remove printing of latent shape

cosmos_transfer1/diffusion/inference/world_generation_pipeline.py

@@ -553,7 +553,6 @@ class DiffusionControl2WorldGenerationPipeline(BaseWorldGenerationPipeline):
             end_frame = num_new_generated_frames * (i_clip + 1) + self.num_input_frames
 
             # Prepare x_sigma_max
-            print("==============================================================")
             if input_video is not None:
                 if is_upscale_case:
                     x_sigma_max = []
@@ -573,8 +572,6 @@ class DiffusionControl2WorldGenerationPipeline(BaseWorldGenerationPipeline):
 
             else:
                 x_sigma_max = None
-            print("final ->", x_sigma_max.shape)
-            print("==============================================================")
 
             data_batch_i[hint_key] = control_input[:, :, start_frame:end_frame].cuda()
             latent_hint = []

cosmos_transfer1/diffusion/model/model_t2w.py

@@ -177,9 +177,6 @@ class DiffusionT2WModel(torch.nn.Module):
                 noise prediction (eps_pred) and optional confidence (logvar).
         """
 
-        print("<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<")
-        print(xt.shape)
-        print("<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<")
         xt = xt.to(**self.tensor_kwargs)
         sigma = sigma.to(**self.tensor_kwargs)
         # get precondition for the network