensor("input_1585_cast_fp16")]; + tensor input_1587_cast_fp16 = add(x = input_1571_cast_fp16, y = input_1585_cast_fp16)[name = tensor("input_1587_cast_fp16")]; + tensor output_213_axes_0 = const()[name = tensor("output_213_axes_0"), val = tensor([-1])]; + tensor const_324_to_fp16 = const()[name = tensor("const_324_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(330762816)))]; + tensor const_325_to_fp16 = const()[name = tensor("const_325_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(330763904)))]; + tensor output_213_cast_fp16 = layer_norm(axes = output_213_axes_0, beta = const_325_to_fp16, epsilon = var_46_to_fp16, gamma = const_324_to_fp16, x = input_1587_cast_fp16)[name = tensor("output_213_cast_fp16")]; + tensor encoder_tp_encoders_2_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_2_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(330764992)))]; + tensor encoder_tp_encoders_2_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_2_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(332862208)))]; + tensor linear_210_cast_fp16 = linear(bias = encoder_tp_encoders_2_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_2_feed_forward_w_1_weight_to_fp16, x = output_213_cast_fp16)[name = tensor("linear_210_cast_fp16")]; + tensor input_1595_cast_fp16 = relu(x = linear_210_cast_fp16)[name = tensor("input_1595_cast_fp16")]; + tensor encoder_tp_encoders_2_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_2_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(332866368)))]; + tensor encoder_tp_encoders_2_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_2_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(334963584)))]; + tensor linear_211_cast_fp16 = linear(bias = encoder_tp_encoders_2_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_2_feed_forward_w_2_weight_to_fp16, x = input_1595_cast_fp16)[name = tensor("linear_211_cast_fp16")]; + tensor input_1601_cast_fp16 = add(x = input_1587_cast_fp16, y = linear_211_cast_fp16)[name = tensor("input_1601_cast_fp16")]; + tensor output_215_axes_0 = const()[name = tensor("output_215_axes_0"), val = tensor([-1])]; + tensor const_326_to_fp16 = const()[name = tensor("const_326_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(334964672)))]; + tensor const_327_to_fp16 = const()[name = tensor("const_327_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(334965760)))]; + tensor output_215_cast_fp16 = layer_norm(axes = output_215_axes_0, beta = const_327_to_fp16, epsilon = var_46_to_fp16, gamma = const_326_to_fp16, x = input_1601_cast_fp16)[name = tensor("output_215_cast_fp16")]; + tensor encoder_tp_encoders_3_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_3_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(334966848)))]; + tensor encoder_tp_encoders_3_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_3_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(336539776)))]; + tensor linear_212_cast_fp16 = linear(bias = encoder_tp_encoders_3_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_3_self_attn_linear_q_k_v_weight_to_fp16, x = output_215_cast_fp16)[name = tensor("linear_212_cast_fp16")]; + tensor tile_53 = const()[name = tensor("tile_53"), val = tensor([512, 512, 512])]; + tensor var_5697_axis_0 = const()[name = tensor("op_5697_axis_0"), val = tensor(-1)]; + tensor var_5697_cast_fp16_0, tensor var_5697_cast_fp16_1, tensor var_5697_cast_fp16_2 = split(axis = var_5697_axis_0, split_sizes = tile_53, x = linear_212_cast_fp16)[name = tensor("op_5697_cast_fp16")]; + tensor concat_159x = const()[name = tensor("concat_159x"), val = tensor([1, -1, 4, 128])]; + tensor var_5702_cast_fp16 = reshape(shape = concat_159x, x = var_5697_cast_fp16_0)[name = tensor("op_5702_cast_fp16")]; + tensor concat_160x = const()[name = tensor("concat_160x"), val = tensor([1, -1, 4, 128])]; + tensor var_5705_cast_fp16 = reshape(shape = concat_160x, x = var_5697_cast_fp16_1)[name = tensor("op_5705_cast_fp16")]; + tensor concat_161x = const()[name = tensor("concat_161x"), val = tensor([1, -1, 4, 128])]; + tensor var_5708_cast_fp16 = reshape(shape = concat_161x, x = var_5697_cast_fp16_2)[name = tensor("op_5708_cast_fp16")]; + tensor value_107_perm_0 = const()[name = tensor("value_107_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_107_cast_fp16 = mul(x = var_5697_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_107_cast_fp16")]; + tensor input_1605_perm_0 = const()[name = tensor("input_1605_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1607_pad_0 = const()[name = tensor("input_1607_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1607_mode_0 = const()[name = tensor("input_1607_mode_0"), val = tensor("constant")]; + tensor const_329_to_fp16 = const()[name = tensor("const_329_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1605_cast_fp16 = transpose(perm = input_1605_perm_0, x = inputs_107_cast_fp16)[name = tensor("transpose_450")]; + tensor input_1607_cast_fp16 = pad(constant_val = const_329_to_fp16, mode = input_1607_mode_0, pad = input_1607_pad_0, x = input_1605_cast_fp16)[name = tensor("input_1607_cast_fp16")]; + tensor x_535_pad_type_0 = const()[name = tensor("x_535_pad_type_0"), val = tensor("valid")]; + tensor x_535_groups_0 = const()[name = tensor("x_535_groups_0"), val = tensor(512)]; + tensor x_535_strides_0 = const()[name = tensor("x_535_strides_0"), val = tensor([1])]; + tensor x_535_pad_0 = const()[name = tensor("x_535_pad_0"), val = tensor([0, 0])]; + tensor x_535_dilations_0 = const()[name = tensor("x_535_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_3_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_3_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(336542912)))]; + tensor x_535_cast_fp16 = conv(dilations = x_535_dilations_0, groups = x_535_groups_0, pad = x_535_pad_0, pad_type = x_535_pad_type_0, strides = x_535_strides_0, weight = encoder_tp_encoders_3_self_attn_fsmn_block_weight_to_fp16, x = input_1607_cast_fp16)[name = tensor("x_535_cast_fp16")]; + tensor x_537_perm_0 = const()[name = tensor("x_537_perm_0"), val = tensor([0, 2, 1])]; + tensor x_537_cast_fp16 = transpose(perm = x_537_perm_0, x = x_535_cast_fp16)[name = tensor("transpose_449")]; + tensor input_1609_cast_fp16 = add(x = x_537_cast_fp16, y = inputs_107_cast_fp16)[name = tensor("input_1609_cast_fp16")]; + tensor fsmn_memory_107_cast_fp16 = mul(x = input_1609_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_107_cast_fp16")]; + tensor var_5727_to_fp16 = const()[name = tensor("op_5727_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_215_cast_fp16 = mul(x = var_5702_cast_fp16, y = var_5727_to_fp16)[name = tensor("q_h_215_cast_fp16")]; + tensor scores_213_transpose_x_0 = const()[name = tensor("scores_213_transpose_x_0"), val = tensor(false)]; + tensor scores_213_transpose_y_0 = const()[name = tensor("scores_213_transpose_y_0"), val = tensor(false)]; + tensor transpose_316_perm_0 = const()[name = tensor("transpose_316_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_317_perm_0 = const()[name = tensor("transpose_317_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_317 = transpose(perm = transpose_317_perm_0, x = var_5705_cast_fp16)[name = tensor("transpose_447")]; + tensor transpose_316 = transpose(perm = transpose_316_perm_0, x = q_h_215_cast_fp16)[name = tensor("transpose_448")]; + tensor scores_213_cast_fp16 = matmul(transpose_x = scores_213_transpose_x_0, transpose_y = scores_213_transpose_y_0, x = transpose_316, y = transpose_317)[name = tensor("scores_213_cast_fp16")]; + tensor scores_215_cast_fp16 = select(a = var_48_to_fp16, b = scores_213_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_215_cast_fp16")]; + tensor var_5735_cast_fp16 = softmax(axis = var_61, x = scores_215_cast_fp16)[name = tensor("op_5735_cast_fp16")]; + tensor input_1611_cast_fp16 = select(a = var_53_to_fp16, b = var_5735_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1611_cast_fp16")]; + tensor x_541_transpose_x_0 = const()[name = tensor("x_541_transpose_x_0"), val = tensor(false)]; + tensor x_541_transpose_y_0 = const()[name = tensor("x_541_transpose_y_0"), val = tensor(false)]; + tensor value_107_cast_fp16 = transpose(perm = value_107_perm_0, x = var_5708_cast_fp16)[name = tensor("transpose_451")]; + tensor x_541_cast_fp16 = matmul(transpose_x = x_541_transpose_x_0, transpose_y = x_541_transpose_y_0, x = input_1611_cast_fp16, y = value_107_cast_fp16)[name = tensor("x_541_cast_fp16")]; + tensor var_5739_perm_0 = const()[name = tensor("op_5739_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_5741 = const()[name = tensor("op_5741"), val = tensor([1, -1, 512])]; + tensor var_5739_cast_fp16 = transpose(perm = var_5739_perm_0, x = x_541_cast_fp16)[name = tensor("transpose_446")]; + tensor input_1613_cast_fp16 = reshape(shape = var_5741, x = var_5739_cast_fp16)[name = tensor("input_1613_cast_fp16")]; + tensor encoder_tp_encoders_3_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_3_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(336554240)))]; + tensor encoder_tp_encoders_3_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_3_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(337078592)))]; + tensor linear_213_cast_fp16 = linear(bias = encoder_tp_encoders_3_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_3_self_attn_linear_out_weight_to_fp16, x = input_1613_cast_fp16)[name = tensor("linear_213_cast_fp16")]; + tensor input_1615_cast_fp16 = add(x = linear_213_cast_fp16, y = fsmn_memory_107_cast_fp16)[name = tensor("input_1615_cast_fp16")]; + tensor input_1617_cast_fp16 = add(x = input_1601_cast_fp16, y = input_1615_cast_fp16)[name = tensor("input_1617_cast_fp16")]; + tensor output_217_axes_0 = const()[name = tensor("output_217_axes_0"), val = tensor([-1])]; + tensor const_330_to_fp16 = const()[name = tensor("const_330_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(337079680)))]; + tensor const_331_to_fp16 = const()[name = tensor("const_331_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(337080768)))]; + tensor output_217_cast_fp16 = layer_norm(axes = output_217_axes_0, beta = const_331_to_fp16, epsilon = var_46_to_fp16, gamma = const_330_to_fp16, x = input_1617_cast_fp16)[name = tensor("output_217_cast_fp16")]; + tensor encoder_tp_encoders_3_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_3_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(337081856)))]; + tensor encoder_tp_encoders_3_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_3_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(339179072)))]; + tensor linear_214_cast_fp16 = linear(bias = encoder_tp_encoders_3_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_3_feed_forward_w_1_weight_to_fp16, x = output_217_cast_fp16)[name = tensor("linear_214_cast_fp16")]; + tensor input_1625_cast_fp16 = relu(x = linear_214_cast_fp16)[name = tensor("input_1625_cast_fp16")]; + tensor encoder_tp_encoders_3_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_3_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(339183232)))]; + tensor encoder_tp_encoders_3_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_3_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(341280448)))]; + tensor linear_215_cast_fp16 = linear(bias = encoder_tp_encoders_3_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_3_feed_forward_w_2_weight_to_fp16, x = input_1625_cast_fp16)[name = tensor("linear_215_cast_fp16")]; + tensor input_1631_cast_fp16 = add(x = input_1617_cast_fp16, y = linear_215_cast_fp16)[name = tensor("input_1631_cast_fp16")]; + tensor output_219_axes_0 = const()[name = tensor("output_219_axes_0"), val = tensor([-1])]; + tensor const_332_to_fp16 = const()[name = tensor("const_332_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(341281536)))]; + tensor const_333_to_fp16 = const()[name = tensor("const_333_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(341282624)))]; + tensor output_219_cast_fp16 = layer_norm(axes = output_219_axes_0, beta = const_333_to_fp16, epsilon = var_46_to_fp16, gamma = const_332_to_fp16, x = input_1631_cast_fp16)[name = tensor("output_219_cast_fp16")]; + tensor encoder_tp_encoders_4_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_4_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(341283712)))]; + tensor encoder_tp_encoders_4_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_4_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(342856640)))]; + tensor linear_216_cast_fp16 = linear(bias = encoder_tp_encoders_4_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_4_self_attn_linear_q_k_v_weight_to_fp16, x = output_219_cast_fp16)[name = tensor("linear_216_cast_fp16")]; + tensor tile_54 = const()[name = tensor("tile_54"), val = tensor([512, 512, 512])]; + tensor var_5799_axis_0 = const()[name = tensor("op_5799_axis_0"), val = tensor(-1)]; + tensor var_5799_cast_fp16_0, tensor var_5799_cast_fp16_1, tensor var_5799_cast_fp16_2 = split(axis = var_5799_axis_0, split_sizes = tile_54, x = linear_216_cast_fp16)[name = tensor("op_5799_cast_fp16")]; + tensor concat_162x = const()[name = tensor("concat_162x"), val = tensor([1, -1, 4, 128])]; + tensor var_5804_cast_fp16 = reshape(shape = concat_162x, x = var_5799_cast_fp16_0)[name = tensor("op_5804_cast_fp16")]; + tensor concat_163x = const()[name = tensor("concat_163x"), val = tensor([1, -1, 4, 128])]; + tensor var_5807_cast_fp16 = reshape(shape = concat_163x, x = var_5799_cast_fp16_1)[name = tensor("op_5807_cast_fp16")]; + tensor concat_164x = const()[name = tensor("concat_164x"), val = tensor([1, -1, 4, 128])]; + tensor var_5810_cast_fp16 = reshape(shape = concat_164x, x = var_5799_cast_fp16_2)[name = tensor("op_5810_cast_fp16")]; + tensor value_109_perm_0 = const()[name = tensor("value_109_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_109_cast_fp16 = mul(x = var_5799_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_109_cast_fp16")]; + tensor input_1635_perm_0 = const()[name = tensor("input_1635_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1637_pad_0 = const()[name = tensor("input_1637_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1637_mode_0 = const()[name = tensor("input_1637_mode_0"), val = tensor("constant")]; + tensor const_335_to_fp16 = const()[name = tensor("const_335_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1635_cast_fp16 = transpose(perm = input_1635_perm_0, x = inputs_109_cast_fp16)[name = tensor("transpose_444")]; + tensor input_1637_cast_fp16 = pad(constant_val = const_335_to_fp16, mode = input_1637_mode_0, pad = input_1637_pad_0, x = input_1635_cast_fp16)[name = tensor("input_1637_cast_fp16")]; + tensor x_545_pad_type_0 = const()[name = tensor("x_545_pad_type_0"), val = tensor("valid")]; + tensor x_545_groups_0 = const()[name = tensor("x_545_groups_0"), val = tensor(512)]; + tensor x_545_strides_0 = const()[name = tensor("x_545_strides_0"), val = tensor([1])]; + tensor x_545_pad_0 = const()[name = tensor("x_545_pad_0"), val = tensor([0, 0])]; + tensor x_545_dilations_0 = const()[name = tensor("x_545_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_4_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_4_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(342859776)))]; + tensor x_545_cast_fp16 = conv(dilations = x_545_dilations_0, groups = x_545_groups_0, pad = x_545_pad_0, pad_type = x_545_pad_type_0, strides = x_545_strides_0, weight = encoder_tp_encoders_4_self_attn_fsmn_block_weight_to_fp16, x = input_1637_cast_fp16)[name = tensor("x_545_cast_fp16")]; + tensor x_547_perm_0 = const()[name = tensor("x_547_perm_0"), val = tensor([0, 2, 1])]; + tensor x_547_cast_fp16 = transpose(perm = x_547_perm_0, x = x_545_cast_fp16)[name = tensor("transpose_443")]; + tensor input_1639_cast_fp16 = add(x = x_547_cast_fp16, y = inputs_109_cast_fp16)[name = tensor("input_1639_cast_fp16")]; + tensor fsmn_memory_109_cast_fp16 = mul(x = input_1639_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_109_cast_fp16")]; + tensor var_5829_to_fp16 = const()[name = tensor("op_5829_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_219_cast_fp16 = mul(x = var_5804_cast_fp16, y = var_5829_to_fp16)[name = tensor("q_h_219_cast_fp16")]; + tensor scores_217_transpose_x_0 = const()[name = tensor("scores_217_transpose_x_0"), val = tensor(false)]; + tensor scores_217_transpose_y_0 = const()[name = tensor("scores_217_transpose_y_0"), val = tensor(false)]; + tensor transpose_318_perm_0 = const()[name = tensor("transpose_318_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_319_perm_0 = const()[name = tensor("transpose_319_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_319 = transpose(perm = transpose_319_perm_0, x = var_5807_cast_fp16)[name = tensor("transpose_441")]; + tensor transpose_318 = transpose(perm = transpose_318_perm_0, x = q_h_219_cast_fp16)[name = tensor("transpose_442")]; + tensor scores_217_cast_fp16 = matmul(transpose_x = scores_217_transpose_x_0, transpose_y = scores_217_transpose_y_0, x = transpose_318, y = transpose_319)[name = tensor("scores_217_cast_fp16")]; + tensor scores_219_cast_fp16 = select(a = var_48_to_fp16, b = scores_217_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_219_cast_fp16")]; + tensor var_5837_cast_fp16 = softmax(axis = var_61, x = scores_219_cast_fp16)[name = tensor("op_5837_cast_fp16")]; + tensor input_1641_cast_fp16 = select(a = var_53_to_fp16, b = var_5837_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1641_cast_fp16")]; + tensor x_551_transpose_x_0 = const()[name = tensor("x_551_transpose_x_0"), val = tensor(false)]; + tensor x_551_transpose_y_0 = const()[name = tensor("x_551_transpose_y_0"), val = tensor(false)]; + tensor value_109_cast_fp16 = transpose(perm = value_109_perm_0, x = var_5810_cast_fp16)[name = tensor("transpose_445")]; + tensor x_551_cast_fp16 = matmul(transpose_x = x_551_transpose_x_0, transpose_y = x_551_transpose_y_0, x = input_1641_cast_fp16, y = value_109_cast_fp16)[name = tensor("x_551_cast_fp16")]; + tensor var_5841_perm_0 = const()[name = tensor("op_5841_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_5843 = const()[name = tensor("op_5843"), val = tensor([1, -1, 512])]; + tensor var_5841_cast_fp16 = transpose(perm = var_5841_perm_0, x = x_551_cast_fp16)[name = tensor("transpose_440")]; + tensor input_1643_cast_fp16 = reshape(shape = var_5843, x = var_5841_cast_fp16)[name = tensor("input_1643_cast_fp16")]; + tensor encoder_tp_encoders_4_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_4_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(342871104)))]; + tensor encoder_tp_encoders_4_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_4_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(343395456)))]; + tensor linear_217_cast_fp16 = linear(bias = encoder_tp_encoders_4_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_4_self_attn_linear_out_weight_to_fp16, x = input_1643_cast_fp16)[name = tensor("linear_217_cast_fp16")]; + tensor input_1645_cast_fp16 = add(x = linear_217_cast_fp16, y = fsmn_memory_109_cast_fp16)[name = tensor("input_1645_cast_fp16")]; + tensor input_1647_cast_fp16 = add(x = input_1631_cast_fp16, y = input_1645_cast_fp16)[name = tensor("input_1647_cast_fp16")]; + tensor output_221_axes_0 = const()[name = tensor("output_221_axes_0"), val = tensor([-1])]; + tensor const_336_to_fp16 = const()[name = tensor("const_336_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(343396544)))]; + tensor const_337_to_fp16 = const()[name = tensor("const_337_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(343397632)))]; + tensor output_221_cast_fp16 = layer_norm(axes = output_221_axes_0, beta = const_337_to_fp16, epsilon = var_46_to_fp16, gamma = const_336_to_fp16, x = input_1647_cast_fp16)[name = tensor("output_221_cast_fp16")]; + tensor encoder_tp_encoders_4_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_4_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(343398720)))]; + tensor encoder_tp_encoders_4_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_4_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(345495936)))]; + tensor linear_218_cast_fp16 = linear(bias = encoder_tp_encoders_4_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_4_feed_forward_w_1_weight_to_fp16, x = output_221_cast_fp16)[name = tensor("linear_218_cast_fp16")]; + tensor input_1655_cast_fp16 = relu(x = linear_218_cast_fp16)[name = tensor("input_1655_cast_fp16")]; + tensor encoder_tp_encoders_4_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_4_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(345500096)))]; + tensor encoder_tp_encoders_4_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_4_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(347597312)))]; + tensor