fixes

hyvideo/diffusion/pipelines/pipeline_hunyuan_video.py

@@ -742,7 +742,7 @@ class HunyuanVideoPipeline(DiffusionPipeline):
             self.transformer.slg_start_percent = slg_args["start_percent"]
             self.transformer.slg_end_percent = slg_args["end_percent"]
         else:
-            self.transformer.slg_blocks = None
+            self.transformer.slg_single_blocks = self.transformer.slg_double_blocks = None
         
         logger.info(f"Sampling {video_length} frames in {latents.shape[2]} latents at {width}x{height} with {len(timesteps)} inference steps")
     

hyvideo/modules/models.py

@@ -760,8 +760,6 @@ class HYVideoDiffusionTransformer(ModelMixin, ConfigMixin):
         self.accumulated_rel_l1_distance = 0
         self.previous_modulated_input = None
         self.previous_residual = None
-        self.last_dimensions = None
-        self.last_frame_count = None
         self.teacache_device = None
 
         self.slg_single_blocks = None
@@ -1168,12 +1166,6 @@ class HYVideoDiffusionTransformer(ModelMixin, ConfigMixin):
                     self.teacache_skipped_steps_uncond += 1
                 else:
                     self.teacache_skipped_steps_cond += 1
-                
-                # Verify tensor dimensions match before adding
-                if img.shape == previous_residual.shape:
-                    img = img + previous_residual.to(img.device)
-                else:
-                    should_calc = True # Force recalculation if dimensions don't match
 
             if should_calc:
                 ori_img = img.clone()

nodes.py

@@ -1419,23 +1419,15 @@ class HyVideoSampler:
 
         # Initialize TeaCache if enabled
         if teacache_args is not None:
-            # Check if dimensions have changed since last run
-            if (not hasattr(transformer, 'last_dimensions') or
-                    transformer.last_dimensions != (height, width, num_frames) or
-                    not hasattr(transformer, 'last_frame_count') or
-                    transformer.last_frame_count != num_frames):
-                # Reset TeaCache state on dimension change
-                transformer.cnt = 0
-                transformer.teacache_skipped_steps_cond = 0
-                transformer.teacache_skipped_steps_uncond = 0
-                transformer.accumulated_rel_l1_distance = 0
-                transformer.previous_modulated_input = None
-                transformer.previous_residual = None
-                transformer.last_dimensions = (height, width, num_frames)
-                transformer.last_frame_count = num_frames
-                transformer.teacache_device = device
-                transformer.teacache_start_step = 0
-                transformer.teacache_end_step = steps - 1
+            transformer.cnt = 0
+            transformer.teacache_skipped_steps_cond = 0
+            transformer.teacache_skipped_steps_uncond = 0
+            transformer.accumulated_rel_l1_distance = 0
+            transformer.previous_modulated_input = None
+            transformer.previous_residual = None
+            transformer.teacache_device = device
+            transformer.teacache_start_step = 0
+            transformer.teacache_end_step = steps - 1
 
             transformer.enable_teacache = True
             transformer.num_steps = steps