Repository: huggingface/transformers
Pull request: more fixes for post-training llama4

# What does this PR do?

Along with the changes in #37319 , these are also needed to train llama4.

The guard on the `past_key_values` cache is because that will be None during training.

this is a LoRA training on Scout
<img width="1787" alt="Screenshot 2025-04-06 at 11 59 57 PM" src="https://github.com/user-attachments/assets/a44b5826-d255-475f-9f86-08dea837246e" />

Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-request),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?
@ArthurZucker @SunMarc
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

<!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @

 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

Models:

- text models: @ArthurZucker
- vision models: @amyeroberts, @qubvel
- speech models: @eustlb
- graph models: @clefourrier

Library:

- flax: @gante and @Rocketknight1
- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- pipelines: @Rocketknight1
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @zach-huggingface and @SunMarc
- chat templates: @Rocketknight1

Integrations:

- deepspeed: HF Trainer/Accelerate: @SunMarc @zach-huggingface
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc @MekkCyber

Documentation: @stevhliu

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @Rocketknight1
- PyTorch: See Models above and tag the person corresponding to the modality of the example.
- TensorFlow: @Rocketknight1

 -->


Changed files:
filename: src/transformers/models/llama4/modeling_llama4.py
patch: @@ -730,6 +730,7 @@ def forward(
         )
         return output if return_dict else output.to_tuple()
 
+    @torch.compiler.disable  # the operations in this method are not compilable
     def _update_causal_mask(
         self,
         attention_mask: torch.Tensor,
@@ -767,7 +768,7 @@ def _update_causal_mask(
         )
 
         if past_key_values is not None and past_key_values.is_compileable:
-            target_length = past_key_values.get_max_cache_shape
+            target_length = past_key_values.get_max_cache_shape()
         else:
             target_length = attention_mask.shape[-1] if attention_mask is not None else sequence_length
 
@@ -780,7 +781,7 @@ def _update_causal_mask(
                 attention_mask = make_flex_block_causal_mask(
                     attention_mask,
                     query_length=sequence_length,
-                    key_length=past_key_values.get_max_cache_shape(),
+                    key_length=target_length,
                     offsets=None if sequence_length != 1 else (first_cache_position, 0),
                 )
                 return attention_mask, chunked_attention_mask