Upload model file

processing.py

@@ -0,0 +1,54 @@
+from fractions import Fraction
+
+from transformers import LlavaNextProcessor
+from transformers.image_processing_utils import select_best_resolution
+
+
+
+class Granite4VisionProcessor(LlavaNextProcessor):
+    model_type = "granite4_vision"
+
+    def __init__(
+        self,
+        image_processor=None,
+        tokenizer=None,
+        patch_size=None,
+        vision_feature_select_strategy=None,
+        chat_template=None,
+        image_token="<image>",  # set the default and let users change if they have peculiar special tokens in rare cases
+        num_additional_image_tokens=0,
+        downsample_rate=None,
+        **kwargs,
+    ):
+        super().__init__(image_processor=image_processor, 
+                         tokenizer=tokenizer,
+                         patch_size=patch_size,
+                         vision_feature_select_strategy=vision_feature_select_strategy,
+                         chat_template=chat_template,
+                         image_token=image_token,
+                         num_additional_image_tokens=num_additional_image_tokens,
+                         )
+        self.downsample_rate = downsample_rate
+
+    def _get_number_of_features(self, orig_height: int, orig_width: int, height: int, width: int) -> int:
+        image_grid_pinpoints = self.image_processor.image_grid_pinpoints
+
+        height_best_resolution, width_best_resolution = select_best_resolution(
+            [orig_height, orig_width], image_grid_pinpoints
+        )
+        scale_height, scale_width = height_best_resolution // height, width_best_resolution // width
+
+        patches_height = height // self.patch_size
+        patches_width = width // self.patch_size
+        if self.downsample_rate is not None:
+            ds_rate = Fraction(self.downsample_rate)
+            patches_height = int(patches_height * ds_rate)
+            patches_width = int(patches_width * ds_rate)
+            
+        unpadded_features, newline_features = self._get_unpadded_features(
+            orig_height, orig_width, patches_height, patches_width, scale_height, scale_width
+        )
+        # The base patch covers the entire image (+1 for the CLS)
+        base_features = patches_height * patches_width + self.num_additional_image_tokens
+        num_image_tokens = unpadded_features + newline_features + base_features
+        return num_image_tokens