Update LTX-Video/ltx_video/pipelines/pipeline_ltx_video.py

LTX-Video/ltx_video/pipelines/pipeline_ltx_video.py

@@ -57,7 +57,7 @@ logging.set_verbosity_info()
 logging.set_verbosity_debug()
 
 
-logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
+#logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
 
 
 ASPECT_RATIO_1024_BIN = {
@@ -203,7 +203,7 @@ def retrieve_timesteps(
         print(f"[ADUC DEBUG LTX *causal_video_autoencoder.py*]=======")
         print(f"skip_initial_inference_steps {skip_initial_inference_steps}")
         print(f"skip_final_inference_steps {skip_final_inference_steps}")
-        print(f"timesteps {timesteps}")
+       # print(f"timesteps {timesteps}")
  
 
     return timesteps, num_inference_steps
@@ -403,10 +403,10 @@ class LTXVideoPipeline(DiffusionPipeline):
                 removed_text = self.tokenizer.batch_decode(
                     untruncated_ids[:, max_length - 1 : -1]
                 )
-                logger.warning(
-                    "The following part of your input was truncated because CLIP can only handle sequences up to"
-                    f" {max_length} tokens: {removed_text}"
-                )
+                #logger.warning(
+                #    "The following part of your input was truncated because CLIP can only handle sequences up to"
+                #    f" {max_length} tokens: {removed_text}"
+                #)
 
             prompt_attention_mask = text_inputs.attention_mask
             prompt_attention_mask = prompt_attention_mask.to(text_enc_device)
@@ -903,7 +903,7 @@ class LTXVideoPipeline(DiffusionPipeline):
         print(f"[1ADUC DEBUG LTX *causal_video_autoencoder.py*]=======")
         print(f"skip_initial_inference_steps {skip_initial_inference_steps}")
         print(f"skip_final_inference_steps {skip_final_inference_steps}")
-        print(f"latents {latents.shape}")
+        #print(f"latents {latents.shape}")
         
         
         if "mask_feature" in kwargs:
@@ -977,7 +977,7 @@ class LTXVideoPipeline(DiffusionPipeline):
         print(f"[2ADUC DEBUG LTX *causal_video_autoencoder.py*]=======")
         print(f"skip_initial_inference_steps {skip_initial_inference_steps}")
         print(f"skip_final_inference_steps {skip_final_inference_steps}")
-        print(f"latents {latents.shape}")
+        #print(f"latents {latents.shape}")
 
         if self.allowed_inference_steps is not None:
             for timestep in [round(x, 4) for x in timesteps.tolist()]:
@@ -1050,7 +1050,7 @@ class LTXVideoPipeline(DiffusionPipeline):
         print(f"[4ADUC DEBUG LTX *causal_video_autoencoder.py*]=======")
         print(f"skip_initial_inference_steps {skip_initial_inference_steps}")
         print(f"skip_final_inference_steps {skip_final_inference_steps}")
-        print(f"latents {latents.shape}")
+        #print(f"latents {latents.shape}")
         
         # 3. Encode input prompt
         if self.text_encoder is not None:
@@ -1121,7 +1121,7 @@ class LTXVideoPipeline(DiffusionPipeline):
         print(f"[5ADUC DEBUG LTX *causal_video_autoencoder.py*]=======")
         print(f"skip_initial_inference_steps {skip_initial_inference_steps}")
         print(f"skip_final_inference_steps {skip_final_inference_steps}")
-        print(f"latents {latents.shape}")
+        #print(f"latents {latents.shape}")
         
 
         # Update the latents with the conditioning items and patchify them into (b, n, c)
@@ -1143,7 +1143,7 @@ class LTXVideoPipeline(DiffusionPipeline):
         print(f"[6ADUC DEBUG LTX *causal_video_autoencoder.py*]=======")
         print(f"skip_initial_inference_steps {skip_initial_inference_steps}")
         print(f"skip_final_inference_steps {skip_final_inference_steps}")
-        print(f"latents {latents.shape}")
+        #print(f"latents {latents.shape}")
         # 6. Prepare extra step kwargs. TODO: Logic should ideally just be moved out of the pipeline
         extra_step_kwargs = self.prepare_extra_step_kwargs(generator, eta)
 
@@ -1151,7 +1151,7 @@ class LTXVideoPipeline(DiffusionPipeline):
         print(f"[7ADUC DEBUG LTX *causal_video_autoencoder.py*]=======")
         print(f"skip_initial_inference_steps {skip_initial_inference_steps}")
         print(f"skip_final_inference_steps {skip_final_inference_steps}")
-        print(f"latents {latents.shape}")
+        #print(f"latents {latents.shape}")
         # 7. Denoising loop
         num_warmup_steps = max(
             len(timesteps) - num_inference_steps * self.scheduler.order, 0
@@ -1347,7 +1347,7 @@ class LTXVideoPipeline(DiffusionPipeline):
         print(f"[8ADUC DEBUG LTX *causal_video_autoencoder.py*]=======")
         print(f"skip_initial_inference_steps {skip_initial_inference_steps}")
         print(f"skip_final_inference_steps {skip_final_inference_steps}")
-        print(f"latents {latents.shape}")
+        #print(f"latents {latents.shape}")
       
           if offload_to_cpu:
             self.transformer = self.transformer.cpu()