Fix Auto classes to support dynamically registered processors (#41865)

Author: MilkClouds

src/transformers/models/auto/image_processing_auto.py

@@ -524,10 +524,9 @@ def from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwargs):
                 )
                 use_fast = False
             if use_fast:
-                for image_processors in IMAGE_PROCESSOR_MAPPING_NAMES.values():
-                    if image_processor_type in image_processors:
-                        break
-                else:
+                # Check if the fast image processor class exists
+                image_processor_class_fast = get_image_processor_class_from_name(image_processor_type)
+                if image_processor_class_fast is None:
                     image_processor_type = image_processor_type[:-4]
                     use_fast = False
                     logger.warning_once(

src/transformers/models/auto/video_processing_auto.py

@@ -291,7 +291,7 @@ def from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwargs):
 
                 # Some models have different image processors, e.g. InternVL uses GotOCRImageProcessor
                 # We cannot use GotOCRVideoProcessor when falling back for BC and should try to infer from config later on
-                if video_processor_class_inferred in VIDEO_PROCESSOR_MAPPING_NAMES.values():
+                if video_processor_class_from_name(video_processor_class_inferred) is not None:
                     video_processor_class = video_processor_class_inferred
             if "AutoImageProcessor" in config_dict.get("auto_map", {}):
                 image_processor_auto_map = config_dict["auto_map"]["AutoImageProcessor"]