fix mask discrepancies in train_dreambooth_inpaint (#1529)

The mask and instance image were being cropped in different ways without --center_crop, causing the model to learn to ignore the mask in some cases. This PR fixes that and generate more consistent results.

examples/dreambooth/train_dreambooth_inpaint.py

@@ -295,10 +295,15 @@ class DreamBoothDataset(Dataset):
         else:
             self.class_data_root = None
 
-        self.image_transforms = transforms.Compose(
+        self.image_transforms_resize_and_crop = transforms.Compose(
             [
                 transforms.Resize(size, interpolation=transforms.InterpolationMode.BILINEAR),
                 transforms.CenterCrop(size) if center_crop else transforms.RandomCrop(size),
+            ]
+        )
+
+        self.image_transforms = transforms.Compose(
+            [
                 transforms.ToTensor(),
                 transforms.Normalize([0.5], [0.5]),
             ]
@@ -312,6 +317,7 @@ class DreamBoothDataset(Dataset):
         instance_image = Image.open(self.instance_images_path[index % self.num_instance_images])
         if not instance_image.mode == "RGB":
             instance_image = instance_image.convert("RGB")
+        instance_image = self.image_transforms_resize_and_crop(instance_image)
 
         example["PIL_images"] = instance_image
         example["instance_images"] = self.image_transforms(instance_image)
@@ -327,6 +333,7 @@ class DreamBoothDataset(Dataset):
             class_image = Image.open(self.class_images_path[index % self.num_class_images])
             if not class_image.mode == "RGB":
                 class_image = class_image.convert("RGB")
+            class_image = self.image_transforms_resize_and_crop(class_image)
             example["class_images"] = self.image_transforms(class_image)
             example["class_PIL_images"] = class_image
             example["class_prompt_ids"] = self.tokenizer(
@@ -513,12 +520,6 @@ def main():
     )
 
     def collate_fn(examples):
-        image_transforms = transforms.Compose(
-            [
-                transforms.Resize(args.resolution, interpolation=transforms.InterpolationMode.BILINEAR),
-                transforms.CenterCrop(args.resolution) if args.center_crop else transforms.RandomCrop(args.resolution),
-            ]
-        )
         input_ids = [example["instance_prompt_ids"] for example in examples]
         pixel_values = [example["instance_images"] for example in examples]
 
@@ -535,9 +536,6 @@ def main():
             pil_image = example["PIL_images"]
             # generate a random mask
             mask = random_mask(pil_image.size, 1, False)
-            # apply transforms
-            mask = image_transforms(mask)
-            pil_image = image_transforms(pil_image)
             # prepare mask and masked image
             mask, masked_image = prepare_mask_and_masked_image(pil_image, mask)
 
@@ -548,9 +546,6 @@ def main():
             for pil_image in pior_pil:
                 # generate a random mask
                 mask = random_mask(pil_image.size, 1, False)
-                # apply transforms
-                mask = image_transforms(mask)
-                pil_image = image_transforms(pil_image)
                 # prepare mask and masked image
                 mask, masked_image = prepare_mask_and_masked_image(pil_image, mask)