linear_219_cast_fp16 = linear(bias = encoder_tp_encoders_4_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_4_feed_forward_w_2_weight_to_fp16, x = input_1655_cast_fp16)[name = tensor("linear_219_cast_fp16")]; + tensor input_1661_cast_fp16 = add(x = input_1647_cast_fp16, y = linear_219_cast_fp16)[name = tensor("input_1661_cast_fp16")]; + tensor output_223_axes_0 = const()[name = tensor("output_223_axes_0"), val = tensor([-1])]; + tensor const_338_to_fp16 = const()[name = tensor("const_338_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(347598400)))]; + tensor const_339_to_fp16 = const()[name = tensor("const_339_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(347599488)))]; + tensor output_223_cast_fp16 = layer_norm(axes = output_223_axes_0, beta = const_339_to_fp16, epsilon = var_46_to_fp16, gamma = const_338_to_fp16, x = input_1661_cast_fp16)[name = tensor("output_223_cast_fp16")]; + tensor encoder_tp_encoders_5_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_5_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(347600576)))]; + tensor encoder_tp_encoders_5_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_5_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(349173504)))]; + tensor linear_220_cast_fp16 = linear(bias = encoder_tp_encoders_5_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_5_self_attn_linear_q_k_v_weight_to_fp16, x = output_223_cast_fp16)[name = tensor("linear_220_cast_fp16")]; + tensor tile_55 = const()[name = tensor("tile_55"), val = tensor([512, 512, 512])]; + tensor var_5901_axis_0 = const()[name = tensor("op_5901_axis_0"), val = tensor(-1)]; + tensor var_5901_cast_fp16_0, tensor var_5901_cast_fp16_1, tensor var_5901_cast_fp16_2 = split(axis = var_5901_axis_0, split_sizes = tile_55, x = linear_220_cast_fp16)[name = tensor("op_5901_cast_fp16")]; + tensor concat_165x = const()[name = tensor("concat_165x"), val = tensor([1, -1, 4, 128])]; + tensor var_5906_cast_fp16 = reshape(shape = concat_165x, x = var_5901_cast_fp16_0)[name = tensor("op_5906_cast_fp16")]; + tensor concat_166x = const()[name = tensor("concat_166x"), val = tensor([1, -1, 4, 128])]; + tensor var_5909_cast_fp16 = reshape(shape = concat_166x, x = var_5901_cast_fp16_1)[name = tensor("op_5909_cast_fp16")]; + tensor concat_167x = const()[name = tensor("concat_167x"), val = tensor([1, -1, 4, 128])]; + tensor var_5912_cast_fp16 = reshape(shape = concat_167x, x = var_5901_cast_fp16_2)[name = tensor("op_5912_cast_fp16")]; + tensor value_111_perm_0 = const()[name = tensor("value_111_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_111_cast_fp16 = mul(x = var_5901_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_111_cast_fp16")]; + tensor input_1665_perm_0 = const()[name = tensor("input_1665_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1667_pad_0 = const()[name = tensor("input_1667_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1667_mode_0 = const()[name = tensor("input_1667_mode_0"), val = tensor("constant")]; + tensor const_341_to_fp16 = const()[name = tensor("const_341_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1665_cast_fp16 = transpose(perm = input_1665_perm_0, x = inputs_111_cast_fp16)[name = tensor("transpose_438")]; + tensor input_1667_cast_fp16 = pad(constant_val = const_341_to_fp16, mode = input_1667_mode_0, pad = input_1667_pad_0, x = input_1665_cast_fp16)[name = tensor("input_1667_cast_fp16")]; + tensor x_555_pad_type_0 = const()[name = tensor("x_555_pad_type_0"), val = tensor("valid")]; + tensor x_555_groups_0 = const()[name = tensor("x_555_groups_0"), val = tensor(512)]; + tensor x_555_strides_0 = const()[name = tensor("x_555_strides_0"), val = tensor([1])]; + tensor x_555_pad_0 = const()[name = tensor("x_555_pad_0"), val = tensor([0, 0])]; + tensor x_555_dilations_0 = const()[name = tensor("x_555_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_5_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_5_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(349176640)))]; + tensor x_555_cast_fp16 = conv(dilations = x_555_dilations_0, groups = x_555_groups_0, pad = x_555_pad_0, pad_type = x_555_pad_type_0, strides = x_555_strides_0, weight = encoder_tp_encoders_5_self_attn_fsmn_block_weight_to_fp16, x = input_1667_cast_fp16)[name = tensor("x_555_cast_fp16")]; + tensor x_557_perm_0 = const()[name = tensor("x_557_perm_0"), val = tensor([0, 2, 1])]; + tensor x_557_cast_fp16 = transpose(perm = x_557_perm_0, x = x_555_cast_fp16)[name = tensor("transpose_437")]; + tensor input_1669_cast_fp16 = add(x = x_557_cast_fp16, y = inputs_111_cast_fp16)[name = tensor("input_1669_cast_fp16")]; + tensor fsmn_memory_111_cast_fp16 = mul(x = input_1669_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_111_cast_fp16")]; + tensor var_5931_to_fp16 = const()[name = tensor("op_5931_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_223_cast_fp16 = mul(x = var_5906_cast_fp16, y = var_5931_to_fp16)[name = tensor("q_h_223_cast_fp16")]; + tensor scores_221_transpose_x_0 = const()[name = tensor("scores_221_transpose_x_0"), val = tensor(false)]; + tensor scores_221_transpose_y_0 = const()[name = tensor("scores_221_transpose_y_0"), val = tensor(false)]; + tensor transpose_320_perm_0 = const()[name = tensor("transpose_320_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_321_perm_0 = const()[name = tensor("transpose_321_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_321 = transpose(perm = transpose_321_perm_0, x = var_5909_cast_fp16)[name = tensor("transpose_435")]; + tensor transpose_320 = transpose(perm = transpose_320_perm_0, x = q_h_223_cast_fp16)[name = tensor("transpose_436")]; + tensor scores_221_cast_fp16 = matmul(transpose_x = scores_221_transpose_x_0, transpose_y = scores_221_transpose_y_0, x = transpose_320, y = transpose_321)[name = tensor("scores_221_cast_fp16")]; + tensor scores_223_cast_fp16 = select(a = var_48_to_fp16, b = scores_221_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_223_cast_fp16")]; + tensor var_5939_cast_fp16 = softmax(axis = var_61, x = scores_223_cast_fp16)[name = tensor("op_5939_cast_fp16")]; + tensor input_1671_cast_fp16 = select(a = var_53_to_fp16, b = var_5939_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1671_cast_fp16")]; + tensor x_561_transpose_x_0 = const()[name = tensor("x_561_transpose_x_0"), val = tensor(false)]; + tensor x_561_transpose_y_0 = const()[name = tensor("x_561_transpose_y_0"), val = tensor(false)]; + tensor value_111_cast_fp16 = transpose(perm = value_111_perm_0, x = var_5912_cast_fp16)[name = tensor("transpose_439")]; + tensor x_561_cast_fp16 = matmul(transpose_x = x_561_transpose_x_0, transpose_y = x_561_transpose_y_0, x = input_1671_cast_fp16, y = value_111_cast_fp16)[name = tensor("x_561_cast_fp16")]; + tensor var_5943_perm_0 = const()[name = tensor("op_5943_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_5945 = const()[name = tensor("op_5945"), val = tensor([1, -1, 512])]; + tensor var_5943_cast_fp16 = transpose(perm = var_5943_perm_0, x = x_561_cast_fp16)[name = tensor("transpose_434")]; + tensor input_1673_cast_fp16 = reshape(shape = var_5945, x = var_5943_cast_fp16)[name = tensor("input_1673_cast_fp16")]; + tensor encoder_tp_encoders_5_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_5_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(349187968)))]; + tensor encoder_tp_encoders_5_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_5_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(349712320)))]; + tensor linear_221_cast_fp16 = linear(bias = encoder_tp_encoders_5_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_5_self_attn_linear_out_weight_to_fp16, x = input_1673_cast_fp16)[name = tensor("linear_221_cast_fp16")]; + tensor input_1675_cast_fp16 = add(x = linear_221_cast_fp16, y = fsmn_memory_111_cast_fp16)[name = tensor("input_1675_cast_fp16")]; + tensor input_1677_cast_fp16 = add(x = input_1661_cast_fp16, y = input_1675_cast_fp16)[name = tensor("input_1677_cast_fp16")]; + tensor output_225_axes_0 = const()[name = tensor("output_225_axes_0"), val = tensor([-1])]; + tensor const_342_to_fp16 = const()[name = tensor("const_342_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(349713408)))]; + tensor const_343_to_fp16 = const()[name = tensor("const_343_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(349714496)))]; + tensor output_225_cast_fp16 = layer_norm(axes = output_225_axes_0, beta = const_343_to_fp16, epsilon = var_46_to_fp16, gamma = const_342_to_fp16, x = input_1677_cast_fp16)[name = tensor("output_225_cast_fp16")]; + tensor encoder_tp_encoders_5_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_5_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(349715584)))]; + tensor encoder_tp_encoders_5_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_5_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(351812800)))]; + tensor linear_222_cast_fp16 = linear(bias = encoder_tp_encoders_5_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_5_feed_forward_w_1_weight_to_fp16, x = output_225_cast_fp16)[name = tensor("linear_222_cast_fp16")]; + tensor input_1685_cast_fp16 = relu(x = linear_222_cast_fp16)[name = tensor("input_1685_cast_fp16")]; + tensor encoder_tp_encoders_5_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_5_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(351816960)))]; + tensor encoder_tp_encoders_5_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_5_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(353914176)))]; + tensor linear_223_cast_fp16 = linear(bias = encoder_tp_encoders_5_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_5_feed_forward_w_2_weight_to_fp16, x = input_1685_cast_fp16)[name = tensor("linear_223_cast_fp16")]; + tensor input_1691_cast_fp16 = add(x = input_1677_cast_fp16, y = linear_223_cast_fp16)[name = tensor("input_1691_cast_fp16")]; + tensor output_227_axes_0 = const()[name = tensor("output_227_axes_0"), val = tensor([-1])]; + tensor const_344_to_fp16 = const()[name = tensor("const_344_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(353915264)))]; + tensor const_345_to_fp16 = const()[name = tensor("const_345_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(353916352)))]; + tensor output_227_cast_fp16 = layer_norm(axes = output_227_axes_0, beta = const_345_to_fp16, epsilon = var_46_to_fp16, gamma = const_344_to_fp16, x = input_1691_cast_fp16)[name = tensor("output_227_cast_fp16")]; + tensor encoder_tp_encoders_6_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_6_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(353917440)))]; + tensor encoder_tp_encoders_6_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_6_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(355490368)))]; + tensor linear_224_cast_fp16 = linear(bias = encoder_tp_encoders_6_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_6_self_attn_linear_q_k_v_weight_to_fp16, x = output_227_cast_fp16)[name = tensor("linear_224_cast_fp16")]; + tensor tile_56 = const()[name = tensor("tile_56"), val = tensor([512, 512, 512])]; + tensor var_6003_axis_0 = const()[name = tensor("op_6003_axis_0"), val = tensor(-1)]; + tensor var_6003_cast_fp16_0, tensor var_6003_cast_fp16_1, tensor var_6003_cast_fp16_2 = split(axis = var_6003_axis_0, split_sizes = tile_56, x = linear_224_cast_fp16)[name = tensor("op_6003_cast_fp16")]; + tensor concat_168x = const()[name = tensor("concat_168x"), val = tensor([1, -1, 4, 128])]; + tensor var_6008_cast_fp16 = reshape(shape = concat_168x, x = var_6003_cast_fp16_0)[name = tensor("op_6008_cast_fp16")]; + tensor concat_169x = const()[name = tensor("concat_169x"), val = tensor([1, -1, 4, 128])]; + tensor var_6011_cast_fp16 = reshape(shape = concat_169x, x = var_6003_cast_fp16_1)[name = tensor("op_6011_cast_fp16")]; + tensor concat_170x = const()[name = tensor("concat_170x"), val = tensor([1, -1, 4, 128])]; + tensor var_6014_cast_fp16 = reshape(shape = concat_170x, x = var_6003_cast_fp16_2)[name = tensor("op_6014_cast_fp16")]; + tensor value_113_perm_0 = const()[name = tensor("value_113_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_113_cast_fp16 = mul(x = var_6003_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_113_cast_fp16")]; + tensor input_1695_perm_0 = const()[name = tensor("input_1695_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1697_pad_0 = const()[name = tensor("input_1697_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1697_mode_0 = const()[name = tensor("input_1697_mode_0"), val = tensor("constant")]; + tensor const_347_to_fp16 = const()[name = tensor("const_347_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1695_cast_fp16 = transpose(perm = input_1695_perm_0, x = inputs_113_cast_fp16)[name = tensor("transpose_432")]; + tensor input_1697_cast_fp16 = pad(constant_val = const_347_to_fp16, mode = input_1697_mode_0, pad = input_1697_pad_0, x = input_1695_cast_fp16)[name = tensor("input_1697_cast_fp16")]; + tensor x_565_pad_type_0 = const()[name = tensor("x_565_pad_type_0"), val = tensor("valid")]; + tensor x_565_groups_0 = const()[name = tensor("x_565_groups_0"), val = tensor(512)]; + tensor x_565_strides_0 = const()[name = tensor("x_565_strides_0"), val = tensor([1])]; + tensor x_565_pad_0 = const()[name = tensor("x_565_pad_0"), val = tensor([0, 0])]; + tensor x_565_dilations_0 = const()[name = tensor("x_565_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_6_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_6_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(355493504)))]; + tensor x_565_cast_fp16 = conv(dilations = x_565_dilations_0, groups = x_565_groups_0, pad = x_565_pad_0, pad_type = x_565_pad_type_0, strides = x_565_strides_0, weight = encoder_tp_encoders_6_self_attn_fsmn_block_weight_to_fp16, x = input_1697_cast_fp16)[name = tensor("x_565_cast_fp16")]; + tensor x_567_perm_0 = const()[name = tensor("x_567_perm_0"), val = tensor([0, 2, 1])]; + tensor x_567_cast_fp16 = transpose(perm = x_567_perm_0, x = x_565_cast_fp16)[name = tensor("transpose_431")]; + tensor input_1699_cast_fp16 = add(x = x_567_cast_fp16, y = inputs_113_cast_fp16)[name = tensor("input_1699_cast_fp16")]; + tensor fsmn_memory_113_cast_fp16 = mul(x = input_1699_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_113_cast_fp16")]; + tensor var_6033_to_fp16 = const()[name = tensor("op_6033_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_227_cast_fp16 = mul(x = var_6008_cast_fp16, y = var_6033_to_fp16)[name = tensor("q_h_227_cast_fp16")]; + tensor scores_225_transpose_x_0 = const()[name = tensor("scores_225_transpose_x_0"), val = tensor(false)]; + tensor scores_225_transpose_y_0 = const()[name = tensor("scores_225_transpose_y_0"), val = tensor(false)]; + tensor transpose_322_perm_0 = const()[name = tensor("transpose_322_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_323_perm_0 = const()[name = tensor("transpose_323_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_323 = transpose(perm = transpose_323_perm_0, x = var_6011_cast_fp16)[name = tensor("transpose_429")]; + tensor transpose_322 = transpose(perm = transpose_322_perm_0, x = q_h_227_cast_fp16)[name = tensor("transpose_430")]; + tensor scores_225_cast_fp16 = matmul(transpose_x = scores_225_transpose_x_0, transpose_y = scores_225_transpose_y_0, x = transpose_322, y = transpose_323)[name = tensor("scores_225_cast_fp16")]; + tensor scores_227_cast_fp16 = select(a = var_48_to_fp16, b = scores_225_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_227_cast_fp16")]; + tensor var_6041_cast_fp16 = softmax(axis = var_61, x = scores_227_cast_fp16)[name = tensor("op_6041_cast_fp16")]; + tensor input_1701_cast_fp16 = select(a = var_53_to_fp16, b = var_6041_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1701_cast_fp16")]; + tensor x_571_transpose_x_0 = const()[name = tensor("x_571_transpose_x_0"), val = tensor(false)]; + tensor x_571_transpose_y_0 = const()[name = tensor("x_571_transpose_y_0"), val = tensor(false)]; + tensor value_113_cast_fp16 = transpose(perm = value_113_perm_0, x = var_6014_cast_fp16)[name = tensor("transpose_433")]; + tensor x_571_cast_fp16 = matmul(transpose_x = x_571_transpose_x_0, transpose_y = x_571_transpose_y_0, x = input_1701_cast_fp16, y = value_113_cast_fp16)[name = tensor("x_571_cast_fp16")]; + tensor var_6045_perm_0 = const()[name = tensor("op_6045_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_6047 = const()[name = tensor("op_6047"), val = tensor([1, -1, 512])]; + tensor var_6045_cast_fp16 = transpose(perm = var_6045_perm_0, x = x_571_cast_fp16)[name = tensor("transpose_428")]; + tensor input_1703_cast_fp16 = reshape(shape = var_6047, x = var_6045_cast_fp16)[name = tensor("input_1703_cast_fp16")]; + tensor encoder_tp_encoders_6_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_6_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(355504832)))]; + tensor encoder_tp_encoders_6_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_6_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(356029184)))]; + tensor linear_225_cast_fp16 = linear(bias = encoder_tp_encoders_6_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_6_self_attn_linear_out_weight_to_fp16, x = input_1703_cast_fp16)[name = tensor("linear_225_cast_fp16")]; + tensor input_1705_cast_fp16 = add(x = linear_225_cast_fp16, y = fsmn_memory_113_cast_fp16)[name = tensor("input_1705_cast_fp16")]; + tensor input_1707_cast_fp16 = add(x = input_1691_cast_fp16, y = input_1705_cast_fp16)[name = tensor("input_1707_cast_fp16")]; + tensor output_229_axes_0 = const()[name = tensor("output_229_axes_0"), val = tensor([-1])]; + tensor const_348_to_fp16 = const()[name = tensor("const_348_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(356030272)))]; + tensor const_349_to_fp16 = const()[name = tensor("const_349_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(356031360)))]; + tensor output_229_cast_fp16 = layer_norm(axes = output_229_axes_0, beta = const_349_to_fp16, epsilon = var_46_to_fp16, gamma = const_348_to_fp16, x = input_1707_cast_fp16)[name = tensor("output_229_cast_fp16")]; + tensor encoder_tp_encoders_6_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_6_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(356032448)))]; + tensor encoder_tp_encoders_6_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_6_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(358129664)))]; + tensor linear_226_cast_fp16 = linear(bias = encoder_tp_encoders_6_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_6_feed_forward_w_1_weight_to_fp16, x = output_229_cast_fp16)[name = tensor("linear_226_cast_fp16")]; + tensor input_1715_cast_fp16 = relu(x = linear_226_cast_fp16)[name = tensor("input_1715_cast_fp16")]; + tensor encoder_tp_encoders_6_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_6_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(358133824)))]; + tensor encoder_tp_encoders_6_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_6_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(360231040)))]; + tensor linear_227_cast_fp16 = linear(bias = encoder_tp_encoders_6_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_6_feed_forward_w_2_weight_to_fp16, x = input_1715_cast_fp16)[name = tensor("linear_227_cast_fp16")]; + tensor input_1721_cast_fp16 = add(x = input_1707_cast_fp16, y = linear_227_cast_fp16)[name = tensor("input_1721_cast_fp16")]; + tensor output_231_axes_0 = const()[name = tensor("output_231_axes_0"), val = tensor([-1])]; + tensor const_350_to_fp16 = const()[name = tensor("const_350_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(360232128)))]; + tensor const_351_to_fp16 = const()[name = tensor("const_351_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(360233216)))]; + tensor output_231_cast_fp16 = layer_norm(axes = output_231_axes_0, beta = const_351_to_fp16, epsilon = var_46_to_fp16, gamma = const_350_to_fp16, x = input_1721_cast_fp16)[name = tensor("output_231_cast_fp16")]; + tensor encoder_tp_encoders_7_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_7_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(360234304)))]; + tensor encoder_tp_encoders_7_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_7_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(361807232)))]; + tensor linear_228_cast_fp16 = linear(bias = encoder_tp_encoders_7_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_7_self_attn_linear_q_k_v_weight_to_fp16, x = output_231_cast_fp16)[name = tensor("linear_228_cast_fp16")]; + tensor tile_57 = const()[name = tensor("tile_57"), val = tensor([512, 512, 512])]; + tensor var_6105_axis_0 = const()[name = tensor("op_6105_axis_0"), val = tensor(-1)]; + tensor var_6105_cast_fp16_0, tensor var_6105_cast_fp16_1, tensor var_6105_cast_fp16_2 = split(axis = var_6105_axis_0, split_sizes = tile_57, x = linear_228_cast_fp16)[name = tensor("op_6105_cast_fp16")]; + tensor concat_171x = const()[name = tensor("concat_171x"), val = tensor([1, -1, 4, 128])]; + tensor var_6110_cast_fp16 = reshape(shape = concat_171x, x = var_6105_cast_fp16_0)[name = tensor("op_6110_cast_fp16")]; + tensor concat_172x = const()[name = tensor("concat_172x"), val = tensor([1, -1, 4, 128])]; + tensor var_6113_cast_fp16 = reshape(shape = concat_172x, x = var_6105_cast_fp16_1)[name = tensor("op_6113_cast_fp16")]; + tensor concat_173x = const()[name = tensor("concat_173x"), val = tensor([1, -1, 4, 128])]; + tensor var_6116_cast_fp16 = reshape(shape = concat_173x, x = var_6105_cast_fp16_2)[name = tensor("op_6116_cast_fp16")]; + tensor value_115_perm_0 = const()[name = tensor("value_115_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_115_cast_fp16 = mul(x = var_6105_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_115_cast_fp16")]; + tensor input_1725_perm_0 = const()[name = tensor("input_1725_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1727_pad_0 = const()[name = tensor("input_1727_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1727_mode_0 = const()[name = tensor("input_1727_mode_0"), val = tensor("constant")]; + tensor const_353_to_fp16 = const()[name = tensor("const_353_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1725_cast_fp16 = transpose(perm = input_1725_perm_0, x = inputs_115_cast_fp16)[name = tensor("transpose_426")]; + tensor input_1727_cast_fp16 = pad(constant_val = const_353_to_fp16, mode = input_1727_mode_0, pad = input_1727_pad_0, x = input_1725_cast_fp16)[name = tensor("input_1727_cast_fp16")]; + tensor x_575_pad_type_0 = const()[name = tensor("x_575_pad_type_0"), val = tensor("valid")]; + tensor x_575_groups_0 = const()[name = tensor("x_575_groups_0"), val = tensor(512)]; + tensor x_575_strides_0 = const()[name = tensor("x_575_strides_0"), val = tensor([1])]; + tensor x_575_pad_0 = const()[name = tensor("x_575_pad_0"), val = tensor([0, 0])]; + tensor x_575_dilations_0 = const()[name = tensor("x_575_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_7_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_7_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(361810368)))]; + tensor x_575_cast_fp16 = conv(dilations = x_575_dilations_0, groups = x_575_groups_0, pad = x_575_pad_0, pad_type = x_575_pad_type_0, strides = x_575_strides_0, weight = encoder_tp_encoders_7_self_attn_fsmn_block_weight_to_fp16, x = input_1727_cast_fp16)[name = tensor("x_575_cast_fp16")]; + tensor x_577_perm_0 = const()[name = tensor("x_577_perm_0"), val = tensor([0, 2, 1])]; + tensor x_577_cast_fp16 = transpose(perm = x_577_perm_0, x = x_575_cast_fp16)[name = tensor("transpose_425")]; + tensor input_1729_cast_fp16 = add(x = x_577_cast_fp16, y = inputs_115_cast_fp16)[name = tensor("input_1729_cast_fp16")]; + tensor fsmn_memory_115_cast_fp16 = mul(x = input_1729_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_115_cast_fp16")]; + tensor var_6135_to_fp16 = const()[name = tensor("op_6135_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_231_cast_fp16 = mul(x = var_6110_cast_fp16, y = var_6135_to_fp16)[name = tensor("q_h_231_cast_fp16")]; + tensor scores_229_transpose_x_0 = const()[name = tensor("scores_229_transpose_x_0"), val = tensor(false)]; + tensor scores_229_transpose_y_0 = const()[name = tensor("scores_229_transpose_y_0"), val = tensor(false)]; + tensor transpose_324_perm_0 = const()[name = tensor("transpose_324_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_325_perm_0 = const()[name = tensor("transpose_325_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_325 = transpose(perm = transpose_325_perm_0, x = var_6113_cast_fp16)[name = tensor("transpose_423")]; + tensor transpose_324 = transpose(perm = transpose_324_perm_0, x = q_h_231_cast_fp16)[name = tensor("transpose_424")]; + tensor scores_229_cast_fp16 = matmul(transpose_x = scores_229_transpose_x_0, transpose_y = scores_229_transpose_y_0, x = transpose_324, y = transpose_325)[name = tensor("scores_229_cast_fp16")]; + tensor scores_231_cast_fp16 = select(a = var_48_to_fp16, b = scores_229_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_231_cast_fp16")]; + tensor var_6143_cast_fp16 = softmax(axis = var_61, x = scores_231_cast_fp16)[name = tensor("op_6143_cast_fp16")]; + tensor input_1731_cast_fp16 = select(a = var_53_to_fp16, b = var_6143_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1731_cast_fp16")]; + tensor x_581_transpose_x_0 = const()[name = tensor("x_581_transpose_x_0"), val = tensor(false)]; + tensor x_581_transpose_y_0 = const()[name = tensor("x_581_transpose_y_0"), val = tensor(false)]; + tensor value_115_cast_fp16 = transpose(perm = value_115_perm_0, x = var_6116_cast_fp16)[name = tensor("transpose_427")]; + tensor x_581_cast_fp16 = matmul(transpose_x = x_581_transpose_x_0, transpose_y = x_581_transpose_y_0, x = input_1731_cast_fp16, y = value_115_cast_fp16)[name = tensor("x_581_cast_fp16")]; + tensor var_6147_perm_0 = const()[name = tensor("op_6147_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_6149 = const()[name = tensor("op_6149"), val = tensor([1, -1, 512])]; + tensor var_6147_cast_fp16 = transpose(perm = var_6147_perm_0, x = x_581_cast_fp16)[name = tensor("transpose_422")]; + tensor input_1733_cast_fp16 = reshape(shape = var_6149, x = var_6147_cast_fp16)[name = tensor("input_1733_cast_fp16")]; + tensor encoder_tp_encoders_7_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_7_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(361821696)))]; + tensor encoder_tp_encoders_7_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_7_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(362346048)))]; + tensor linear_229_cast_fp16 = linear(bias = encoder_tp_encoders_7_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_7_self_attn_linear_out_weight_to_fp16, x = input_1733_cast_fp16)[name = tensor("linear_229_cast_fp16")]; + tensor input_1735_cast_fp16 = add(x = linear_229_cast_fp16, y = fsmn_memory_115_cast_fp16)[name = tensor("input_1735_cast_fp16")]; + tensor input_1737_cast_fp16 = add(x = input_1721_cast_fp16, y = input_1735_cast_fp16)[name = tensor("input_1737_cast_fp16")]; + tensor output_233_axes_0 = const()[name = tensor("output_233_axes_0"), val = tensor([-1])]; + tensor const_354_to_fp16 = const()[name = tensor("const_354_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(362347136)))]; + tensor const_355_to_fp16 = const()[name = tensor("const_355_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(362348224)))]; + tensor output_233_cast_fp16 = layer_norm(axes = output_233_axes_0, beta = const_355_to_fp16, epsilon = var_46_to_fp16, gamma = const_354_to_fp16, x = input_1737_cast_fp16)[name = tensor("output_233_cast_fp16")]; + tensor encoder_tp_encoders_7_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_7_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(362349312)))]; + tensor encoder_tp_encoders_7_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_7_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(364446528)))]; + tensor linear_230_cast_fp16 = linear(bias = encoder_tp_encoders_7_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_7_feed_forward_w_1_weight_to_fp16, x = output_233_cast_fp16)[name = tensor("linear_230_cast_fp16")]; + tensor input_1745_cast_fp16 = relu(x = linear_230_cast_fp16)[name = tensor("input_1745_cast_fp16")]; + tensor encoder_tp_encoders_7_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_7_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(364450688)))]; + tensor encoder_tp_encoders_7_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_7_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(366547904)))]; + tensor linear_231_cast_fp16 = linear(bias = encoder_tp_encoders_7_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_7_feed_forward_w_2_weight_to_fp16, x = input_1745_cast_fp16)[name = tensor("linear_231_cast_fp16")]; + tensor input_1751_cast_fp16 = add(x = input_1737_cast_fp16, y = linear_231_cast_fp16)[name = tensor("input_1751_cast_fp16")]; + tensor output_235_axes_0 = const()[name = tensor("output_235_axes_0"), val = tensor([-1])]; + tensor const_356_to_fp16 = const()[name = tensor("const_356_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(366548992)))]; + tensor const_357_to_fp16 = const()[name = tensor("const_357_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(366550080)))]; + tensor output_235_cast_fp16 = layer_norm(axes = output_235_axes_0, beta = const_357_to_fp16, epsilon = var_46_to_fp16, gamma = const_356_to_fp16, x = input_1751_cast_fp16)[name = tensor("output_235_cast_fp16")]; + tensor encoder_tp_encoders_8_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_8_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(366551168)))]; + tensor encoder_tp_encoders_8_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_8_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(368124096)))]; + tensor linear_232_cast_fp16 = linear(bias = encoder_tp_encoders_8_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_8_self_attn_linear_q_k_v_weight_to_fp16, x = output_235_cast_fp16)[name = tensor("linear_232_cast_fp16")]; + tensor tile_58 = const()[name = tensor("tile_58"), val = tensor([512, 512, 512])]; + tensor var_6207_axis_0 = const()[name = tensor("op_6207_axis_0"), val = tensor(-1)]; + tensor var_6207_cast_fp16_0, tensor var_6207_cast_fp16_1, tensor var_6207_cast_fp16_2 = split(axis = var_6207_axis_0, split_sizes = tile_58, x = linear_232_cast_fp16)[name = tensor("op_6207_cast_fp16")]; + tensor concat_174x = const()[name = tensor("concat_174x"), val = tensor([1, -1, 4, 128])]; + tensor var_6212_cast_fp16 = reshape(shape = concat_174x, x = var_6207_cast_fp16_0)[name = tensor("op_6212_cast_fp16")]; + tensor concat_175x = const()[name = tensor("concat_175x"), val = tensor([1, -1, 4, 128])]; + tensor var_6215_cast_fp16 = reshape(shape = concat_175x, x = var_6207_cast_fp16_1)[name = tensor("op_6215_cast_fp16")]; + tensor concat_176x = const()[name = tensor("concat_176x"), val = tensor([1, -1, 4, 128])]; + tensor var_6218_cast_fp16 = reshape(shape = concat_176x, x = var_6207_cast_fp16_2)[name = tensor("op_6218_cast_fp16")]; + tensor value_117_perm_0 = const()[name = tensor("value_117_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_117_cast_fp16 = mul(x = var_6207_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_117_cast_fp16")]; + tensor input_1755_perm_0 = const()[name = tensor("input_1755_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1757_pad_0 = const()[name = tensor("input_1757_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1757_mode_0 = const()[name = tensor("input_1757_mode_0"), val = tensor("constant")]; + tensor const_359_to_fp16 = const()[name = tensor("const_359_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1755_cast_fp16 = transpose(perm = input_1755_perm_0, x = inputs_117_cast_fp16)[name = tensor("transpose_420")]; + tensor input_1757_cast_fp16 = pad(constant_val = const_359_to_fp16, mode = input_1757_mode_0, pad = input_1757_pad_0, x = input_1755_cast_fp16)[name = tensor("input_1757_cast_fp16")]; + tensor x_585_pad_type_0 = const()[name = tensor("x_585_pad_type_0"), val = tensor("valid")]; + tensor x_585_groups_0 = const()[name = tensor("x_585_groups_0"), val = tensor(512)]; + tensor x_585_strides_0 = const()[name = tensor("x_585_strides_0"), val = tensor([1])]; + tensor x_585_pad_0 = const()[name = tensor("x_585_pad_0"), val = tensor([0, 0])]; + tensor x_585_dilations_0 = const()[name = tensor("x_585_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_8_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_8_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(368127232)))]; + tensor x_585_cast_fp16 = conv(dilations = x_585_dilations_0, groups = x_585_groups_0, pad = x_585_pad_0, pad_type = x_585_pad_type_0, strides = x_585_strides_0, weight = encoder_tp_encoders_8_self_attn_fsmn_block_weight_to_fp16, x = input_1757_cast_fp16)[name = tensor("x_585_cast_fp16")]; + tensor x_587_perm_0 = const()[name = tensor("x_587_perm_0"), val = tensor([0, 2, 1])]; + tensor x_587_cast_fp16 = transpose(perm = x_587_perm_0, x = x_585_cast_fp16)[name = tensor("transpose_419")]; + tensor input_1759_cast_fp16 = add(x = x_587_cast_fp16, y = inputs_117_cast_fp16)[name = tensor("input_1759_cast_fp16")]; + tensor fsmn_memory_117_cast_fp16 = mul(x = input_1759_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_117_cast_fp16")]; + tensor var_6237_to_fp16 = const()[name = tensor("op_6237_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_235_cast_fp16 = mul(x = var_6212_cast_fp16, y = var_6237_to_fp16)[name = tensor("q_h_235_cast_fp16")]; + tensor scores_233_transpose_x_0 = const()[name = tensor("scores_233_transpose_x_0"), val = tensor(false)]; + tensor scores_233_transpose_y_0 = const()[name = tensor("scores_233_transpose_y_0"), val = tensor(false)]; + tensor transpose_326_perm_0 = const()[name = tensor("transpose_326_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_327_perm_0 = const()[name = tensor("transpose_327_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_327 = transpose(perm = transpose_327_perm_0, x = var_6215_cast_fp16)[name = tensor("transpose_417")]; + tensor transpose_326 = transpose(perm = transpose_326_perm_0, x = q_h_235_cast_fp16)[name = tensor("transpose_418")]; + tensor scores_233_cast_fp16 = matmul(transpose_x = scores_233_transpose_x_0, transpose_y = scores_233_transpose_y_0, x = transpose_326, y = transpose_327)[name = tensor("scores_233_cast_fp16")]; + tensor scores_235_cast_fp16 = select(a = var_48_to_fp16, b = scores_233_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_235_cast_fp16")]; + tensor var_6245_cast_fp16 = softmax(axis = var_61, x = scores_235_cast_fp16)[name = tensor("op_6245_cast_fp16")]; + tensor input_1761_cast_fp16 = select(a = var_53_to_fp16, b = var_6245_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1761_cast_fp16")]; + tensor x_591_transpose_x_0 = const()[name = tensor("x_591_transpose_x_0"), val = tensor(false)]; + tensor x_591_transpose_y_0 = const()[name = tensor("x_591_transpose_y_0"), val = tensor(false)]; + tensor value_117_cast_fp16 = transpose(perm = value_117_perm_0, x = var_6218_cast_fp16)[name = tensor("transpose_421")]; + tensor x_591_cast_fp16 = matmul(transpose_x = x_591_transpose_x_0, transpose_y = x_591_transpose_y_0, x = input_1761_cast_fp16, y = value_117_cast_fp16)[name = tensor("x_591_cast_fp16")]; + tensor var_6249_perm_0 = const()[name = tensor("op_6249_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_6251 = const()[name = tensor("op_6251"), val = tensor([1, -1, 512])]; + tensor var_6249_cast_fp16 = transpose(perm = var_6249_perm_0, x = x_591_cast_fp16)[name = tensor("transpose_416")]; + tensor input_1763_cast_fp16 = reshape(shape = var_6251, x = var_6249_cast_fp16)[name = tensor("input_1763_cast_fp16")]; + tensor encoder_tp_encoders_8_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_8_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(368138560)))]; + tensor encoder_tp_encoders_8_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_8_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(368662912)))]; + tensor linear_233_cast_fp16 = linear(bias = encoder_tp_encoders_8_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_8_self_attn_linear_out_weight_to_fp16, x = input_1763_cast_fp16)[name = tensor("linear_233_cast_fp16")]; + tensor input_1765_cast_fp16 = add(x = linear_233_cast_fp16, y = fsmn_memory_117_cast_fp16)[name = tensor("input_1765_cast_fp16")]; + tensor input_1767_cast_fp16 = add(x = input_1751_cast_fp16, y = input_1765_cast_fp16)[name = tensor("input_1767_cast_fp16")]; + tensor output_237_axes_0 = const()[name = tensor("output_237_axes_0"), val = tensor([-1])]; + tensor const_360_to_fp16 = const()[name = tensor("const_360_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(368664000)))]; + tensor const_361_to_fp16 = const()[name = tensor("const_361_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(368665088)))]; + tensor output_237_cast_fp16 = layer_norm(axes = output_237_axes_0, beta = const_361_to_fp16, epsilon = var_46_to_fp16, gamma = const_360_to_fp16, x = input_1767_cast_fp16)[name = tensor("output_237_cast_fp16")]; + tensor encoder_tp_encoders_8_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_8_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(368666176)))]; + tensor encoder_tp_encoders_8_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_8_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(370763392)))]; + tensor linear_234_cast_fp16 = linear(bias = encoder_tp_encoders_8_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_8_feed_forward_w_1_weight_to_fp16, x = output_237_cast_fp16)[name = tensor("linear_234_cast_fp16")]; + tensor input_1775_cast_fp16 = relu(x = linear_234_cast_fp16)[name = tensor("input_1775_cast_fp16")]; + tensor encoder_tp_encoders_8_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_8_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(370767552)))]; + tensor encoder_tp_encoders_8_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_8_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(372864768)))]; + tensor linear_235_cast_fp16 = linear(bias = encoder_tp_encoders_8_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_8_feed_forward_w_2_weight_to_fp16, x = input_1775_cast_fp16)[name = tensor("linear_235_cast_fp16")]; + tensor input_1781_cast_fp16 = add(x = input_1767_cast_fp16, y = linear_235_cast_fp16)[name = tensor("input_1781_cast_fp16")]; + tensor output_239_axes_0 = const()[name = tensor("output_239_axes_0"), val = tensor([-1])]; + tensor const_362_to_fp16 = const()[name = tensor("const_362_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(372865856)))]; + tensor const_363_to_fp16 = const()[name = tensor("const_363_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(372866944)))]; + tensor output_239_cast_fp16 = layer_norm(axes = output_239_axes_0, beta = const_363_to_fp16, epsilon = var_46_to_fp16, gamma = const_362_to_fp16, x = input_1781_cast_fp16)[name = tensor("output_239_cast_fp16")]; + tensor encoder_tp_encoders_9_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_9_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(372868032)))]; + tensor encoder_tp_encoders_9_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_9_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(374440960)))]; + tensor linear_236_cast_fp16 = linear(bias = encoder_tp_encoders_9_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_9_self_attn_linear_q_k_v_weight_to_fp16, x = output_239_cast_fp16)[name = tensor("linear_236_cast_fp16")]; + tensor tile_59 = const()[name = tensor("tile_59"), val = tensor([512, 512, 512])]; + tensor var_6309_axis_0 = const()[name = tensor("op_6309_axis_0"), val = tensor(-1)]; + tensor var_6309_cast_fp16_0, tensor var_6309_cast_fp16_1, tensor var_6309_cast_fp16_2 = split(axis = var_6309_axis_0, split_sizes = tile_59, x = linear_236_cast_fp16)[name = tensor("op_6309_cast_fp16")]; + tensor concat_177x = const()[name = tensor("concat_177x"), val = tensor([1, -1, 4, 128])]; + tensor var_6314_cast_fp16 = reshape(shape = concat_177x, x = var_6309_cast_fp16_0)[name = tensor("op_6314_cast_fp16")]; + tensor concat_178x = const()[name = tensor("concat_178x"), val = tensor([1, -1, 4, 128])]; + tensor var_6317_cast_fp16 = reshape(shape = concat_178x, x = var_6309_cast_fp16_1)[name = tensor("op_6317_cast_fp16")]; + tensor concat_179x = const()[name = tensor("concat_179x"), val = tensor([1, -1, 4, 128])]; + tensor var_6320_cast_fp16 = reshape(shape = concat_179x, x = var_6309_cast_fp16_2)[name = tensor("op_6320_cast_fp16")]; + tensor value_119_perm_0 = const()[name = tensor("value_119_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_119_cast_fp16 = mul(x = var_6309_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_119_cast_fp16")]; + tensor input_1785_perm_0 = const()[name = tensor("input_1785_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1787_pad_0 = const()[name = tensor("input_1787_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1787_mode_0 = const()[name = tensor("input_1787_mode_0"), val = tensor("constant")]; + tensor const_365_to_fp16 = const()[name = tensor("const_365_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1785_cast_fp16 = transpose(perm = input_1785_perm_0, x = inputs_119_cast_fp16)[name = tensor("transpose_414")]; + tensor