harry900000 commited on
Commit
1e9a1ec
·
1 Parent(s): 817cd1e

remove printing of latent shape

Browse files
cosmos_transfer1/diffusion/inference/world_generation_pipeline.py CHANGED
@@ -553,7 +553,6 @@ class DiffusionControl2WorldGenerationPipeline(BaseWorldGenerationPipeline):
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  end_frame = num_new_generated_frames * (i_clip + 1) + self.num_input_frames
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  # Prepare x_sigma_max
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- print("==============================================================")
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  if input_video is not None:
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  if is_upscale_case:
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  x_sigma_max = []
@@ -573,8 +572,6 @@ class DiffusionControl2WorldGenerationPipeline(BaseWorldGenerationPipeline):
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  else:
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  x_sigma_max = None
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- print("final ->", x_sigma_max.shape)
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- print("==============================================================")
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  data_batch_i[hint_key] = control_input[:, :, start_frame:end_frame].cuda()
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  latent_hint = []
 
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  end_frame = num_new_generated_frames * (i_clip + 1) + self.num_input_frames
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  # Prepare x_sigma_max
 
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  if input_video is not None:
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  if is_upscale_case:
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  x_sigma_max = []
 
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  else:
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  x_sigma_max = None
 
 
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  data_batch_i[hint_key] = control_input[:, :, start_frame:end_frame].cuda()
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  latent_hint = []
cosmos_transfer1/diffusion/model/model_t2w.py CHANGED
@@ -177,9 +177,6 @@ class DiffusionT2WModel(torch.nn.Module):
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  noise prediction (eps_pred) and optional confidence (logvar).
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  """
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- print("<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<")
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- print(xt.shape)
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- print("<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<")
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  xt = xt.to(**self.tensor_kwargs)
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  sigma = sigma.to(**self.tensor_kwargs)
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  # get precondition for the network
 
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  noise prediction (eps_pred) and optional confidence (logvar).
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  """
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  xt = xt.to(**self.tensor_kwargs)
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  sigma = sigma.to(**self.tensor_kwargs)
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  # get precondition for the network