fix: accidentally reassigning tensor to weight

src/axolotl/integrations/cut_cross_entropy/monkeypatch/llama4.py

@@ -26,6 +26,7 @@ from transformers.utils import (
 )
 
 _PATCH_OPTS: PatchOptions | None = None
+RESET_LM_HEAD = True
 
 
 @add_start_docstrings_to_model_forward(LLAMA4_INPUTS_DOCSTRING)
@@ -308,7 +309,16 @@ def cce_forward_multimodal(
 
     if _PATCH_OPTS is not None and _PATCH_OPTS.use_lce(labels, self.training):
         assert labels is not None
-        # TODO: check if need to handle attention_mask
+
+        # reset lm head gradient on first pass.
+        # linear model has some lm_head weight issue
+        # see https://github.com/axolotl-ai-cloud/axolotl/pull/2505
+        global RESET_LM_HEAD  # pylint: disable=global-statement
+        if RESET_LM_HEAD:
+            RESET_LM_HEAD = False
+            self.language_model.lm_head.weight.requires_grad_(False)  # Detach
+            self.language_model.lm_head.weight.requires_grad_(True)  # Reattach
+
         loss = apply_lce(
             hidden_states,
             self.language_model.lm_head.weight,
@@ -373,11 +383,7 @@ def patch_llama4_text(
 
         return maybe_model
 
-    setattr(
+    modeling_llama4.Llama4ForCausalLM.forward = cce_forward
-        modeling_llama4.Llama4ForCausalLM,
-        "forward",
-        cce_forward,
-    )
     return None
 
 
@@ -403,12 +409,8 @@ def patch_llama4(
         )
         return maybe_model
 
-    setattr(
+    modeling_llama4.Llama4ForConditionalGeneration.forward = cce_forward_multimodal
-        modeling_llama4.Llama4ForConditionalGeneration,
-        "forward",
-        cce_forward_multimodal,
-    )
 
     # patch the causal language model
-    setattr(modeling_llama4.Llama4ForCausalLM, "forward", cce_forward)
+    modeling_llama4.Llama4ForCausalLM.forward = cce_forward
     return None