fix(llama4): honour skip_logits in lce_forward

[yupengtang]

Summary

llama4.lce_forward is the only one of the 42 forwards under transformers/model/ that has no skip_logits parameter. It still decides on its own:

if self.training and (labels is not None or shift_labels is not None):

#704 added skip_logits precisely so a caller could override that, and swept every model that existed on 2025-05-23. llama4 arrived a month later in #740 and never picked it up; everything added since has it.

Because the signature does not name it, a skip_logits argument lands in **kwargs and is silently ignored, so skip_logits=False during training still takes the fused path and returns logits=None. That is the one thing the flag exists to prevent, and the convergence harness relies on it, setting eval_batch["skip_logits"] = False before reading eval_output.logits.

The change mirrors mllama, which has the identical LigerForCausalLMLoss shape. skip_logits=None evaluates to the previous condition, so nothing moves for callers that do not pass it.

Testing Done

New test/transformers/test_llama4.py. Both cases stay on the non-fused branch, so they run without a GPU:

• skip_logits=False in training mode returns logits and a loss. On main this fails: the flag is ignored, the fused path runs, and on a CPU box Triton raises RuntimeError: 0 active drivers. On a GPU box it fails on logits is None instead.

• skip_logits=True with no labels raises ValueError, as it does on every other model. On main this is DID NOT RAISE.

• pytest test/transformers/test_monkey_patch.py test/transformers/test_llama4.py: 65 passed / 1 skipped (63 + the 2 new; the skip is muse_glimmer missing from the installed transformers).

• ruff check . and ruff format --check . with the v0.14.11 pinned in .pre-commit-config.yaml: clean.

Hardware Type: CPU. Ran on transformers 5.9.0 / torch 2.11.0.