input_1787_cast_fp16 = pad(constant_val = const_365_to_fp16, mode = input_1787_mode_0, pad = input_1787_pad_0, x = input_1785_cast_fp16)[name = tensor("input_1787_cast_fp16")]; + tensor x_595_pad_type_0 = const()[name = tensor("x_595_pad_type_0"), val = tensor("valid")]; + tensor x_595_groups_0 = const()[name = tensor("x_595_groups_0"), val = tensor(512)]; + tensor x_595_strides_0 = const()[name = tensor("x_595_strides_0"), val = tensor([1])]; + tensor x_595_pad_0 = const()[name = tensor("x_595_pad_0"), val = tensor([0, 0])]; + tensor x_595_dilations_0 = const()[name = tensor("x_595_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_9_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_9_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(374444096)))]; + tensor x_595_cast_fp16 = conv(dilations = x_595_dilations_0, groups = x_595_groups_0, pad = x_595_pad_0, pad_type = x_595_pad_type_0, strides = x_595_strides_0, weight = encoder_tp_encoders_9_self_attn_fsmn_block_weight_to_fp16, x = input_1787_cast_fp16)[name = tensor("x_595_cast_fp16")]; + tensor x_597_perm_0 = const()[name = tensor("x_597_perm_0"), val = tensor([0, 2, 1])]; + tensor x_597_cast_fp16 = transpose(perm = x_597_perm_0, x = x_595_cast_fp16)[name = tensor("transpose_413")]; + tensor input_1789_cast_fp16 = add(x = x_597_cast_fp16, y = inputs_119_cast_fp16)[name = tensor("input_1789_cast_fp16")]; + tensor fsmn_memory_119_cast_fp16 = mul(x = input_1789_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_119_cast_fp16")]; + tensor var_6339_to_fp16 = const()[name = tensor("op_6339_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_239_cast_fp16 = mul(x = var_6314_cast_fp16, y = var_6339_to_fp16)[name = tensor("q_h_239_cast_fp16")]; + tensor scores_237_transpose_x_0 = const()[name = tensor("scores_237_transpose_x_0"), val = tensor(false)]; + tensor scores_237_transpose_y_0 = const()[name = tensor("scores_237_transpose_y_0"), val = tensor(false)]; + tensor transpose_328_perm_0 = const()[name = tensor("transpose_328_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_329_perm_0 = const()[name = tensor("transpose_329_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_329 = transpose(perm = transpose_329_perm_0, x = var_6317_cast_fp16)[name = tensor("transpose_411")]; + tensor transpose_328 = transpose(perm = transpose_328_perm_0, x = q_h_239_cast_fp16)[name = tensor("transpose_412")]; + tensor scores_237_cast_fp16 = matmul(transpose_x = scores_237_transpose_x_0, transpose_y = scores_237_transpose_y_0, x = transpose_328, y = transpose_329)[name = tensor("scores_237_cast_fp16")]; + tensor scores_239_cast_fp16 = select(a = var_48_to_fp16, b = scores_237_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_239_cast_fp16")]; + tensor var_6347_cast_fp16 = softmax(axis = var_61, x = scores_239_cast_fp16)[name = tensor("op_6347_cast_fp16")]; + tensor input_1791_cast_fp16 = select(a = var_53_to_fp16, b = var_6347_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1791_cast_fp16")]; + tensor x_601_transpose_x_0 = const()[name = tensor("x_601_transpose_x_0"), val = tensor(false)]; + tensor x_601_transpose_y_0 = const()[name = tensor("x_601_transpose_y_0"), val = tensor(false)]; + tensor value_119_cast_fp16 = transpose(perm = value_119_perm_0, x = var_6320_cast_fp16)[name = tensor("transpose_415")]; + tensor x_601_cast_fp16 = matmul(transpose_x = x_601_transpose_x_0, transpose_y = x_601_transpose_y_0, x = input_1791_cast_fp16, y = value_119_cast_fp16)[name = tensor("x_601_cast_fp16")]; + tensor var_6351_perm_0 = const()[name = tensor("op_6351_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_6353 = const()[name = tensor("op_6353"), val = tensor([1, -1, 512])]; + tensor var_6351_cast_fp16 = transpose(perm = var_6351_perm_0, x = x_601_cast_fp16)[name = tensor("transpose_410")]; + tensor input_1793_cast_fp16 = reshape(shape = var_6353, x = var_6351_cast_fp16)[name = tensor("input_1793_cast_fp16")]; + tensor encoder_tp_encoders_9_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_9_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(374455424)))]; + tensor encoder_tp_encoders_9_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_9_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(374979776)))]; + tensor linear_237_cast_fp16 = linear(bias = encoder_tp_encoders_9_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_9_self_attn_linear_out_weight_to_fp16, x = input_1793_cast_fp16)[name = tensor("linear_237_cast_fp16")]; + tensor input_1795_cast_fp16 = add(x = linear_237_cast_fp16, y = fsmn_memory_119_cast_fp16)[name = tensor("input_1795_cast_fp16")]; + tensor input_1797_cast_fp16 = add(x = input_1781_cast_fp16, y = input_1795_cast_fp16)[name = tensor("input_1797_cast_fp16")]; + tensor output_241_axes_0 = const()[name = tensor("output_241_axes_0"), val = tensor([-1])]; + tensor const_366_to_fp16 = const()[name = tensor("const_366_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(374980864)))]; + tensor const_367_to_fp16 = const()[name = tensor("const_367_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(374981952)))]; + tensor output_241_cast_fp16 = layer_norm(axes = output_241_axes_0, beta = const_367_to_fp16, epsilon = var_46_to_fp16, gamma = const_366_to_fp16, x = input_1797_cast_fp16)[name = tensor("output_241_cast_fp16")]; + tensor encoder_tp_encoders_9_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_9_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(374983040)))]; + tensor encoder_tp_encoders_9_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_9_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(377080256)))]; + tensor linear_238_cast_fp16 = linear(bias = encoder_tp_encoders_9_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_9_feed_forward_w_1_weight_to_fp16, x = output_241_cast_fp16)[name = tensor("linear_238_cast_fp16")]; + tensor input_1805_cast_fp16 = relu(x = linear_238_cast_fp16)[name = tensor("input_1805_cast_fp16")]; + tensor encoder_tp_encoders_9_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_9_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(377084416)))]; + tensor encoder_tp_encoders_9_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_9_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(379181632)))]; + tensor linear_239_cast_fp16 = linear(bias = encoder_tp_encoders_9_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_9_feed_forward_w_2_weight_to_fp16, x = input_1805_cast_fp16)[name = tensor("linear_239_cast_fp16")]; + tensor input_1811_cast_fp16 = add(x = input_1797_cast_fp16, y = linear_239_cast_fp16)[name = tensor("input_1811_cast_fp16")]; + tensor output_243_axes_0 = const()[name = tensor("output_243_axes_0"), val = tensor([-1])]; + tensor const_368_to_fp16 = const()[name = tensor("const_368_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(379182720)))]; + tensor const_369_to_fp16 = const()[name = tensor("const_369_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(379183808)))]; + tensor output_243_cast_fp16 = layer_norm(axes = output_243_axes_0, beta = const_369_to_fp16, epsilon = var_46_to_fp16, gamma = const_368_to_fp16, x = input_1811_cast_fp16)[name = tensor("output_243_cast_fp16")]; + tensor encoder_tp_encoders_10_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_10_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(379184896)))]; + tensor encoder_tp_encoders_10_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_10_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(380757824)))]; + tensor linear_240_cast_fp16 = linear(bias = encoder_tp_encoders_10_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_10_self_attn_linear_q_k_v_weight_to_fp16, x = output_243_cast_fp16)[name = tensor("linear_240_cast_fp16")]; + tensor tile_60 = const()[name = tensor("tile_60"), val = tensor([512, 512, 512])]; + tensor var_6411_axis_0 = const()[name = tensor("op_6411_axis_0"), val = tensor(-1)]; + tensor var_6411_cast_fp16_0, tensor var_6411_cast_fp16_1, tensor var_6411_cast_fp16_2 = split(axis = var_6411_axis_0, split_sizes = tile_60, x = linear_240_cast_fp16)[name = tensor("op_6411_cast_fp16")]; + tensor concat_180x = const()[name = tensor("concat_180x"), val = tensor([1, -1, 4, 128])]; + tensor var_6416_cast_fp16 = reshape(shape = concat_180x, x = var_6411_cast_fp16_0)[name = tensor("op_6416_cast_fp16")]; + tensor concat_181x = const()[name = tensor("concat_181x"), val = tensor([1, -1, 4, 128])]; + tensor var_6419_cast_fp16 = reshape(shape = concat_181x, x = var_6411_cast_fp16_1)[name = tensor("op_6419_cast_fp16")]; + tensor concat_182x = const()[name = tensor("concat_182x"), val = tensor([1, -1, 4, 128])]; + tensor var_6422_cast_fp16 = reshape(shape = concat_182x, x = var_6411_cast_fp16_2)[name = tensor("op_6422_cast_fp16")]; + tensor value_121_perm_0 = const()[name = tensor("value_121_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_121_cast_fp16 = mul(x = var_6411_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_121_cast_fp16")]; + tensor input_1815_perm_0 = const()[name = tensor("input_1815_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1817_pad_0 = const()[name = tensor("input_1817_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1817_mode_0 = const()[name = tensor("input_1817_mode_0"), val = tensor("constant")]; + tensor const_371_to_fp16 = const()[name = tensor("const_371_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1815_cast_fp16 = transpose(perm = input_1815_perm_0, x = inputs_121_cast_fp16)[name = tensor("transpose_408")]; + tensor input_1817_cast_fp16 = pad(constant_val = const_371_to_fp16, mode = input_1817_mode_0, pad = input_1817_pad_0, x = input_1815_cast_fp16)[name = tensor("input_1817_cast_fp16")]; + tensor x_605_pad_type_0 = const()[name = tensor("x_605_pad_type_0"), val = tensor("valid")]; + tensor x_605_groups_0 = const()[name = tensor("x_605_groups_0"), val = tensor(512)]; + tensor x_605_strides_0 = const()[name = tensor("x_605_strides_0"), val = tensor([1])]; + tensor x_605_pad_0 = const()[name = tensor("x_605_pad_0"), val = tensor([0, 0])]; + tensor x_605_dilations_0 = const()[name = tensor("x_605_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_10_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_10_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(380760960)))]; + tensor x_605_cast_fp16 = conv(dilations = x_605_dilations_0, groups = x_605_groups_0, pad = x_605_pad_0, pad_type = x_605_pad_type_0, strides = x_605_strides_0, weight = encoder_tp_encoders_10_self_attn_fsmn_block_weight_to_fp16, x = input_1817_cast_fp16)[name = tensor("x_605_cast_fp16")]; + tensor x_607_perm_0 = const()[name = tensor("x_607_perm_0"), val = tensor([0, 2, 1])]; + tensor x_607_cast_fp16 = transpose(perm = x_607_perm_0, x = x_605_cast_fp16)[name = tensor("transpose_407")]; + tensor input_1819_cast_fp16 = add(x = x_607_cast_fp16, y = inputs_121_cast_fp16)[name = tensor("input_1819_cast_fp16")]; + tensor fsmn_memory_121_cast_fp16 = mul(x = input_1819_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_121_cast_fp16")]; + tensor var_6441_to_fp16 = const()[name = tensor("op_6441_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_243_cast_fp16 = mul(x = var_6416_cast_fp16, y = var_6441_to_fp16)[name = tensor("q_h_243_cast_fp16")]; + tensor scores_241_transpose_x_0 = const()[name = tensor("scores_241_transpose_x_0"), val = tensor(false)]; + tensor scores_241_transpose_y_0 = const()[name = tensor("scores_241_transpose_y_0"), val = tensor(false)]; + tensor transpose_330_perm_0 = const()[name = tensor("transpose_330_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_331_perm_0 = const()[name = tensor("transpose_331_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_331 = transpose(perm = transpose_331_perm_0, x = var_6419_cast_fp16)[name = tensor("transpose_405")]; + tensor transpose_330 = transpose(perm = transpose_330_perm_0, x = q_h_243_cast_fp16)[name = tensor("transpose_406")]; + tensor scores_241_cast_fp16 = matmul(transpose_x = scores_241_transpose_x_0, transpose_y = scores_241_transpose_y_0, x = transpose_330, y = transpose_331)[name = tensor("scores_241_cast_fp16")]; + tensor scores_243_cast_fp16 = select(a = var_48_to_fp16, b = scores_241_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_243_cast_fp16")]; + tensor var_6449_cast_fp16 = softmax(axis = var_61, x = scores_243_cast_fp16)[name = tensor("op_6449_cast_fp16")]; + tensor input_1821_cast_fp16 = select(a = var_53_to_fp16, b = var_6449_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1821_cast_fp16")]; + tensor x_611_transpose_x_0 = const()[name = tensor("x_611_transpose_x_0"), val = tensor(false)]; + tensor x_611_transpose_y_0 = const()[name = tensor("x_611_transpose_y_0"), val = tensor(false)]; + tensor value_121_cast_fp16 = transpose(perm = value_121_perm_0, x = var_6422_cast_fp16)[name = tensor("transpose_409")]; + tensor x_611_cast_fp16 = matmul(transpose_x = x_611_transpose_x_0, transpose_y = x_611_transpose_y_0, x = input_1821_cast_fp16, y = value_121_cast_fp16)[name = tensor("x_611_cast_fp16")]; + tensor var_6453_perm_0 = const()[name = tensor("op_6453_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_6455 = const()[name = tensor("op_6455"), val = tensor([1, -1, 512])]; + tensor var_6453_cast_fp16 = transpose(perm = var_6453_perm_0, x = x_611_cast_fp16)[name = tensor("transpose_404")]; + tensor input_1823_cast_fp16 = reshape(shape = var_6455, x = var_6453_cast_fp16)[name = tensor("input_1823_cast_fp16")]; + tensor encoder_tp_encoders_10_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_10_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(380772288)))]; + tensor encoder_tp_encoders_10_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_10_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(381296640)))]; + tensor linear_241_cast_fp16 = linear(bias = encoder_tp_encoders_10_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_10_self_attn_linear_out_weight_to_fp16, x = input_1823_cast_fp16)[name = tensor("linear_241_cast_fp16")]; + tensor input_1825_cast_fp16 = add(x = linear_241_cast_fp16, y = fsmn_memory_121_cast_fp16)[name = tensor("input_1825_cast_fp16")]; + tensor input_1827_cast_fp16 = add(x = input_1811_cast_fp16, y = input_1825_cast_fp16)[name = tensor("input_1827_cast_fp16")]; + tensor output_245_axes_0 = const()[name = tensor("output_245_axes_0"), val = tensor([-1])]; + tensor const_372_to_fp16 = const()[name = tensor("const_372_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(381297728)))]; + tensor const_373_to_fp16 = const()[name = tensor("const_373_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(381298816)))]; + tensor output_245_cast_fp16 = layer_norm(axes = output_245_axes_0, beta = const_373_to_fp16, epsilon = var_46_to_fp16, gamma = const_372_to_fp16, x = input_1827_cast_fp16)[name = tensor("output_245_cast_fp16")]; + tensor encoder_tp_encoders_10_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_10_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(381299904)))]; + tensor encoder_tp_encoders_10_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_10_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(383397120)))]; + tensor linear_242_cast_fp16 = linear(bias = encoder_tp_encoders_10_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_10_feed_forward_w_1_weight_to_fp16, x = output_245_cast_fp16)[name = tensor("linear_242_cast_fp16")]; + tensor input_1835_cast_fp16 = relu(x = linear_242_cast_fp16)[name = tensor("input_1835_cast_fp16")]; + tensor encoder_tp_encoders_10_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_10_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(383401280)))]; + tensor encoder_tp_encoders_10_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_10_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(385498496)))]; + tensor linear_243_cast_fp16 = linear(bias = encoder_tp_encoders_10_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_10_feed_forward_w_2_weight_to_fp16, x = input_1835_cast_fp16)[name = tensor("linear_243_cast_fp16")]; + tensor input_1841_cast_fp16 = add(x = input_1827_cast_fp16, y = linear_243_cast_fp16)[name = tensor("input_1841_cast_fp16")]; + tensor output_247_axes_0 = const()[name = tensor("output_247_axes_0"), val = tensor([-1])]; + tensor const_374_to_fp16 = const()[name = tensor("const_374_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(385499584)))]; + tensor const_375_to_fp16 = const()[name = tensor("const_375_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(385500672)))]; + tensor output_247_cast_fp16 = layer_norm(axes = output_247_axes_0, beta = const_375_to_fp16, epsilon = var_46_to_fp16, gamma = const_374_to_fp16, x = input_1841_cast_fp16)[name = tensor("output_247_cast_fp16")]; + tensor encoder_tp_encoders_11_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_11_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(385501760)))]; + tensor encoder_tp_encoders_11_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_11_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387074688)))]; + tensor linear_244_cast_fp16 = linear(bias = encoder_tp_encoders_11_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_11_self_attn_linear_q_k_v_weight_to_fp16, x = output_247_cast_fp16)[name = tensor("linear_244_cast_fp16")]; + tensor tile_61 = const()[name = tensor("tile_61"), val = tensor([512, 512, 512])]; + tensor var_6513_axis_0 = const()[name = tensor("op_6513_axis_0"), val = tensor(-1)]; + tensor var_6513_cast_fp16_0, tensor var_6513_cast_fp16_1, tensor var_6513_cast_fp16_2 = split(axis = var_6513_axis_0, split_sizes = tile_61, x = linear_244_cast_fp16)[name = tensor("op_6513_cast_fp16")]; + tensor concat_183x = const()[name = tensor("concat_183x"), val = tensor([1, -1, 4, 128])]; + tensor var_6518_cast_fp16 = reshape(shape = concat_183x, x = var_6513_cast_fp16_0)[name = tensor("op_6518_cast_fp16")]; + tensor concat_184x = const()[name = tensor("concat_184x"), val = tensor([1, -1, 4, 128])]; + tensor var_6521_cast_fp16 = reshape(shape = concat_184x, x = var_6513_cast_fp16_1)[name = tensor("op_6521_cast_fp16")]; + tensor concat_185x = const()[name = tensor("concat_185x"), val = tensor([1, -1, 4, 128])]; + tensor var_6524_cast_fp16 = reshape(shape = concat_185x, x = var_6513_cast_fp16_2)[name = tensor("op_6524_cast_fp16")]; + tensor value_123_perm_0 = const()[name = tensor("value_123_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_123_cast_fp16 = mul(x = var_6513_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_123_cast_fp16")]; + tensor input_1845_perm_0 = const()[name = tensor("input_1845_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1847_pad_0 = const()[name = tensor("input_1847_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1847_mode_0 = const()[name = tensor("input_1847_mode_0"), val = tensor("constant")]; + tensor const_377_to_fp16 = const()[name = tensor("const_377_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1845_cast_fp16 = transpose(perm = input_1845_perm_0, x = inputs_123_cast_fp16)[name = tensor("transpose_402")]; + tensor input_1847_cast_fp16 = pad(constant_val = const_377_to_fp16, mode = input_1847_mode_0, pad = input_1847_pad_0, x = input_1845_cast_fp16)[name = tensor("input_1847_cast_fp16")]; + tensor x_615_pad_type_0 = const()[name = tensor("x_615_pad_type_0"), val = tensor("valid")]; + tensor x_615_groups_0 = const()[name = tensor("x_615_groups_0"), val = tensor(512)]; + tensor x_615_strides_0 = const()[name = tensor("x_615_strides_0"), val = tensor([1])]; + tensor x_615_pad_0 = const()[name = tensor("x_615_pad_0"), val = tensor([0, 0])]; + tensor x_615_dilations_0 = const()[name = tensor("x_615_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_11_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_11_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387077824)))]; + tensor x_615_cast_fp16 = conv(dilations = x_615_dilations_0, groups = x_615_groups_0, pad = x_615_pad_0, pad_type = x_615_pad_type_0, strides = x_615_strides_0, weight = encoder_tp_encoders_11_self_attn_fsmn_block_weight_to_fp16, x = input_1847_cast_fp16)[name = tensor("x_615_cast_fp16")]; + tensor x_617_perm_0 = const()[name = tensor("x_617_perm_0"), val = tensor([0, 2, 1])]; + tensor x_617_cast_fp16 = transpose(perm = x_617_perm_0, x = x_615_cast_fp16)[name = tensor("transpose_401")]; + tensor input_1849_cast_fp16 = add(x = x_617_cast_fp16, y = inputs_123_cast_fp16)[name = tensor("input_1849_cast_fp16")]; + tensor fsmn_memory_123_cast_fp16 = mul(x = input_1849_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_123_cast_fp16")]; + tensor var_6543_to_fp16 = const()[name = tensor("op_6543_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_247_cast_fp16 = mul(x = var_6518_cast_fp16, y = var_6543_to_fp16)[name = tensor("q_h_247_cast_fp16")]; + tensor scores_245_transpose_x_0 = const()[name = tensor("scores_245_transpose_x_0"), val = tensor(false)]; + tensor scores_245_transpose_y_0 = const()[name = tensor("scores_245_transpose_y_0"), val = tensor(false)]; + tensor transpose_332_perm_0 = const()[name = tensor("transpose_332_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_333_perm_0 = const()[name = tensor("transpose_333_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_333 = transpose(perm = transpose_333_perm_0, x = var_6521_cast_fp16)[name = tensor("transpose_399")]; + tensor transpose_332 = transpose(perm = transpose_332_perm_0, x = q_h_247_cast_fp16)[name = tensor("transpose_400")]; + tensor scores_245_cast_fp16 = matmul(transpose_x = scores_245_transpose_x_0, transpose_y = scores_245_transpose_y_0, x = transpose_332, y = transpose_333)[name = tensor("scores_245_cast_fp16")]; + tensor scores_247_cast_fp16 = select(a = var_48_to_fp16, b = scores_245_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_247_cast_fp16")]; + tensor var_6551_cast_fp16 = softmax(axis = var_61, x = scores_247_cast_fp16)[name = tensor("op_6551_cast_fp16")]; + tensor input_1851_cast_fp16 = select(a = var_53_to_fp16, b = var_6551_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1851_cast_fp16")]; + tensor x_621_transpose_x_0 = const()[name = tensor("x_621_transpose_x_0"), val = tensor(false)]; + tensor x_621_transpose_y_0 = const()[name = tensor("x_621_transpose_y_0"), val = tensor(false)]; + tensor value_123_cast_fp16 = transpose(perm = value_123_perm_0, x = var_6524_cast_fp16)[name = tensor("transpose_403")]; + tensor x_621_cast_fp16 = matmul(transpose_x = x_621_transpose_x_0, transpose_y = x_621_transpose_y_0, x = input_1851_cast_fp16, y = value_123_cast_fp16)[name = tensor("x_621_cast_fp16")]; + tensor var_6555_perm_0 = const()[name = tensor("op_6555_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_6557 = const()[name = tensor("op_6557"), val = tensor([1, -1, 512])]; + tensor var_6555_cast_fp16 = transpose(perm = var_6555_perm_0, x = x_621_cast_fp16)[name = tensor("transpose_398")]; + tensor input_1853_cast_fp16 = reshape(shape = var_6557, x = var_6555_cast_fp16)[name = tensor("input_1853_cast_fp16")]; + tensor encoder_tp_encoders_11_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_11_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387089152)))]; + tensor encoder_tp_encoders_11_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_11_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387613504)))]; + tensor linear_245_cast_fp16 = linear(bias = encoder_tp_encoders_11_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_11_self_attn_linear_out_weight_to_fp16, x = input_1853_cast_fp16)[name = tensor("linear_245_cast_fp16")]; + tensor input_1855_cast_fp16 = add(x = linear_245_cast_fp16, y = fsmn_memory_123_cast_fp16)[name = tensor("input_1855_cast_fp16")]; + tensor input_1857_cast_fp16 = add(x = input_1841_cast_fp16, y = input_1855_cast_fp16)[name = tensor("input_1857_cast_fp16")]; + tensor output_249_axes_0 = const()[name = tensor("output_249_axes_0"), val = tensor([-1])]; + tensor const_378_to_fp16 = const()[name = tensor("const_378_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387614592)))]; + tensor const_379_to_fp16 = const()[name = tensor("const_379_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387615680)))]; + tensor output_249_cast_fp16 = layer_norm(axes = output_249_axes_0, beta = const_379_to_fp16, epsilon = var_46_to_fp16, gamma = const_378_to_fp16, x = input_1857_cast_fp16)[name = tensor("output_249_cast_fp16")]; + tensor encoder_tp_encoders_11_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_11_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(387616768)))]; + tensor encoder_tp_encoders_11_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_11_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(389713984)))]; + tensor linear_246_cast_fp16 = linear(bias = encoder_tp_encoders_11_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_11_feed_forward_w_1_weight_to_fp16, x = output_249_cast_fp16)[name = tensor("linear_246_cast_fp16")]; + tensor input_1865_cast_fp16 = relu(x = linear_246_cast_fp16)[name = tensor("input_1865_cast_fp16")]; + tensor encoder_tp_encoders_11_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_11_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(389718144)))]; + tensor encoder_tp_encoders_11_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_11_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(391815360)))]; + tensor linear_247_cast_fp16 = linear(bias = encoder_tp_encoders_11_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_11_feed_forward_w_2_weight_to_fp16, x = input_1865_cast_fp16)[name = tensor("linear_247_cast_fp16")]; + tensor input_1871_cast_fp16 = add(x = input_1857_cast_fp16, y = linear_247_cast_fp16)[name = tensor("input_1871_cast_fp16")]; + tensor output_251_axes_0 = const()[name = tensor("output_251_axes_0"), val = tensor([-1])]; + tensor const_380_to_fp16 = const()[name = tensor("const_380_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(391816448)))]; + tensor const_381_to_fp16 = const()[name = tensor("const_381_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(391817536)))]; + tensor output_251_cast_fp16 = layer_norm(axes = output_251_axes_0, beta = const_381_to_fp16, epsilon = var_46_to_fp16, gamma = const_380_to_fp16, x = input_1871_cast_fp16)[name = tensor("output_251_cast_fp16")]; + tensor encoder_tp_encoders_12_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_12_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(391818624)))]; + tensor encoder_tp_encoders_12_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_12_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(393391552)))]; + tensor linear_248_cast_fp16 = linear(bias = encoder_tp_encoders_12_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_12_self_attn_linear_q_k_v_weight_to_fp16, x = output_251_cast_fp16)[name = tensor("linear_248_cast_fp16")]; + tensor tile_62 = const()[name = tensor("tile_62"), val = tensor([512, 512, 512])]; + tensor var_6615_axis_0 = const()[name = tensor("op_6615_axis_0"), val = tensor(-1)]; + tensor var_6615_cast_fp16_0, tensor var_6615_cast_fp16_1, tensor var_6615_cast_fp16_2 = split(axis = var_6615_axis_0, split_sizes = tile_62, x = linear_248_cast_fp16)[name = tensor("op_6615_cast_fp16")]; + tensor concat_186x = const()[name = tensor("concat_186x"), val = tensor([1, -1, 4, 128])]; + tensor var_6620_cast_fp16 = reshape(shape = concat_186x, x = var_6615_cast_fp16_0)[name = tensor("op_6620_cast_fp16")]; + tensor concat_187x = const()[name = tensor("concat_187x"), val = tensor([1, -1, 4, 128])]; + tensor var_6623_cast_fp16 = reshape(shape = concat_187x, x = var_6615_cast_fp16_1)[name = tensor("op_6623_cast_fp16")]; + tensor concat_188x = const()[name = tensor("concat_188x"), val = tensor([1, -1, 4, 128])]; + tensor var_6626_cast_fp16 = reshape(shape = concat_188x, x = var_6615_cast_fp16_2)[name = tensor("op_6626_cast_fp16")]; + tensor value_125_perm_0 = const()[name = tensor("value_125_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_125_cast_fp16 = mul(x = var_6615_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_125_cast_fp16")]; + tensor input_1875_perm_0 = const()[name = tensor("input_1875_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1877_pad_0 = const()[name = tensor("input_1877_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1877_mode_0 = const()[name = tensor("input_1877_mode_0"), val = tensor("constant")]; + tensor const_383_to_fp16 = const()[name = tensor("const_383_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1875_cast_fp16 = transpose(perm = input_1875_perm_0, x = inputs_125_cast_fp16)[name = tensor("transpose_396")]; + tensor input_1877_cast_fp16 = pad(constant_val = const_383_to_fp16, mode = input_1877_mode_0, pad = input_1877_pad_0, x = input_1875_cast_fp16)[name = tensor("input_1877_cast_fp16")]; + tensor x_625_pad_type_0 = const()[name = tensor("x_625_pad_type_0"), val = tensor("valid")]; + tensor x_625_groups_0 = const()[name = tensor("x_625_groups_0"), val = tensor(512)]; + tensor x_625_strides_0 = const()[name = tensor("x_625_strides_0"), val = tensor([1])]; + tensor x_625_pad_0 = const()[name = tensor("x_625_pad_0"), val = tensor([0, 0])]; + tensor x_625_dilations_0 = const()[name = tensor("x_625_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_12_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_12_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(393394688)))]; + tensor x_625_cast_fp16 = conv(dilations = x_625_dilations_0, groups = x_625_groups_0, pad = x_625_pad_0, pad_type = x_625_pad_type_0, strides = x_625_strides_0, weight = encoder_tp_encoders_12_self_attn_fsmn_block_weight_to_fp16, x = input_1877_cast_fp16)[name = tensor("x_625_cast_fp16")]; + tensor x_627_perm_0 = const()[name = tensor("x_627_perm_0"), val = tensor([0, 2, 1])]; + tensor x_627_cast_fp16 = transpose(perm = x_627_perm_0, x = x_625_cast_fp16)[name = tensor("transpose_395")]; + tensor input_1879_cast_fp16 = add(x = x_627_cast_fp16, y = inputs_125_cast_fp16)[name = tensor("input_1879_cast_fp16")]; + tensor fsmn_memory_125_cast_fp16 = mul(x = input_1879_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_125_cast_fp16")]; + tensor var_6645_to_fp16 = const()[name = tensor("op_6645_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_251_cast_fp16 = mul(x = var_6620_cast_fp16, y = var_6645_to_fp16)[name = tensor("q_h_251_cast_fp16")]; + tensor scores_249_transpose_x_0 = const()[name = tensor("scores_249_transpose_x_0"), val = tensor(false)]; + tensor scores_249_transpose_y_0 = const()[name = tensor("scores_249_transpose_y_0"), val = tensor(false)]; + tensor transpose_334_perm_0 = const()[name = tensor("transpose_334_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_335_perm_0 = const()[name = tensor("transpose_335_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_335 = transpose(perm = transpose_335_perm_0, x = var_6623_cast_fp16)[name = tensor("transpose_393")]; + tensor transpose_334 = transpose(perm = transpose_334_perm_0, x = q_h_251_cast_fp16)[name = tensor("transpose_394")]; + tensor scores_249_cast_fp16 = matmul(transpose_x = scores_249_transpose_x_0, transpose_y = scores_249_transpose_y_0, x = transpose_334, y = transpose_335)[name = tensor("scores_249_cast_fp16")]; + tensor scores_251_cast_fp16 = select(a = var_48_to_fp16, b = scores_249_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_251_cast_fp16")]; + tensor var_6653_cast_fp16 = softmax(axis = var_61, x = scores_251_cast_fp16)[name = tensor("op_6653_cast_fp16")]; + tensor input_1881_cast_fp16 = select(a = var_53_to_fp16, b = var_6653_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1881_cast_fp16")]; + tensor x_631_transpose_x_0 = const()[name = tensor("x_631_transpose_x_0"), val = tensor(false)]; + tensor x_631_transpose_y_0 = const()[name = tensor("x_631_transpose_y_0"), val = tensor(false)]; + tensor value_125_cast_fp16 = transpose(perm = value_125_perm_0, x = var_6626_cast_fp16)[name = tensor("transpose_397")]; + tensor x_631_cast_fp16 = matmul(transpose_x = x_631_transpose_x_0, transpose_y = x_631_transpose_y_0, x = input_1881_cast_fp16, y = value_125_cast_fp16)[name = tensor("x_631_cast_fp16")]; + tensor var_6657_perm_0 = const()[name = tensor("op_6657_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_6659 = const()[name = tensor("op_6659"), val = tensor([1, -1, 512])]; + tensor var_6657_cast_fp16 = transpose(perm = var_6657_perm_0, x = x_631_cast_fp16)[name = tensor("transpose_392")]; + tensor input_1883_cast_fp16 = reshape(shape = var_6659, x = var_6657_cast_fp16)[name = tensor("input_1883_cast_fp16")]; + tensor encoder_tp_encoders_12_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_12_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(393406016)))]; + tensor encoder_tp_encoders_12_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_12_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(393930368)))]; + tensor linear_249_cast_fp16 = linear(bias = encoder_tp_encoders_12_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_12_self_attn_linear_out_weight_to_fp16, x = input_1883_cast_fp16)[name = tensor("linear_249_cast_fp16")]; + tensor input_1885_cast_fp16 = add(x = linear_249_cast_fp16, y = fsmn_memory_125_cast_fp16)[name = tensor("input_1885_cast_fp16")]; + tensor input_1887_cast_fp16 = add(x = input_1871_cast_fp16, y = input_1885_cast_fp16)[name = tensor("input_1887_cast_fp16")]; + tensor output_253_axes_0 = const()[name = tensor("output_253_axes_0"), val = tensor([-1])]; + tensor const_384_to_fp16 = const()[name = tensor("const_384_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(393931456)))]; + tensor const_385_to_fp16 = const()[name = tensor("const_385_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(393932544)))]; + tensor output_253_cast_fp16 = layer_norm(axes = output_253_axes_0, beta = const_385_to_fp16, epsilon = var_46_to_fp16, gamma = const_384_to_fp16, x = input_1887_cast_fp16)[name = tensor("output_253_cast_fp16")]; + tensor encoder_tp_encoders_12_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_12_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(393933632)))]; + tensor encoder_tp_encoders_12_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_12_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(396030848)))]; + tensor linear_250_cast_fp16 = linear(bias = encoder_tp_encoders_12_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_12_feed_forward_w_1_weight_to_fp16, x = output_253_cast_fp16)[name = tensor("linear_250_cast_fp16")]; + tensor input_1895_cast_fp16 = relu(x = linear_250_cast_fp16)[name = tensor("input_1895_cast_fp16")]; + tensor encoder_tp_encoders_12_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_12_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(396035008)))]; + tensor encoder_tp_encoders_12_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_12_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(398132224)))]; + tensor linear_251_cast_fp16 = linear(bias = encoder_tp_encoders_12_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_12_feed_forward_w_2_weight_to_fp16, x = input_1895_cast_fp16)[name = tensor("linear_251_cast_fp16")]; + tensor input_1901_cast_fp16 = add(x = input_1887_cast_fp16, y = linear_251_cast_fp16)[name = tensor("input_1901_cast_fp16")]; + tensor output_255_axes_0 = const()[name = tensor("output_255_axes_0"), val = tensor([-1])]; + tensor const_386_to_fp16 = const()[name = tensor("const_386_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(398133312)))]; + tensor const_387_to_fp16 = const()[name = tensor("const_387_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(398134400)))]; + tensor output_255_cast_fp16 = layer_norm(axes = output_255_axes_0, beta = const_387_to_fp16, epsilon = var_46_to_fp16, gamma = const_386_to_fp16, x = input_1901_cast_fp16)[name = tensor("output_255_cast_fp16")]; + tensor encoder_tp_encoders_13_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_13_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(398135488)))]; + tensor encoder_tp_encoders_13_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_13_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(399708416)))]; + tensor linear_252_cast_fp16 = linear(bias = encoder_tp_encoders_13_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_13_self_attn_linear_q_k_v_weight_to_fp16, x = output_255_cast_fp16)[name = tensor("linear_252_cast_fp16")]; + tensor tile_63 = const()[name = tensor("tile_63"), val = tensor([512, 512, 512])]; + tensor var_6717_axis_0 = const()[name = tensor("op_6717_axis_0"), val = tensor(-1)]; + tensor var_6717_cast_fp16_0, tensor var_6717_cast_fp16_1, tensor var_6717_cast_fp16_2 = split(axis = var_6717_axis_0, split_sizes = tile_63, x = linear_252_cast_fp16)[name = tensor("op_6717_cast_fp16")]; + tensor concat_189x = const()[name = tensor("concat_189x"), val = tensor([1, -1, 4, 128])]; + tensor var_6722_cast_fp16 = reshape(shape = concat_189x, x = var_6717_cast_fp16_0)[name = tensor("op_6722_cast_fp16")]; + tensor concat_190x = const()[name = tensor("concat_190x"), val = tensor([1, -1, 4, 128])]; + tensor var_6725_cast_fp16 = reshape(shape = concat_190x, x = var_6717_cast_fp16_1)[name = tensor("op_6725_cast_fp16")]; + tensor concat_191x = const()[name = tensor("concat_191x"), val = tensor([1, -1, 4, 128])]; + tensor var_6728_cast_fp16 = reshape(shape = concat_191x, x = var_6717_cast_fp16_2)[name = tensor("op_6728_cast_fp16")]; + tensor value_127_perm_0 = const()[name = tensor("value_127_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_127_cast_fp16 = mul(x = var_6717_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_127_cast_fp16")]; + tensor input_1905_perm_0 = const()[name = tensor("input_1905_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1907_pad_0 = const()[name = tensor("input_1907_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1907_mode_0 = const()[name = tensor("input_1907_mode_0"), val = tensor("constant")]; + tensor const_389_to_fp16 = const()[name = tensor("const_389_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1905_cast_fp16 = transpose(perm = input_1905_perm_0, x = inputs_127_cast_fp16)[name = tensor("transpose_390")]; + tensor input_1907_cast_fp16 = pad(constant_val = const_389_to_fp16, mode = input_1907_mode_0, pad = input_1907_pad_0, x = input_1905_cast_fp16)[name = tensor("input_1907_cast_fp16")]; + tensor x_635_pad_type_0 = const()[name = tensor("x_635_pad_type_0"), val = tensor("valid")]; + tensor x_635_groups_0 = const()[name = tensor("x_635_groups_0"), val = tensor(512)]; + tensor x_635_strides_0 = const()[name = tensor("x_635_strides_0"), val = tensor([1])]; + tensor x_635_pad_0 = const()[name = tensor("x_635_pad_0"), val = tensor([0, 0])]; + tensor x_635_dilations_0 = const()[name = tensor("x_635_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_13_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_13_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(399711552)))]; + tensor x_635_cast_fp16 = conv(dilations = x_635_dilations_0, groups = x_635_groups_0, pad = x_635_pad_0, pad_type = x_635_pad_type_0, strides = x_635_strides_0, weight = encoder_tp_encoders_13_self_attn_fsmn_block_weight_to_fp16, x = input_1907_cast_fp16)[name = tensor("x_635_cast_fp16")]; + tensor x_637_perm_0 = const()[name = tensor("x_637_perm_0"), val = tensor([0, 2, 1])]; + tensor x_637_cast_fp16 = transpose(perm = x_637_perm_0, x = x_635_cast_fp16)[name = tensor("transpose_389")]; + tensor input_1909_cast_fp16 = add(x = x_637_cast_fp16, y = inputs_127_cast_fp16)[name = tensor("input_1909_cast_fp16")]; + tensor fsmn_memory_127_cast_fp16 = mul(x = input_1909_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_127_cast_fp16")]; + tensor var_6747_to_fp16 = const()[name = tensor("op_6747_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_255_cast_fp16 = mul(x = var_6722_cast_fp16, y = var_6747_to_fp16)[name = tensor("q_h_255_cast_fp16")]; + tensor scores_253_transpose_x_0 = const()[name = tensor("scores_253_transpose_x_0"), val = tensor(false)]; + tensor scores_253_transpose_y_0 = const()[name = tensor("scores_253_transpose_y_0"), val = tensor(false)]; + tensor transpose_336_perm_0 = const()[name = tensor("transpose_336_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_337_perm_0 = const()[name = tensor("transpose_337_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_337 = transpose(perm = transpose_337_perm_0, x = var_6725_cast_fp16)[name = tensor("transpose_387")]; + tensor transpose_336 = transpose(perm = transpose_336_perm_0, x = q_h_255_cast_fp16)[name = tensor("transpose_388")]; + tensor scores_253_cast_fp16 = matmul(transpose_x = scores_253_transpose_x_0, transpose_y = scores_253_transpose_y_0, x = transpose_336, y = transpose_337)[name = tensor("scores_253_cast_fp16")]; + tensor scores_255_cast_fp16 = select(a = var_48_to_fp16, b = scores_253_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_255_cast_fp16")]; + tensor var_6755_cast_fp16 = softmax(axis = var_61, x = scores_255_cast_fp16)[name = tensor("op_6755_cast_fp16")]; + tensor input_1911_cast_fp16 = select(a = var_53_to_fp16, b = var_6755_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1911_cast_fp16")]; + tensor x_641_transpose_x_0 = const()[name = tensor("x_641_transpose_x_0"), val = tensor(false)]; + tensor x_641_transpose_y_0 = const()[name = tensor("x_641_transpose_y_0"), val = tensor(false)]; + tensor value_127_cast_fp16 = transpose(perm = value_127_perm_0, x = var_6728_cast_fp16)[name = tensor("transpose_391")]; + tensor x_641_cast_fp16 = matmul(transpose_x = x_641_transpose_x_0, transpose_y = x_641_transpose_y_0, x = input_1911_cast_fp16, y = value_127_cast_fp16)[name = tensor("x_641_cast_fp16")]; + tensor var_6759_perm_0 = const()[name = tensor("op_6759_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_6761 = const()[name = tensor("op_6761"), val = tensor([1, -1, 512])]; + tensor var_6759_cast_fp16 = transpose(perm = var_6759_perm_0, x = x_641_cast_fp16)[name = tensor("transpose_386")]; + tensor input_1913_cast_fp16 = reshape(shape = var_6761, x = var_6759_cast_fp16)[name = tensor("input_1913_cast_fp16")]; + tensor encoder_tp_encoders_13_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_13_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(399722880)))]; + tensor encoder_tp_encoders_13_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_13_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(400247232)))]; + tensor linear_253_cast_fp16 = linear(bias = encoder_tp_encoders_13_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_13_self_attn_linear_out_weight_to_fp16, x = input_1913_cast_fp16)[name = tensor("linear_253_cast_fp16")]; + tensor input_1915_cast_fp16 = add(x = linear_253_cast_fp16, y = fsmn_memory_127_cast_fp16)[name = tensor("input_1915_cast_fp16")]; + tensor input_1917_cast_fp16 = add(x = input_1901_cast_fp16, y = input_1915_cast_fp16)[name = tensor("input_1917_cast_fp16")]; + tensor output_257_axes_0 = const()[name = tensor("output_257_axes_0"), val = tensor([-1])]; + tensor const_390_to_fp16 = const()[name = tensor("const_390_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(400248320)))]; + tensor const_391_to_fp16 = const()[name = tensor("const_391_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(400249408)))]; + tensor output_257_cast_fp16 = layer_norm(axes = output_257_axes_0, beta = const_391_to_fp16, epsilon = var_46_to_fp16, gamma = const_390_to_fp16, x = input_1917_cast_fp16)[name = tensor("output_257_cast_fp16")]; + tensor encoder_tp_encoders_13_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_13_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(400250496)))]; + tensor encoder_tp_encoders_13_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_13_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(402347712)))]; + tensor linear_254_cast_fp16 = linear(bias = encoder_tp_encoders_13_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_13_feed_forward_w_1_weight_to_fp16, x = output_257_cast_fp16)[name = tensor("linear_254_cast_fp16")]; + tensor input_1925_cast_fp16 = relu(x = linear_254_cast_fp16)[name = tensor("input_1925_cast_fp16")]; + tensor encoder_tp_encoders_13_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_13_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(402351872)))]; + tensor encoder_tp_encoders_13_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_13_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(404449088)))]; + tensor linear_255_cast_fp16 = linear(bias = encoder_tp_encoders_13_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_13_feed_forward_w_2_weight_to_fp16, x = input_1925_cast_fp16)[name = tensor("linear_255_cast_fp16")]; + tensor input_1931_cast_fp16 = add(x = input_1917_cast_fp16, y = linear_255_cast_fp16)[name = tensor("input_1931_cast_fp16")]; + tensor output_259_axes_0 = const()[name = tensor("output_259_axes_0"), val = tensor([-1])]; + tensor const_392_to_fp16 = const()[name = tensor("const_392_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(404450176)))]; + tensor const_393_to_fp16 = const()[name = tensor("const_393_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(404451264)))]; + tensor output_259_cast_fp16 = layer_norm(axes = output_259_axes_0, beta = const_393_to_fp16, epsilon = var_46_to_fp16, gamma = const_392_to_fp16, x = input_1931_cast_fp16)[name = tensor("output_259_cast_fp16")]; + tensor encoder_tp_encoders_14_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_14_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(404452352)))]; + tensor encoder_tp_encoders_14_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_14_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(406025280)))]; + tensor linear_256_cast_fp16 = linear(bias = encoder_tp_encoders_14_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_14_self_attn_linear_q_k_v_weight_to_fp16, x = output_259_cast_fp16)[name = tensor("linear_256_cast_fp16")]; + tensor tile_64 = const()[name = tensor("tile_64"), val = tensor([512, 512, 512])]; + tensor var_6819_axis_0 = const()[name = tensor("op_6819_axis_0"), val = tensor(-1)]; + tensor var_6819_cast_fp16_0, tensor var_6819_cast_fp16_1, tensor var_6819_cast_fp16_2 = split(axis = var_6819_axis_0, split_sizes = tile_64, x = linear_256_cast_fp16)[name = tensor("op_6819_cast_fp16")]; + tensor concat_192x = const()[name = tensor("concat_192x"), val = tensor([1, -1, 4, 128])]; + tensor var_6824_cast_fp16 = reshape(shape = concat_192x, x = var_6819_cast_fp16_0)[name = tensor("op_6824_cast_fp16")]; + tensor concat_193x = const()[name = tensor("concat_193x"), val = tensor([1, -1, 4, 128])]; + tensor var_6827_cast_fp16 = reshape(shape = concat_193x, x = var_6819_cast_fp16_1)[name = tensor("op_6827_cast_fp16")]; + tensor concat_194x = const()[name = tensor("concat_194x"), val = tensor([1, -1, 4, 128])]; + tensor var_6830_cast_fp16 = reshape(shape = concat_194x, x = var_6819_cast_fp16_2)[name = tensor("op_6830_cast_fp16")]; + tensor value_129_perm_0 = const()[name = tensor("value_129_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_129_cast_fp16 = mul(x = var_6819_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_129_cast_fp16")]; + tensor input_1935_perm_0 = const()[name = tensor("input_1935_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1937_pad_0 = const()[name = tensor("input_1937_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1937_mode_0 = const()[name = tensor("input_1937_mode_0"), val = tensor("constant")]; + tensor const_395_to_fp16 = const()[name = tensor("const_395_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1935_cast_fp16 = transpose(perm = input_1935_perm_0, x = inputs_129_cast_fp16)[name = tensor("transpose_384")]; + tensor input_1937_cast_fp16 = pad(constant_val = const_395_to_fp16, mode = input_1937_mode_0, pad = input_1937_pad_0, x = input_1935_cast_fp16)[name = tensor("input_1937_cast_fp16")]; + tensor x_645_pad_type_0 = const()[name = tensor("x_645_pad_type_0"), val = tensor("valid")]; + tensor x_645_groups_0 = const()[name = tensor("x_645_groups_0"), val = tensor(512)]; + tensor x_645_strides_0 = const()[name = tensor("x_645_strides_0"), val = tensor([1])]; + tensor x_645_pad_0 = const()[name = tensor("x_645_pad_0"), val = tensor([0, 0])]; + tensor x_645_dilations_0 = const()[name = tensor("x_645_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_14_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_14_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(406028416)))]; + tensor x_645_cast_fp16 = conv(dilations = x_645_dilations_0, groups = x_645_groups_0, pad = x_645_pad_0, pad_type = x_645_pad_type_0, strides = x_645_strides_0, weight = encoder_tp_encoders_14_self_attn_fsmn_block_weight_to_fp16, x = input_1937_cast_fp16)[name = tensor("x_645_cast_fp16")]; + tensor x_647_perm_0 = const()[name = tensor("x_647_perm_0"), val = tensor([0, 2, 1])]; + tensor x_647_cast_fp16 = transpose(perm = x_647_perm_0, x = x_645_cast_fp16)[name = tensor("transpose_383")]; + tensor input_1939_cast_fp16 = add(x = x_647_cast_fp16, y = inputs_129_cast_fp16)[name = tensor("input_1939_cast_fp16")]; + tensor fsmn_memory_129_cast_fp16 = mul(x = input_1939_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_129_cast_fp16")]; + tensor var_6849_to_fp16 = const()[name = tensor("op_6849_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_259_cast_fp16 = mul(x = var_6824_cast_fp16, y = var_6849_to_fp16)[name = tensor("q_h_259_cast_fp16")]; + tensor scores_257_transpose_x_0 = const()[name = tensor("scores_257_transpose_x_0"), val = tensor(false)]; + tensor scores_257_transpose_y_0 = const()[name = tensor("scores_257_transpose_y_0"), val = tensor(false)]; + tensor transpose_338_perm_0 = const()[name = tensor("transpose_338_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_339_perm_0 = const()[name = tensor("transpose_339_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_339 = transpose(perm = transpose_339_perm_0, x = var_6827_cast_fp16)[name = tensor("transpose_381")]; + tensor transpose_338 = transpose(perm = transpose_338_perm_0, x = q_h_259_cast_fp16)[name = tensor("transpose_382")]; + tensor scores_257_cast_fp16 = matmul(transpose_x = scores_257_transpose_x_0, transpose_y = scores_257_transpose_y_0, x = transpose_338, y = transpose_339)[name = tensor("scores_257_cast_fp16")]; + tensor scores_259_cast_fp16 = select(a = var_48_to_fp16, b = scores_257_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_259_cast_fp16")]; + tensor var_6857_cast_fp16 = softmax(axis = var_61, x = scores_259_cast_fp16)[name = tensor("op_6857_cast_fp16")]; + tensor input_1941_cast_fp16 = select(a = var_53_to_fp16, b = var_6857_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1941_cast_fp16")]; + tensor x_651_transpose_x_0 = const()[name = tensor("x_651_transpose_x_0"), val = tensor(false)]; + tensor x_651_transpose_y_0 = const()[name = tensor("x_651_transpose_y_0"), val = tensor(false)]; + tensor value_129_cast_fp16 = transpose(perm = value_129_perm_0, x = var_6830_cast_fp16)[name = tensor("transpose_385")]; + tensor x_651_cast_fp16 = matmul(transpose_x = x_651_transpose_x_0, transpose_y = x_651_transpose_y_0, x = input_1941_cast_fp16, y = value_129_cast_fp16)[name = tensor("x_651_cast_fp16")]; + tensor var_6861_perm_0 = const()[name = tensor("op_6861_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_6863 = const()[name = tensor("op_6863"), val = tensor([1, -1, 512])]; + tensor var_6861_cast_fp16 = transpose(perm = var_6861_perm_0, x = x_651_cast_fp16)[name = tensor("transpose_380")]; + tensor input_1943_cast_fp16 = reshape(shape = var_6863, x = var_6861_cast_fp16)[name = tensor("input_1943_cast_fp16")]; + tensor encoder_tp_encoders_14_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_14_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(406039744)))]; + tensor encoder_tp_encoders_14_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_14_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(406564096)))]; + tensor linear_257_cast_fp16 = linear(bias = encoder_tp_encoders_14_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_14_self_attn_linear_out_weight_to_fp16, x = input_1943_cast_fp16)[name = tensor("linear_257_cast_fp16")]; + tensor input_1945_cast_fp16 = add(x = linear_257_cast_fp16, y = fsmn_memory_129_cast_fp16)[name = tensor("input_1945_cast_fp16")]; + tensor input_1947_cast_fp16 = add(x = input_1931_cast_fp16, y = input_1945_cast_fp16)[name = tensor("input_1947_cast_fp16")]; + tensor output_261_axes_0 = const()[name = tensor("output_261_axes_0"), val = tensor([-1])]; + tensor const_396_to_fp16 = const()[name = tensor("const_396_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(406565184)))]; + tensor const_397_to_fp16 = const()[name = tensor("const_397_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(406566272)))]; + tensor output_261_cast_fp16 = layer_norm(axes = output_261_axes_0, beta = const_397_to_fp16, epsilon = var_46_to_fp16, gamma = const_396_to_fp16, x = input_1947_cast_fp16)[name = tensor("output_261_cast_fp16")]; + tensor encoder_tp_encoders_14_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_14_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(406567360)))]; + tensor encoder_tp_encoders_14_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_14_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(408664576)))]; + tensor linear_258_cast_fp16 = linear(bias = encoder_tp_encoders_14_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_14_feed_forward_w_1_weight_to_fp16, x = output_261_cast_fp16)[name = tensor("linear_258_cast_fp16")]; + tensor input_1955_cast_fp16 = relu(x = linear_258_cast_fp16)[name = tensor("input_1955_cast_fp16")]; + tensor encoder_tp_encoders_14_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_14_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(408668736)))]; + tensor encoder_tp_encoders_14_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_14_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(410765952)))]; + tensor linear_259_cast_fp16 = linear(bias = encoder_tp_encoders_14_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_14_feed_forward_w_2_weight_to_fp16, x = input_1955_cast_fp16)[name = tensor("linear_259_cast_fp16")]; + tensor input_1961_cast_fp16 = add(x = input_1947_cast_fp16, y = linear_259_cast_fp16)[name = tensor("input_1961_cast_fp16")]; + tensor output_263_axes_0 = const()[name = tensor("output_263_axes_0"), val = tensor([-1])]; + tensor const_398_to_fp16 = const()[name = tensor("const_398_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(410767040)))]; + tensor const_399_to_fp16 = const()[name = tensor("const_399_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(410768128)))]; + tensor output_263_cast_fp16 = layer_norm(axes = output_263_axes_0, beta = const_399_to_fp16, epsilon = var_46_to_fp16, gamma = const_398_to_fp16, x = input_1961_cast_fp16)[name = tensor("output_263_cast_fp16")]; + tensor encoder_tp_encoders_15_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_15_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(410769216)))]; + tensor encoder_tp_encoders_15_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_15_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412342144)))]; + tensor linear_260_cast_fp16 = linear(bias = encoder_tp_encoders_15_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_15_self_attn_linear_q_k_v_weight_to_fp16, x = output_263_cast_fp16)[name = tensor("linear_260_cast_fp16")]; + tensor tile_65 = const()[name = tensor("tile_65"), val = tensor([512, 512, 512])]; + tensor var_6921_axis_0 = const()[name = tensor("op_6921_axis_0"), val = tensor(-1)]; + tensor var_6921_cast_fp16_0, tensor var_6921_cast_fp16_1, tensor var_6921_cast_fp16_2 = split(axis = var_6921_axis_0, split_sizes = tile_65, x = linear_260_cast_fp16)[name = tensor("op_6921_cast_fp16")]; + tensor concat_195x = const()[name = tensor("concat_195x"), val = tensor([1, -1, 4, 128])]; + tensor var_6926_cast_fp16 = reshape(shape = concat_195x, x = var_6921_cast_fp16_0)[name = tensor("op_6926_cast_fp16")]; + tensor concat_196x = const()[name = tensor("concat_196x"), val = tensor([1, -1, 4, 128])]; + tensor var_6929_cast_fp16 = reshape(shape = concat_196x, x = var_6921_cast_fp16_1)[name = tensor("op_6929_cast_fp16")]; + tensor concat_197x = const()[name = tensor("concat_197x"), val = tensor([1, -1, 4, 128])]; + tensor var_6932_cast_fp16 = reshape(shape = concat_197x, x = var_6921_cast_fp16_2)[name = tensor("op_6932_cast_fp16")]; + tensor value_131_perm_0 = const()[name = tensor("value_131_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_131_cast_fp16 = mul(x = var_6921_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_131_cast_fp16")]; + tensor input_1965_perm_0 = const()[name = tensor("input_1965_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1967_pad_0 = const()[name = tensor("input_1967_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1967_mode_0 = const()[name = tensor("input_1967_mode_0"), val = tensor("constant")]; + tensor const_401_to_fp16 = const()[name = tensor("const_401_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1965_cast_fp16 = transpose(perm = input_1965_perm_0, x = inputs_131_cast_fp16)[name = tensor("transpose_378")]; + tensor input_1967_cast_fp16 = pad(constant_val = const_401_to_fp16, mode = input_1967_mode_0, pad = input_1967_pad_0, x = input_1965_cast_fp16)[name = tensor("input_1967_cast_fp16")]; + tensor x_655_pad_type_0 = const()[name = tensor("x_655_pad_type_0"), val = tensor("valid")]; + tensor x_655_groups_0 = const()[name = tensor("x_655_groups_0"), val = tensor(512)]; + tensor x_655_strides_0 = const()[name = tensor("x_655_strides_0"), val = tensor([1])]; + tensor x_655_pad_0 = const()[name = tensor("x_655_pad_0"), val = tensor([0, 0])]; + tensor x_655_dilations_0 = const()[name = tensor("x_655_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_15_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_15_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412345280)))]; + tensor x_655_cast_fp16 = conv(dilations = x_655_dilations_0, groups = x_655_groups_0, pad = x_655_pad_0, pad_type = x_655_pad_type_0, strides = x_655_strides_0, weight = encoder_tp_encoders_15_self_attn_fsmn_block_weight_to_fp16, x = input_1967_cast_fp16)[name = tensor("x_655_cast_fp16")]; + tensor x_657_perm_0 = const()[name = tensor("x_657_perm_0"), val = tensor([0, 2, 1])]; + tensor x_657_cast_fp16 = transpose(perm = x_657_perm_0, x = x_655_cast_fp16)[name = tensor("transpose_377")]; + tensor input_1969_cast_fp16 = add(x = x_657_cast_fp16, y = inputs_131_cast_fp16)[name = tensor("input_1969_cast_fp16")]; + tensor fsmn_memory_131_cast_fp16 = mul(x = input_1969_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_131_cast_fp16")]; + tensor var_6951_to_fp16 = const()[name = tensor("op_6951_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_263_cast_fp16 = mul(x = var_6926_cast_fp16, y = var_6951_to_fp16)[name = tensor("q_h_263_cast_fp16")]; + tensor scores_261_transpose_x_0 = const()[name = tensor("scores_261_transpose_x_0"), val = tensor(false)]; + tensor scores_261_transpose_y_0 = const()[name = tensor("scores_261_transpose_y_0"), val = tensor(false)]; + tensor transpose_340_perm_0 = const()[name = tensor("transpose_340_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_341_perm_0 = const()[name = tensor("transpose_341_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_341 = transpose(perm = transpose_341_perm_0, x = var_6929_cast_fp16)[name = tensor("transpose_375")]; + tensor transpose_340 = transpose(perm = transpose_340_perm_0, x = q_h_263_cast_fp16)[name = tensor("transpose_376")]; + tensor scores_261_cast_fp16 = matmul(transpose_x = scores_261_transpose_x_0, transpose_y = scores_261_transpose_y_0, x = transpose_340, y = transpose_341)[name = tensor("scores_261_cast_fp16")]; + tensor scores_263_cast_fp16 = select(a = var_48_to_fp16, b = scores_261_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_263_cast_fp16")]; + tensor var_6959_cast_fp16 = softmax(axis = var_61, x = scores_263_cast_fp16)[name = tensor("op_6959_cast_fp16")]; + tensor input_1971_cast_fp16 = select(a = var_53_to_fp16, b = var_6959_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_1971_cast_fp16")]; + tensor x_661_transpose_x_0 = const()[name = tensor("x_661_transpose_x_0"), val = tensor(false)]; + tensor x_661_transpose_y_0 = const()[name = tensor("x_661_transpose_y_0"), val = tensor(false)]; + tensor value_131_cast_fp16 = transpose(perm = value_131_perm_0, x = var_6932_cast_fp16)[name = tensor("transpose_379")]; + tensor x_661_cast_fp16 = matmul(transpose_x = x_661_transpose_x_0, transpose_y = x_661_transpose_y_0, x = input_1971_cast_fp16, y = value_131_cast_fp16)[name = tensor("x_661_cast_fp16")]; + tensor var_6963_perm_0 = const()[name = tensor("op_6963_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_6965 = const()[name = tensor("op_6965"), val = tensor([1, -1, 512])]; + tensor var_6963_cast_fp16 = transpose(perm = var_6963_perm_0, x = x_661_cast_fp16)[name = tensor("transpose_374")]; + tensor input_1973_cast_fp16 = reshape(shape = var_6965, x = var_6963_cast_fp16)[name = tensor("input_1973_cast_fp16")]; + tensor encoder_tp_encoders_15_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_15_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412356608)))]; + tensor encoder_tp_encoders_15_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_15_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412880960)))]; + tensor linear_261_cast_fp16 = linear(bias = encoder_tp_encoders_15_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_15_self_attn_linear_out_weight_to_fp16, x = input_1973_cast_fp16)[name = tensor("linear_261_cast_fp16")]; + tensor input_1975_cast_fp16 = add(x = linear_261_cast_fp16, y = fsmn_memory_131_cast_fp16)[name = tensor("input_1975_cast_fp16")]; + tensor input_1977_cast_fp16 = add(x = input_1961_cast_fp16, y = input_1975_cast_fp16)[name = tensor("input_1977_cast_fp16")]; + tensor output_265_axes_0 = const()[name = tensor("output_265_axes_0"), val = tensor([-1])]; + tensor const_402_to_fp16 = const()[name = tensor("const_402_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412882048)))]; + tensor const_403_to_fp16 = const()[name = tensor("const_403_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412883136)))]; + tensor output_265_cast_fp16 = layer_norm(axes = output_265_axes_0, beta = const_403_to_fp16, epsilon = var_46_to_fp16, gamma = const_402_to_fp16, x = input_1977_cast_fp16)[name = tensor("output_265_cast_fp16")]; + tensor encoder_tp_encoders_15_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_15_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(412884224)))]; + tensor encoder_tp_encoders_15_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_15_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(414981440)))]; + tensor linear_262_cast_fp16 = linear(bias = encoder_tp_encoders_15_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_15_feed_forward_w_1_weight_to_fp16, x = output_265_cast_fp16)[name = tensor("linear_262_cast_fp16")]; + tensor input_1985_cast_fp16 = relu(x = linear_262_cast_fp16)[name = tensor("input_1985_cast_fp16")]; + tensor encoder_tp_encoders_15_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_15_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(414985600)))]; + tensor encoder_tp_encoders_15_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_15_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(417082816)))]; + tensor linear_263_cast_fp16 = linear(bias = encoder_tp_encoders_15_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_15_feed_forward_w_2_weight_to_fp16, x = input_1985_cast_fp16)[name = tensor("linear_263_cast_fp16")]; + tensor input_1991_cast_fp16 = add(x = input_1977_cast_fp16, y = linear_263_cast_fp16)[name = tensor("input_1991_cast_fp16")]; + tensor output_267_axes_0 = const()[name = tensor("output_267_axes_0"), val = tensor([-1])]; + tensor const_404_to_fp16 = const()[name = tensor("const_404_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(417083904)))]; + tensor const_405_to_fp16 = const()[name = tensor("const_405_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(417084992)))]; + tensor output_267_cast_fp16 = layer_norm(axes = output_267_axes_0, beta = const_405_to_fp16, epsilon = var_46_to_fp16, gamma = const_404_to_fp16, x = input_1991_cast_fp16)[name = tensor("output_267_cast_fp16")]; + tensor encoder_tp_encoders_16_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_16_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(417086080)))]; + tensor encoder_tp_encoders_16_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_16_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(418659008)))]; + tensor linear_264_cast_fp16 = linear(bias = encoder_tp_encoders_16_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_16_self_attn_linear_q_k_v_weight_to_fp16, x = output_267_cast_fp16)[name = tensor("linear_264_cast_fp16")]; + tensor tile_66 = const()[name = tensor("tile_66"), val = tensor([512, 512, 512])]; + tensor var_7023_axis_0 = const()[name = tensor("op_7023_axis_0"), val = tensor(-1)]; + tensor var_7023_cast_fp16_0, tensor var_7023_cast_fp16_1, tensor var_7023_cast_fp16_2 = split(axis = var_7023_axis_0, split_sizes = tile_66, x = linear_264_cast_fp16)[name = tensor("op_7023_cast_fp16")]; + tensor concat_198x = const()[name = tensor("concat_198x"), val = tensor([1, -1, 4, 128])]; + tensor var_7028_cast_fp16 = reshape(shape = concat_198x, x = var_7023_cast_fp16_0)[name = tensor("op_7028_cast_fp16")]; + tensor concat_199x = const()[name = tensor("concat_199x"), val = tensor([1, -1, 4, 128])]; + tensor var_7031_cast_fp16 = reshape(shape = concat_199x, x = var_7023_cast_fp16_1)[name = tensor("op_7031_cast_fp16")]; + tensor concat_200x = const()[name = tensor("concat_200x"), val = tensor([1, -1, 4, 128])]; + tensor var_7034_cast_fp16 = reshape(shape = concat_200x, x = var_7023_cast_fp16_2)[name = tensor("op_7034_cast_fp16")]; + tensor value_133_perm_0 = const()[name = tensor("value_133_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_133_cast_fp16 = mul(x = var_7023_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_133_cast_fp16")]; + tensor input_1995_perm_0 = const()[name = tensor("input_1995_perm_0"), val = tensor([0, 2, 1])]; + tensor input_1997_pad_0 = const()[name = tensor("input_1997_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_1997_mode_0 = const()[name = tensor("input_1997_mode_0"), val = tensor("constant")]; + tensor const_407_to_fp16 = const()[name = tensor("const_407_to_fp16"), val = tensor(0x0p+0)]; + tensor input_1995_cast_fp16 = transpose(perm = input_1995_perm_0, x = inputs_133_cast_fp16)[name = tensor("transpose_372")]; + tensor input_1997_cast_fp16 = pad(constant_val = const_407_to_fp16, mode = input_1997_mode_0, pad = input_1997_pad_0, x = input_1995_cast_fp16)[name = tensor("input_1997_cast_fp16")]; + tensor x_665_pad_type_0 = const()[name = tensor("x_665_pad_type_0"), val = tensor("valid")]; + tensor x_665_groups_0 = const()[name = tensor("x_665_groups_0"), val = tensor(512)]; + tensor x_665_strides_0 = const()[name = tensor("x_665_strides_0"), val = tensor([1])]; + tensor x_665_pad_0 = const()[name = tensor("x_665_pad_0"), val = tensor([0, 0])]; + tensor x_665_dilations_0 = const()[name = tensor("x_665_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_16_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_16_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(418662144)))]; + tensor x_665_cast_fp16 = conv(dilations = x_665_dilations_0, groups = x_665_groups_0, pad = x_665_pad_0, pad_type = x_665_pad_type_0, strides = x_665_strides_0, weight = encoder_tp_encoders_16_self_attn_fsmn_block_weight_to_fp16, x = input_1997_cast_fp16)[name = tensor("x_665_cast_fp16")]; + tensor x_667_perm_0 = const()[name = tensor("x_667_perm_0"), val = tensor([0, 2, 1])]; + tensor x_667_cast_fp16 = transpose(perm = x_667_perm_0, x = x_665_cast_fp16)[name = tensor("transpose_371")]; + tensor input_1999_cast_fp16 = add(x = x_667_cast_fp16, y = inputs_133_cast_fp16)[name = tensor("input_1999_cast_fp16")]; + tensor fsmn_memory_133_cast_fp16 = mul(x = input_1999_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_133_cast_fp16")]; + tensor var_7053_to_fp16 = const()[name = tensor("op_7053_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_267_cast_fp16 = mul(x = var_7028_cast_fp16, y = var_7053_to_fp16)[name = tensor("q_h_267_cast_fp16")]; + tensor scores_265_transpose_x_0 = const()[name = tensor("scores_265_transpose_x_0"), val = tensor(false)]; + tensor scores_265_transpose_y_0 = const()[name = tensor("scores_265_transpose_y_0"), val = tensor(false)]; + tensor transpose_342_perm_0 = const()[name = tensor("transpose_342_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_343_perm_0 = const()[name = tensor("transpose_343_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_343 = transpose(perm = transpose_343_perm_0, x = var_7031_cast_fp16)[name = tensor("transpose_369")]; + tensor transpose_342 = transpose(perm = transpose_342_perm_0, x = q_h_267_cast_fp16)[name = tensor("transpose_370")]; + tensor scores_265_cast_fp16 = matmul(transpose_x = scores_265_transpose_x_0, transpose_y = scores_265_transpose_y_0, x = transpose_342, y = transpose_343)[name = tensor("scores_265_cast_fp16")]; + tensor scores_267_cast_fp16 = select(a = var_48_to_fp16, b = scores_265_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_267_cast_fp16")]; + tensor var_7061_cast_fp16 = softmax(axis = var_61, x = scores_267_cast_fp16)[name = tensor("op_7061_cast_fp16")]; + tensor input_2001_cast_fp16 = select(a = var_53_to_fp16, b = var_7061_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_2001_cast_fp16")]; + tensor x_671_transpose_x_0 = const()[name = tensor("x_671_transpose_x_0"), val = tensor(false)]; + tensor x_671_transpose_y_0 = const()[name = tensor("x_671_transpose_y_0"), val = tensor(false)]; + tensor value_133_cast_fp16 = transpose(perm = value_133_perm_0, x = var_7034_cast_fp16)[name = tensor("transpose_373")]; + tensor x_671_cast_fp16 = matmul(transpose_x = x_671_transpose_x_0, transpose_y = x_671_transpose_y_0, x = input_2001_cast_fp16, y = value_133_cast_fp16)[name = tensor("x_671_cast_fp16")]; + tensor var_7065_perm_0 = const()[name = tensor("op_7065_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_7067 = const()[name = tensor("op_7067"), val = tensor([1, -1, 512])]; + tensor var_7065_cast_fp16 = transpose(perm = var_7065_perm_0, x = x_671_cast_fp16)[name = tensor("transpose_368")]; + tensor input_2003_cast_fp16 = reshape(shape = var_7067, x = var_7065_cast_fp16)[name = tensor("input_2003_cast_fp16")]; + tensor encoder_tp_encoders_16_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_16_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(418673472)))]; + tensor encoder_tp_encoders_16_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_16_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(419197824)))]; + tensor linear_265_cast_fp16 = linear(bias = encoder_tp_encoders_16_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_16_self_attn_linear_out_weight_to_fp16, x = input_2003_cast_fp16)[name = tensor("linear_265_cast_fp16")]; + tensor input_2005_cast_fp16 = add(x = linear_265_cast_fp16, y = fsmn_memory_133_cast_fp16)[name = tensor("input_2005_cast_fp16")]; + tensor input_2007_cast_fp16 = add(x = input_1991_cast_fp16, y = input_2005_cast_fp16)[name = tensor("input_2007_cast_fp16")]; + tensor output_269_axes_0 = const()[name = tensor("output_269_axes_0"), val = tensor([-1])]; + tensor const_408_to_fp16 = const()[name = tensor("const_408_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(419198912)))]; + tensor const_409_to_fp16 = const()[name = tensor("const_409_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(419200000)))]; + tensor output_269_cast_fp16 = layer_norm(axes = output_269_axes_0, beta = const_409_to_fp16, epsilon = var_46_to_fp16, gamma = const_408_to_fp16, x = input_2007_cast_fp16)[name = tensor("output_269_cast_fp16")]; + tensor encoder_tp_encoders_16_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_16_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(419201088)))]; + tensor encoder_tp_encoders_16_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_16_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(421298304)))]; + tensor linear_266_cast_fp16 = linear(bias = encoder_tp_encoders_16_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_16_feed_forward_w_1_weight_to_fp16, x = output_269_cast_fp16)[name = tensor("linear_266_cast_fp16")]; + tensor input_2015_cast_fp16 = relu(x = linear_266_cast_fp16)[name = tensor("input_2015_cast_fp16")]; + tensor encoder_tp_encoders_16_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_16_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(421302464)))]; + tensor encoder_tp_encoders_16_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_16_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(423399680)))]; + tensor linear_267_cast_fp16 = linear(bias = encoder_tp_encoders_16_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_16_feed_forward_w_2_weight_to_fp16, x = input_2015_cast_fp16)[name = tensor("linear_267_cast_fp16")]; + tensor input_2021_cast_fp16 = add(x = input_2007_cast_fp16, y = linear_267_cast_fp16)[name = tensor("input_2021_cast_fp16")]; + tensor output_271_axes_0 = const()[name = tensor("output_271_axes_0"), val = tensor([-1])]; + tensor const_410_to_fp16 = const()[name = tensor("const_410_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(423400768)))]; + tensor const_411_to_fp16 = const()[name = tensor("const_411_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(423401856)))]; + tensor output_271_cast_fp16 = layer_norm(axes = output_271_axes_0, beta = const_411_to_fp16, epsilon = var_46_to_fp16, gamma = const_410_to_fp16, x = input_2021_cast_fp16)[name = tensor("output_271_cast_fp16")]; + tensor encoder_tp_encoders_17_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_17_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(423402944)))]; + tensor encoder_tp_encoders_17_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_17_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(424975872)))]; + tensor linear_268_cast_fp16 = linear(bias = encoder_tp_encoders_17_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_17_self_attn_linear_q_k_v_weight_to_fp16, x = output_271_cast_fp16)[name = tensor("linear_268_cast_fp16")]; + tensor tile_67 = const()[name = tensor("tile_67"), val = tensor([512, 512, 512])]; + tensor var_7125_axis_0 = const()[name = tensor("op_7125_axis_0"), val = tensor(-1)]; + tensor var_7125_cast_fp16_0, tensor var_7125_cast_fp16_1, tensor var_7125_cast_fp16_2 = split(axis = var_7125_axis_0, split_sizes = tile_67, x = linear_268_cast_fp16)[name = tensor("op_7125_cast_fp16")]; + tensor concat_201x = const()[name = tensor("concat_201x"), val = tensor([1, -1, 4, 128])]; + tensor var_7130_cast_fp16 = reshape(shape = concat_201x, x = var_7125_cast_fp16_0)[name = tensor("op_7130_cast_fp16")]; + tensor concat_202x = const()[name = tensor("concat_202x"), val = tensor([1, -1, 4, 128])]; + tensor var_7133_cast_fp16 = reshape(shape = concat_202x, x = var_7125_cast_fp16_1)[name = tensor("op_7133_cast_fp16")]; + tensor concat_203x = const()[name = tensor("concat_203x"), val = tensor([1, -1, 4, 128])]; + tensor var_7136_cast_fp16 = reshape(shape = concat_203x, x = var_7125_cast_fp16_2)[name = tensor("op_7136_cast_fp16")]; + tensor value_135_perm_0 = const()[name = tensor("value_135_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_135_cast_fp16 = mul(x = var_7125_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_135_cast_fp16")]; + tensor input_2025_perm_0 = const()[name = tensor("input_2025_perm_0"), val = tensor([0, 2, 1])]; + tensor input_2027_pad_0 = const()[name = tensor("input_2027_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_2027_mode_0 = const()[name = tensor("input_2027_mode_0"), val = tensor("constant")]; + tensor const_413_to_fp16 = const()[name = tensor("const_413_to_fp16"), val = tensor(0x0p+0)]; + tensor input_2025_cast_fp16 = transpose(perm = input_2025_perm_0, x = inputs_135_cast_fp16)[name = tensor("transpose_366")]; + tensor input_2027_cast_fp16 = pad(constant_val = const_413_to_fp16, mode = input_2027_mode_0, pad = input_2027_pad_0, x = input_2025_cast_fp16)[name = tensor("input_2027_cast_fp16")]; + tensor x_675_pad_type_0 = const()[name = tensor("x_675_pad_type_0"), val = tensor("valid")]; + tensor x_675_groups_0 = const()[name = tensor("x_675_groups_0"), val = tensor(512)]; + tensor x_675_strides_0 = const()[name = tensor("x_675_strides_0"), val = tensor([1])]; + tensor x_675_pad_0 = const()[name = tensor("x_675_pad_0"), val = tensor([0, 0])]; + tensor x_675_dilations_0 = const()[name = tensor("x_675_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_17_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_17_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(424979008)))]; + tensor x_675_cast_fp16 = conv(dilations = x_675_dilations_0, groups = x_675_groups_0, pad = x_675_pad_0, pad_type = x_675_pad_type_0, strides = x_675_strides_0, weight = encoder_tp_encoders_17_self_attn_fsmn_block_weight_to_fp16, x = input_2027_cast_fp16)[name = tensor("x_675_cast_fp16")]; + tensor x_677_perm_0 = const()[name = tensor("x_677_perm_0"), val = tensor([0, 2, 1])]; + tensor x_677_cast_fp16 = transpose(perm = x_677_perm_0, x = x_675_cast_fp16)[name = tensor("transpose_365")]; + tensor input_2029_cast_fp16 = add(x = x_677_cast_fp16, y = inputs_135_cast_fp16)[name = tensor("input_2029_cast_fp16")]; + tensor fsmn_memory_135_cast_fp16 = mul(x = input_2029_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_135_cast_fp16")]; + tensor var_7155_to_fp16 = const()[name = tensor("op_7155_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_271_cast_fp16 = mul(x = var_7130_cast_fp16, y = var_7155_to_fp16)[name = tensor("q_h_271_cast_fp16")]; + tensor scores_269_transpose_x_0 = const()[name = tensor("scores_269_transpose_x_0"), val = tensor(false)]; + tensor scores_269_transpose_y_0 = const()[name = tensor("scores_269_transpose_y_0"), val = tensor(false)]; + tensor transpose_344_perm_0 = const()[name = tensor("transpose_344_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_345_perm_0 = const()[name = tensor("transpose_345_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_345 = transpose(perm = transpose_345_perm_0, x = var_7133_cast_fp16)[name = tensor("transpose_363")]; + tensor transpose_344 = transpose(perm = transpose_344_perm_0, x = q_h_271_cast_fp16)[name = tensor("transpose_364")]; + tensor scores_269_cast_fp16 = matmul(transpose_x = scores_269_transpose_x_0, transpose_y = scores_269_transpose_y_0, x = transpose_344, y = transpose_345)[name = tensor("scores_269_cast_fp16")]; + tensor scores_271_cast_fp16 = select(a = var_48_to_fp16, b = scores_269_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_271_cast_fp16")]; + tensor var_7163_cast_fp16 = softmax(axis = var_61, x = scores_271_cast_fp16)[name = tensor("op_7163_cast_fp16")]; + tensor input_2031_cast_fp16 = select(a = var_53_to_fp16, b = var_7163_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_2031_cast_fp16")]; + tensor x_681_transpose_x_0 = const()[name = tensor("x_681_transpose_x_0"), val = tensor(false)]; + tensor x_681_transpose_y_0 = const()[name = tensor("x_681_transpose_y_0"), val = tensor(false)]; + tensor value_135_cast_fp16 = transpose(perm = value_135_perm_0, x = var_7136_cast_fp16)[name = tensor("transpose_367")]; + tensor x_681_cast_fp16 = matmul(transpose_x = x_681_transpose_x_0, transpose_y = x_681_transpose_y_0, x = input_2031_cast_fp16, y = value_135_cast_fp16)[name = tensor("x_681_cast_fp16")]; + tensor var_7167_perm_0 = const()[name = tensor("op_7167_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_7169 = const()[name = tensor("op_7169"), val = tensor([1, -1, 512])]; + tensor var_7167_cast_fp16 = transpose(perm = var_7167_perm_0, x = x_681_cast_fp16)[name = tensor("transpose_362")]; + tensor input_2033_cast_fp16 = reshape(shape = var_7169, x = var_7167_cast_fp16)[name = tensor("input_2033_cast_fp16")]; + tensor encoder_tp_encoders_17_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_17_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(424990336)))]; + tensor encoder_tp_encoders_17_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_17_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(425514688)))]; + tensor linear_269_cast_fp16 = linear(bias = encoder_tp_encoders_17_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_17_self_attn_linear_out_weight_to_fp16, x = input_2033_cast_fp16)[name = tensor("linear_269_cast_fp16")]; + tensor input_2035_cast_fp16 = add(x = linear_269_cast_fp16, y = fsmn_memory_135_cast_fp16)[name = tensor("input_2035_cast_fp16")]; + tensor input_2037_cast_fp16 = add(x = input_2021_cast_fp16, y = input_2035_cast_fp16)[name = tensor("input_2037_cast_fp16")]; + tensor output_273_axes_0 = const()[name = tensor("output_273_axes_0"), val = tensor([-1])]; + tensor const_414_to_fp16 = const()[name = tensor("const_414_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(425515776)))]; + tensor const_415_to_fp16 = const()[name = tensor("const_415_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(425516864)))]; + tensor output_273_cast_fp16 = layer_norm(axes = output_273_axes_0, beta = const_415_to_fp16, epsilon = var_46_to_fp16, gamma = const_414_to_fp16, x = input_2037_cast_fp16)[name = tensor("output_273_cast_fp16")]; + tensor encoder_tp_encoders_17_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_17_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(425517952)))]; + tensor encoder_tp_encoders_17_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_17_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(427615168)))]; + tensor linear_270_cast_fp16 = linear(bias = encoder_tp_encoders_17_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_17_feed_forward_w_1_weight_to_fp16, x = output_273_cast_fp16)[name = tensor("linear_270_cast_fp16")]; + tensor input_2045_cast_fp16 = relu(x = linear_270_cast_fp16)[name = tensor("input_2045_cast_fp16")]; + tensor encoder_tp_encoders_17_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_17_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(427619328)))]; + tensor encoder_tp_encoders_17_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_17_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(429716544)))]; + tensor linear_271_cast_fp16 = linear(bias = encoder_tp_encoders_17_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_17_feed_forward_w_2_weight_to_fp16, x = input_2045_cast_fp16)[name = tensor("linear_271_cast_fp16")]; + tensor input_2051_cast_fp16 = add(x = input_2037_cast_fp16, y = linear_271_cast_fp16)[name = tensor("input_2051_cast_fp16")]; + tensor output_275_axes_0 = const()[name = tensor("output_275_axes_0"), val = tensor([-1])]; + tensor const_416_to_fp16 = const()[name = tensor("const_416_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(429717632)))]; + tensor const_417_to_fp16 = const()[name = tensor("const_417_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(429718720)))]; + tensor output_275_cast_fp16 = layer_norm(axes = output_275_axes_0, beta = const_417_to_fp16, epsilon = var_46_to_fp16, gamma = const_416_to_fp16, x = input_2051_cast_fp16)[name = tensor("output_275_cast_fp16")]; + tensor encoder_tp_encoders_18_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_18_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(429719808)))]; + tensor encoder_tp_encoders_18_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_18_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(431292736)))]; + tensor linear_272_cast_fp16 = linear(bias = encoder_tp_encoders_18_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_18_self_attn_linear_q_k_v_weight_to_fp16, x = output_275_cast_fp16)[name = tensor("linear_272_cast_fp16")]; + tensor tile_68 = const()[name = tensor("tile_68"), val = tensor([512, 512, 512])]; + tensor var_7227_axis_0 = const()[name = tensor("op_7227_axis_0"), val = tensor(-1)]; + tensor var_7227_cast_fp16_0, tensor var_7227_cast_fp16_1, tensor var_7227_cast_fp16_2 = split(axis = var_7227_axis_0, split_sizes = tile_68, x = linear_272_cast_fp16)[name = tensor("op_7227_cast_fp16")]; + tensor concat_204x = const()[name = tensor("concat_204x"), val = tensor([1, -1, 4, 128])]; + tensor var_7232_cast_fp16 = reshape(shape = concat_204x, x = var_7227_cast_fp16_0)[name = tensor("op_7232_cast_fp16")]; + tensor concat_205x = const()[name = tensor("concat_205x"), val = tensor([1, -1, 4, 128])]; + tensor var_7235_cast_fp16 = reshape(shape = concat_205x, x = var_7227_cast_fp16_1)[name = tensor("op_7235_cast_fp16")]; + tensor concat_206x = const()[name = tensor("concat_206x"), val = tensor([1, -1, 4, 128])]; + tensor var_7238_cast_fp16 = reshape(shape = concat_206x, x = var_7227_cast_fp16_2)[name = tensor("op_7238_cast_fp16")]; + tensor value_137_perm_0 = const()[name = tensor("value_137_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_137_cast_fp16 = mul(x = var_7227_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_137_cast_fp16")]; + tensor input_2055_perm_0 = const()[name = tensor("input_2055_perm_0"), val = tensor([0, 2, 1])]; + tensor input_2057_pad_0 = const()[name = tensor("input_2057_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_2057_mode_0 = const()[name = tensor("input_2057_mode_0"), val = tensor("constant")]; + tensor const_419_to_fp16 = const()[name = tensor("const_419_to_fp16"), val = tensor(0x0p+0)]; + tensor input_2055_cast_fp16 = transpose(perm = input_2055_perm_0, x = inputs_137_cast_fp16)[name = tensor("transpose_360")]; + tensor input_2057_cast_fp16 = pad(constant_val = const_419_to_fp16, mode = input_2057_mode_0, pad = input_2057_pad_0, x = input_2055_cast_fp16)[name = tensor("input_2057_cast_fp16")]; + tensor x_685_pad_type_0 = const()[name = tensor("x_685_pad_type_0"), val = tensor("valid")]; + tensor x_685_groups_0 = const()[name = tensor("x_685_groups_0"), val = tensor(512)]; + tensor x_685_strides_0 = const()[name = tensor("x_685_strides_0"), val = tensor([1])]; + tensor x_685_pad_0 = const()[name = tensor("x_685_pad_0"), val = tensor([0, 0])]; + tensor x_685_dilations_0 = const()[name = tensor("x_685_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_18_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_18_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(431295872)))]; + tensor x_685_cast_fp16 = conv(dilations = x_685_dilations_0, groups = x_685_groups_0, pad = x_685_pad_0, pad_type = x_685_pad_type_0, strides = x_685_strides_0, weight = encoder_tp_encoders_18_self_attn_fsmn_block_weight_to_fp16, x = input_2057_cast_fp16)[name = tensor("x_685_cast_fp16")]; + tensor x_687_perm_0 = const()[name = tensor("x_687_perm_0"), val = tensor([0, 2, 1])]; + tensor x_687_cast_fp16 = transpose(perm = x_687_perm_0, x = x_685_cast_fp16)[name = tensor("transpose_359")]; + tensor input_2059_cast_fp16 = add(x = x_687_cast_fp16, y = inputs_137_cast_fp16)[name = tensor("input_2059_cast_fp16")]; + tensor fsmn_memory_137_cast_fp16 = mul(x = input_2059_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_137_cast_fp16")]; + tensor var_7257_to_fp16 = const()[name = tensor("op_7257_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_275_cast_fp16 = mul(x = var_7232_cast_fp16, y = var_7257_to_fp16)[name = tensor("q_h_275_cast_fp16")]; + tensor scores_273_transpose_x_0 = const()[name = tensor("scores_273_transpose_x_0"), val = tensor(false)]; + tensor scores_273_transpose_y_0 = const()[name = tensor("scores_273_transpose_y_0"), val = tensor(false)]; + tensor transpose_346_perm_0 = const()[name = tensor("transpose_346_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_347_perm_0 = const()[name = tensor("transpose_347_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_347 = transpose(perm = transpose_347_perm_0, x = var_7235_cast_fp16)[name = tensor("transpose_357")]; + tensor transpose_346 = transpose(perm = transpose_346_perm_0, x = q_h_275_cast_fp16)[name = tensor("transpose_358")]; + tensor scores_273_cast_fp16 = matmul(transpose_x = scores_273_transpose_x_0, transpose_y = scores_273_transpose_y_0, x = transpose_346, y = transpose_347)[name = tensor("scores_273_cast_fp16")]; + tensor scores_275_cast_fp16 = select(a = var_48_to_fp16, b = scores_273_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_275_cast_fp16")]; + tensor var_7265_cast_fp16 = softmax(axis = var_61, x = scores_275_cast_fp16)[name = tensor("op_7265_cast_fp16")]; + tensor input_2061_cast_fp16 = select(a = var_53_to_fp16, b = var_7265_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_2061_cast_fp16")]; + tensor x_691_transpose_x_0 = const()[name = tensor("x_691_transpose_x_0"), val = tensor(false)]; + tensor x_691_transpose_y_0 = const()[name = tensor("x_691_transpose_y_0"), val = tensor(false)]; + tensor value_137_cast_fp16 = transpose(perm = value_137_perm_0, x = var_7238_cast_fp16)[name = tensor("transpose_361")]; + tensor x_691_cast_fp16 = matmul(transpose_x = x_691_transpose_x_0, transpose_y = x_691_transpose_y_0, x = input_2061_cast_fp16, y = value_137_cast_fp16)[name = tensor("x_691_cast_fp16")]; + tensor var_7269_perm_0 = const()[name = tensor("op_7269_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_7271 = const()[name = tensor("op_7271"), val = tensor([1, -1, 512])]; + tensor var_7269_cast_fp16 = transpose(perm = var_7269_perm_0, x = x_691_cast_fp16)[name = tensor("transpose_356")]; + tensor input_2063_cast_fp16 = reshape(shape = var_7271, x = var_7269_cast_fp16)[name = tensor("input_2063_cast_fp16")]; + tensor encoder_tp_encoders_18_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_18_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(431307200)))]; + tensor encoder_tp_encoders_18_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_18_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(431831552)))]; + tensor linear_273_cast_fp16 = linear(bias = encoder_tp_encoders_18_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_18_self_attn_linear_out_weight_to_fp16, x = input_2063_cast_fp16)[name = tensor("linear_273_cast_fp16")]; + tensor input_2065_cast_fp16 = add(x = linear_273_cast_fp16, y = fsmn_memory_137_cast_fp16)[name = tensor("input_2065_cast_fp16")]; + tensor input_2067_cast_fp16 = add(x = input_2051_cast_fp16, y = input_2065_cast_fp16)[name = tensor("input_2067_cast_fp16")]; + tensor output_277_axes_0 = const()[name = tensor("output_277_axes_0"), val = tensor([-1])]; + tensor const_420_to_fp16 = const()[name = tensor("const_420_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(431832640)))]; + tensor const_421_to_fp16 = const()[name = tensor("const_421_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(431833728)))]; + tensor output_277_cast_fp16 = layer_norm(axes = output_277_axes_0, beta = const_421_to_fp16, epsilon = var_46_to_fp16, gamma = const_420_to_fp16, x = input_2067_cast_fp16)[name = tensor("output_277_cast_fp16")]; + tensor encoder_tp_encoders_18_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_18_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(431834816)))]; + tensor encoder_tp_encoders_18_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_18_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(433932032)))]; + tensor linear_274_cast_fp16 = linear(bias = encoder_tp_encoders_18_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_18_feed_forward_w_1_weight_to_fp16, x = output_277_cast_fp16)[name = tensor("linear_274_cast_fp16")]; + tensor input_2075_cast_fp16 = relu(x = linear_274_cast_fp16)[name = tensor("input_2075_cast_fp16")]; + tensor encoder_tp_encoders_18_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_18_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(433936192)))]; + tensor encoder_tp_encoders_18_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_18_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(436033408)))]; + tensor linear_275_cast_fp16 = linear(bias = encoder_tp_encoders_18_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_18_feed_forward_w_2_weight_to_fp16, x = input_2075_cast_fp16)[name = tensor("linear_275_cast_fp16")]; + tensor input_2081_cast_fp16 = add(x = input_2067_cast_fp16, y = linear_275_cast_fp16)[name = tensor("input_2081_cast_fp16")]; + tensor output_279_axes_0 = const()[name = tensor("output_279_axes_0"), val = tensor([-1])]; + tensor const_422_to_fp16 = const()[name = tensor("const_422_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(436034496)))]; + tensor const_423_to_fp16 = const()[name = tensor("const_423_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(436035584)))]; + tensor output_279_cast_fp16 = layer_norm(axes = output_279_axes_0, beta = const_423_to_fp16, epsilon = var_46_to_fp16, gamma = const_422_to_fp16, x = input_2081_cast_fp16)[name = tensor("output_279_cast_fp16")]; + tensor encoder_tp_encoders_19_self_attn_linear_q_k_v_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_19_self_attn_linear_q_k_v_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(436036672)))]; + tensor encoder_tp_encoders_19_self_attn_linear_q_k_v_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_19_self_attn_linear_q_k_v_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(437609600)))]; + tensor linear_276_cast_fp16 = linear(bias = encoder_tp_encoders_19_self_attn_linear_q_k_v_bias_to_fp16, weight = encoder_tp_encoders_19_self_attn_linear_q_k_v_weight_to_fp16, x = output_279_cast_fp16)[name = tensor("linear_276_cast_fp16")]; + tensor tile_69 = const()[name = tensor("tile_69"), val = tensor([512, 512, 512])]; + tensor var_7329_axis_0 = const()[name = tensor("op_7329_axis_0"), val = tensor(-1)]; + tensor var_7329_cast_fp16_0, tensor var_7329_cast_fp16_1, tensor var_7329_cast_fp16_2 = split(axis = var_7329_axis_0, split_sizes = tile_69, x = linear_276_cast_fp16)[name = tensor("op_7329_cast_fp16")]; + tensor concat_207x = const()[name = tensor("concat_207x"), val = tensor([1, -1, 4, 128])]; + tensor var_7334_cast_fp16 = reshape(shape = concat_207x, x = var_7329_cast_fp16_0)[name = tensor("op_7334_cast_fp16")]; + tensor concat_208x = const()[name = tensor("concat_208x"), val = tensor([1, -1, 4, 128])]; + tensor var_7337_cast_fp16 = reshape(shape = concat_208x, x = var_7329_cast_fp16_1)[name = tensor("op_7337_cast_fp16")]; + tensor concat_209x = const()[name = tensor("concat_209x"), val = tensor([1, -1, 4, 128])]; + tensor var_7340_cast_fp16 = reshape(shape = concat_209x, x = var_7329_cast_fp16_2)[name = tensor("op_7340_cast_fp16")]; + tensor value_perm_0 = const()[name = tensor("value_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor inputs_cast_fp16 = mul(x = var_7329_cast_fp16_2, y = mask_7_cast_fp16)[name = tensor("inputs_cast_fp16")]; + tensor input_2085_perm_0 = const()[name = tensor("input_2085_perm_0"), val = tensor([0, 2, 1])]; + tensor input_2087_pad_0 = const()[name = tensor("input_2087_pad_0"), val = tensor([0, 0, 0, 0, 5, 5])]; + tensor input_2087_mode_0 = const()[name = tensor("input_2087_mode_0"), val = tensor("constant")]; + tensor const_425_to_fp16 = const()[name = tensor("const_425_to_fp16"), val = tensor(0x0p+0)]; + tensor input_2085_cast_fp16 = transpose(perm = input_2085_perm_0, x = inputs_cast_fp16)[name = tensor("transpose_354")]; + tensor input_2087_cast_fp16 = pad(constant_val = const_425_to_fp16, mode = input_2087_mode_0, pad = input_2087_pad_0, x = input_2085_cast_fp16)[name = tensor("input_2087_cast_fp16")]; + tensor x_695_pad_type_0 = const()[name = tensor("x_695_pad_type_0"), val = tensor("valid")]; + tensor x_695_groups_0 = const()[name = tensor("x_695_groups_0"), val = tensor(512)]; + tensor x_695_strides_0 = const()[name = tensor("x_695_strides_0"), val = tensor([1])]; + tensor x_695_pad_0 = const()[name = tensor("x_695_pad_0"), val = tensor([0, 0])]; + tensor x_695_dilations_0 = const()[name = tensor("x_695_dilations_0"), val = tensor([1])]; + tensor encoder_tp_encoders_19_self_attn_fsmn_block_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_19_self_attn_fsmn_block_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(437612736)))]; + tensor x_695_cast_fp16 = conv(dilations = x_695_dilations_0, groups = x_695_groups_0, pad = x_695_pad_0, pad_type = x_695_pad_type_0, strides = x_695_strides_0, weight = encoder_tp_encoders_19_self_attn_fsmn_block_weight_to_fp16, x = input_2087_cast_fp16)[name = tensor("x_695_cast_fp16")]; + tensor x_697_perm_0 = const()[name = tensor("x_697_perm_0"), val = tensor([0, 2, 1])]; + tensor x_697_cast_fp16 = transpose(perm = x_697_perm_0, x = x_695_cast_fp16)[name = tensor("transpose_353")]; + tensor input_2089_cast_fp16 = add(x = x_697_cast_fp16, y = inputs_cast_fp16)[name = tensor("input_2089_cast_fp16")]; + tensor fsmn_memory_cast_fp16 = mul(x = input_2089_cast_fp16, y = mask_7_cast_fp16)[name = tensor("fsmn_memory_cast_fp16")]; + tensor var_7359_to_fp16 = const()[name = tensor("op_7359_to_fp16"), val = tensor(0x1.6ap-4)]; + tensor q_h_cast_fp16 = mul(x = var_7334_cast_fp16, y = var_7359_to_fp16)[name = tensor("q_h_cast_fp16")]; + tensor scores_277_transpose_x_0 = const()[name = tensor("scores_277_transpose_x_0"), val = tensor(false)]; + tensor scores_277_transpose_y_0 = const()[name = tensor("scores_277_transpose_y_0"), val = tensor(false)]; + tensor transpose_348_perm_0 = const()[name = tensor("transpose_348_perm_0"), val = tensor([0, 2, -3, -1])]; + tensor transpose_349_perm_0 = const()[name = tensor("transpose_349_perm_0"), val = tensor([0, 2, -1, -3])]; + tensor transpose_349 = transpose(perm = transpose_349_perm_0, x = var_7337_cast_fp16)[name = tensor("transpose_351")]; + tensor transpose_348 = transpose(perm = transpose_348_perm_0, x = q_h_cast_fp16)[name = tensor("transpose_352")]; + tensor scores_277_cast_fp16 = matmul(transpose_x = scores_277_transpose_x_0, transpose_y = scores_277_transpose_y_0, x = transpose_348, y = transpose_349)[name = tensor("scores_277_cast_fp16")]; + tensor scores_cast_fp16 = select(a = var_48_to_fp16, b = scores_277_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("scores_cast_fp16")]; + tensor var_7367_cast_fp16 = softmax(axis = var_61, x = scores_cast_fp16)[name = tensor("op_7367_cast_fp16")]; + tensor input_2091_cast_fp16 = select(a = var_53_to_fp16, b = var_7367_cast_fp16, cond = mask_9_cast_fp16)[name = tensor("input_2091_cast_fp16")]; + tensor x_transpose_x_0 = const()[name = tensor("x_transpose_x_0"), val = tensor(false)]; + tensor x_transpose_y_0 = const()[name = tensor("x_transpose_y_0"), val = tensor(false)]; + tensor value_cast_fp16 = transpose(perm = value_perm_0, x = var_7340_cast_fp16)[name = tensor("transpose_355")]; + tensor x_cast_fp16 = matmul(transpose_x = x_transpose_x_0, transpose_y = x_transpose_y_0, x = input_2091_cast_fp16, y = value_cast_fp16)[name = tensor("x_cast_fp16")]; + tensor var_7371_perm_0 = const()[name = tensor("op_7371_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_7373 = const()[name = tensor("op_7373"), val = tensor([1, -1, 512])]; + tensor var_7371_cast_fp16 = transpose(perm = var_7371_perm_0, x = x_cast_fp16)[name = tensor("transpose_350")]; + tensor input_2093_cast_fp16 = reshape(shape = var_7373, x = var_7371_cast_fp16)[name = tensor("input_2093_cast_fp16")]; + tensor encoder_tp_encoders_19_self_attn_linear_out_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_19_self_attn_linear_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(437624064)))]; + tensor encoder_tp_encoders_19_self_attn_linear_out_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_19_self_attn_linear_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(438148416)))]; + tensor linear_277_cast_fp16 = linear(bias = encoder_tp_encoders_19_self_attn_linear_out_bias_to_fp16, weight = encoder_tp_encoders_19_self_attn_linear_out_weight_to_fp16, x = input_2093_cast_fp16)[name = tensor("linear_277_cast_fp16")]; + tensor input_2095_cast_fp16 = add(x = linear_277_cast_fp16, y = fsmn_memory_cast_fp16)[name = tensor("input_2095_cast_fp16")]; + tensor input_2097_cast_fp16 = add(x = input_2081_cast_fp16, y = input_2095_cast_fp16)[name = tensor("input_2097_cast_fp16")]; + tensor output_281_axes_0 = const()[name = tensor("output_281_axes_0"), val = tensor([-1])]; + tensor const_426_to_fp16 = const()[name = tensor("const_426_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(438149504)))]; + tensor const_427_to_fp16 = const()[name = tensor("const_427_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(438150592)))]; + tensor output_281_cast_fp16 = layer_norm(axes = output_281_axes_0, beta = const_427_to_fp16, epsilon = var_46_to_fp16, gamma = const_426_to_fp16, x = input_2097_cast_fp16)[name = tensor("output_281_cast_fp16")]; + tensor encoder_tp_encoders_19_feed_forward_w_1_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_19_feed_forward_w_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(438151680)))]; + tensor encoder_tp_encoders_19_feed_forward_w_1_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_19_feed_forward_w_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(440248896)))]; + tensor linear_278_cast_fp16 = linear(bias = encoder_tp_encoders_19_feed_forward_w_1_bias_to_fp16, weight = encoder_tp_encoders_19_feed_forward_w_1_weight_to_fp16, x = output_281_cast_fp16)[name = tensor("linear_278_cast_fp16")]; + tensor input_2105_cast_fp16 = relu(x = linear_278_cast_fp16)[name = tensor("input_2105_cast_fp16")]; + tensor encoder_tp_encoders_19_feed_forward_w_2_weight_to_fp16 = const()[name = tensor("encoder_tp_encoders_19_feed_forward_w_2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(440253056)))]; + tensor encoder_tp_encoders_19_feed_forward_w_2_bias_to_fp16 = const()[name = tensor("encoder_tp_encoders_19_feed_forward_w_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(442350272)))]; + tensor linear_279_cast_fp16 = linear(bias = encoder_tp_encoders_19_feed_forward_w_2_bias_to_fp16, weight = encoder_tp_encoders_19_feed_forward_w_2_weight_to_fp16, x = input_2105_cast_fp16)[name = tensor("linear_279_cast_fp16")]; + tensor input_2111_cast_fp16 = add(x = input_2097_cast_fp16, y = linear_279_cast_fp16)[name = tensor("input_2111_cast_fp16")]; + tensor output_axes_0 = const()[name = tensor("output_axes_0"), val = tensor([-1])]; + tensor const_428_to_fp16 = const()[name = tensor("const_428_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(442351360)))]; + tensor const_429_to_fp16 = const()[name = tensor("const_429_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(442352448)))]; + tensor output_cast_fp16 = layer_norm(axes = output_axes_0, beta = const_429_to_fp16, epsilon = var_46_to_fp16, gamma = const_428_to_fp16, x = input_2111_cast_fp16)[name = tensor("output_cast_fp16")]; + tensor ctc_lo_weight_to_fp16 = const()[name = tensor("ctc_lo_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(442353536)))]; + tensor ctc_lo_bias_to_fp16 = const()[name = tensor("ctc_lo_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(468009920)))]; + tensor ctc_logits = linear(bias = ctc_lo_bias_to_fp16, weight = ctc_lo_weight_to_fp16, x = output_cast_fp16)[name = tensor("linear_280_cast_fp16")]; + } -> (ctc_logits); +} \ No newline at end of file