Fix torchvision.transforms and transforms function naming clash (#2274)

* Fix torchvision.transforms and transforms function naming clash

* Update unconditional script for onnx

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

examples/research_projects/onnxruntime/unconditional_image_generation/train_unconditional.py

@@ -386,13 +386,13 @@ def main(args):
         ]
     )
 
-    def transforms(examples):
+    def transform_images(examples):
         images = [augmentations(image.convert("RGB")) for image in examples["image"]]
         return {"input": images}
 
     logger.info(f"Dataset size: {len(dataset)}")
 
-    dataset.set_transform(transforms)
+    dataset.set_transform(transform_images)
     train_dataloader = torch.utils.data.DataLoader(
         dataset, batch_size=args.train_batch_size, shuffle=True, num_workers=args.dataloader_num_workers
     )

examples/unconditional_image_generation/train_unconditional.py

@@ -386,13 +386,13 @@ def main(args):
         ]
     )
 
-    def transforms(examples):
+    def transform_images(examples):
         images = [augmentations(image.convert("RGB")) for image in examples["image"]]
         return {"input": images}
 
     logger.info(f"Dataset size: {len(dataset)}")
 
-    dataset.set_transform(transforms)
+    dataset.set_transform(transform_images)
     train_dataloader = torch.utils.data.DataLoader(
         dataset, batch_size=args.train_batch_size, shuffle=True, num_workers=args.dataloader_num_workers
     )