Fixed issue with offloading text encoder on ltx 2.5

extensions_built_in/diffusion_models/ltx2/ltx2.py

@@ -1536,11 +1536,16 @@ class LTX25Model(LTX2Model):
             self.model_config.layer_offloading
             and self.model_config.layer_offloading_text_encoder_percent > 0
         ):
+            # layer_scalar is a bare tensor buffer on each decoder layer; the
+            # manager never enumerates it, so it must ride along explicitly
+            ignore_modules = [text_encoder.embed_tokens]
+            for layer in text_encoder.layers:
+                ignore_modules.append(layer.layer_scalar)
             MemoryManager.attach(
                 text_encoder,
                 self.device_torch,
                 offload_percent=self.model_config.layer_offloading_text_encoder_percent,
-                ignore_modules=[text_encoder.embed_tokens],
+                ignore_modules=ignore_modules,
             )
 
         text_encoder.to(self.device_torch)

toolkit/memory_management/manager.py

@@ -56,8 +56,8 @@ class MemoryManager:
     def memory_managed_to(self, *args, **kwargs):
         # first move all the unmanaged modules
         for module in self.unmanaged_modules:
-            if isinstance(module, torch.nn.Parameter):
-                # Parameter cannot move this way
+            if isinstance(module, torch.Tensor):
+                # Parameters and bare tensor buffers cannot move this way
                 module.data = module.data.to(*args, **kwargs)
             else:
                 module.to(*args, **kwargs)
@@ -181,7 +181,7 @@ class MemoryManager:
 
         for unmanaged in module._memory_manager.unmanaged_modules:
             try:
-                if isinstance(unmanaged, torch.nn.Parameter):
+                if isinstance(unmanaged, torch.Tensor):
                     unmanaged.data = unmanaged.data.to('cpu')
                 else:
                     unmanaged.to('cpu')