'testing'

LICENSE

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2024 Yang Jin
+Copyright (c) 
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

pyramid_dit/pyramid_dit_for_video_gen_pipeline.py

@@ -541,6 +541,7 @@ class PyramidDiTForVideoGeneration:
                 self._video_guidance_scale = guidance_scale_list[unit_index]
 
             if unit_index == 0:
+                # Generate first frame
                 past_condition_latents = [[] for _ in range(len(stages))]
                 intermed_latents = self.generate_one_unit(
                     latents[:,:,:1],
@@ -557,15 +558,17 @@ class PyramidDiTForVideoGeneration:
                     generator,
                     is_first_frame=True,
                 )
+                generated_latents_list.append(intermed_latents[-1])
             else:
-                # prepare the condition latents
-                past_condition_latents = []
-                # if not generated_latents_list or len(generated_latents_list) == 0:
-                #     raise ValueError("No latent tensors generated - check previous steps ")
+                
+                # check if we have previous frames to condition on 
+                if not generated_latents_list or len(generated_latents_list) == 0:
+                    raise ValueError("No latent tensors generated - check previous steps ")
 
-                print(f"know the tensor of generated_latent_list: {generated_latents_list}")
-                print(f"know the len(stages): {len(stages) - 1}")
                 
+                
+                # prepare the condition latents
+                past_condition_latents = []
                 clean_latents_list = self.get_pyramid_latent(torch.cat(generated_latents_list, dim=2), len(stages) - 1)
                 
                 for i_s in range(len(stages)):