wandb request pil image Type

Author: --unset

examples/cogvideo/train_cogvideox_lora.py

@@ -46,6 +46,7 @@
 from torchvision.transforms import InterpolationMode
 import torchvision.transforms as TT
 import numpy as np
+from diffusers.image_processor import VaeImageProcessor
 
 
 if is_wandb_available():
@@ -740,8 +741,13 @@ def log_validation(
 
     videos = []
     for _ in range(args.num_validation_videos):
-        video = pipe(**pipeline_args, generator=generator, output_type="np").frames[0]
-        videos.append(video)
+        pt_images = pipe(**pipeline_args, generator=generator, output_type="pt").frames[0]
+        pt_images = torch.stack([pt_images[i] for i in range(pt_images.shape[0])])
+
+        image_np = VaeImageProcessor.pt_to_numpy(pt_images)
+        image_pil = VaeImageProcessor.numpy_to_pil(image_np)
+
+        videos.append(image_pil)
 
     for tracker in accelerator.trackers:
         phase_name = "test" if is_final_validation else "validation"