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

LTX-Video/ltx_video/pipelines/pipeline_ltx_video.py

@@ -199,11 +199,10 @@ def retrieve_timesteps(
         scheduler.set_timesteps(timesteps=timesteps, device=device, **kwargs)
         num_inference_steps = len(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}")
+        try:
+            print(f"[LTX]LATENTS {latents.shape}")
+        except Exception:
+                pass
  
 
     return timesteps, num_inference_steps
@@ -900,11 +899,11 @@ class LTXVideoPipeline(DiffusionPipeline):
                 returned where the first element is a list with the generated images
         """
         
-        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}")
-        
+        try:
+            print(f"[LTX]LATENTS {latents.shape}")
+        except Exception:
+            pass
+ 
         
         if "mask_feature" in kwargs:
             deprecation_message = "The use of `mask_feature` is deprecated. It is no longer used in any computation and that doesn't affect the end results. It will be removed in a future version."
@@ -974,11 +973,11 @@ class LTXVideoPipeline(DiffusionPipeline):
             **retrieve_timesteps_kwargs,
         )
         
-        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}")
-
+        try:
+            print(f"[LTX2]LATENTS {latents.shape}")
+        except Exception:
+            pass
+            
         if self.allowed_inference_steps is not None:
             for timestep in [round(x, 4) for x in timesteps.tolist()]:
                 assert (
@@ -1047,11 +1046,11 @@ class LTXVideoPipeline(DiffusionPipeline):
                 max_new_tokens=text_encoder_max_tokens,
             )
             
-        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}")
-        
+        try:
+            print(f"[LTX3]LATENTS {latents.shape}")
+        except Exception:
+            pass
+            
         # 3. Encode input prompt
         if self.text_encoder is not None:
             self.text_encoder = self.text_encoder.to(self._execution_device)
@@ -1118,11 +1117,10 @@ 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}")
-        
+        try:
+            print(f"[LTX4]LATENTS {latents.shape}")
+        except Exception:
+            pass        
 
         # Update the latents with the conditioning items and patchify them into (b, n, c)
         latents, pixel_coords, conditioning_mask, num_cond_latents = (
@@ -1140,18 +1138,16 @@ 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}")
+        
         # 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)
 
 
-        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}")
+        try:
+            print(f"[LTX5]LATENTS {latents.shape}")
+        except Exception:
+            pass
+        
         # 7. Denoising loop
         num_warmup_steps = max(
             len(timesteps) - num_inference_steps * self.scheduler.order, 0
@@ -1344,11 +1340,11 @@ 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}")
-      
+        try:
+            print(f"[LTX6]LATENTS {latents.shape}")
+        except Exception:
+            pass
+            
         if offload_to_cpu:
             self.transformer = self.transformer.cpu()
             if self._execution_device == "cuda":