Repository: huggingface/transformers
Pull request: remove sequence parallel in llama4

# What does this PR do?

This PR fix the issue #39835 where a `RuntimeError` was triggered due to mixing tensor and Dtensor. This is due to `_prepare_output_fn` being force to returns a tensor instead of Dtensor.

```
    @staticmethod
    def _prepare_output_fn(output_layouts, use_local_output, mod, outputs, device_mesh):
        outputs = outputs.redistribute(
            placements=(Replicate(),), async_op=True
        )  # maybe we have to replicate ? because next layer is not sharded
        return outputs.to_local()
 
```

An easy fix could be to just to return a Dtensor everytime. However, after some discussion, it is better to remove the `SequenceParallel` use for now as it slows down the overall generation.

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Changed files:
filename: src/transformers/models/llama4/configuration_llama4.py
patch: @@ -251,9 +251,6 @@ class Llama4TextConfig(PretrainedConfig):
         "layers.*.self_attn.k_proj": "colwise",
         "layers.*.self_attn.v_proj": "colwise",
         "layers.*.self_attn.o_proj": "rowwise",
-        "layers.*.input_layernorm.weight": "sequence_parallel",
-        "layers.*.post_attention_layernorm.weight": "sequence_parallel",
-        "norm.weight": "sequence_parallel",
         "layers.*.feed_forward.shared_expert.gate_proj": "local_colwise",
         "layers.*.feed_forward.shared_expert.up_proj": "local_colwise",
         "layers.*.feed_forward.shared_expert.down_proj": "local_rowwise",