Set LANCZOS as the default interpolation method for image resizing. (#11492)

* Set LANCZOS as the default interpolation method for image resizing.

* style: run make style and quality checks

examples/advanced_diffusion_training/train_dreambooth_lora_sd15_advanced.py

@@ -673,6 +673,15 @@ def parse_args(input_args=None):
         default=False,
         help="Cache the VAE latents",
     )
+    parser.add_argument(
+        "--image_interpolation_mode",
+        type=str,
+        default="lanczos",
+        choices=[
+            f.lower() for f in dir(transforms.InterpolationMode) if not f.startswith("__") and not f.endswith("__")
+        ],
+        help="The image interpolation method to use for resizing images.",
+    )
 
     if input_args is not None:
         args = parser.parse_args(input_args)
@@ -907,6 +916,10 @@ class DreamBoothDataset(Dataset):
         self.num_instance_images = len(self.instance_images)
         self._length = self.num_instance_images
 
+        interpolation = getattr(transforms.InterpolationMode, args.image_interpolation_mode.upper(), None)
+        if interpolation is None:
+            raise ValueError(f"Unsupported interpolation mode {interpolation=}.")
+
         if class_data_root is not None:
             self.class_data_root = Path(class_data_root)
             self.class_data_root.mkdir(parents=True, exist_ok=True)
@@ -921,7 +934,7 @@ class DreamBoothDataset(Dataset):
 
         self.image_transforms = transforms.Compose(
             [
-                transforms.Resize(size, interpolation=transforms.InterpolationMode.BILINEAR),
+                transforms.Resize(size, interpolation=interpolation),
                 transforms.CenterCrop(size) if center_crop else transforms.RandomCrop(size),
                 transforms.ToTensor(),
                 transforms.Normalize([0.5], [0.5]),