class <lambda>(torch.nn.Module):
    def forward(self, arg0_1: "f32[4096, 8192][8192, 1]cuda:0", arg1_1: "f32[4096][1]cuda:0", arg2_1: "i32[4096][1]cuda:0"):
         # File: /shared_volume/repos/quark/quark/torch/kernel/__init__.py:168 in forward, code: return ops.quark.scaled_fake_quantize(quant_dtype, inputs, scale, zero_point, axis, group_size, quant_min,
        scaled_fake_quantize: "f32[4096, 8192][8192, 1]cuda:0" = torch.ops.quark.scaled_fake_quantize.default('int4', arg0_1, arg1_1, arg2_1, 0, 0, 0.0, 15.0, 0, 'per_channel', 'haha');  arg0_1 = arg1_1 = arg2_1 = None
        return (scaled_fake_quantize,)