Repository: huggingface/transformers
Pull request: 43125: Ensure correct checkpoint saving behavior by simplifying Trainer.save_model parallelism logic

# What does this PR do?

This PR improves the correctness and robustness of model checkpoint saving by removing a redundant parallelism_config branch from Trainer.save_model().

The removed logic attempted to special-case checkpoint saving whenever accelerator.parallelism_config was present. In practice, this routing was unnecessary and error-prone, as checkpointing behavior for supported parallelism strategies (FSDP, DeepSpeed, tensor parallelism) is already handled by their respective, dedicated code paths.

As discussed in the linked issue, the presence of this branch could intercept the save flow prematurely, leading to incorrect save semantics—particularly in configurations involving FSDP—by invoking a generic _save() path instead of the required backend-specific logic.

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Fixes #43125 


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@SunMarc 

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Changed files:
filename: src/transformers/trainer.py
patch: @@ -4008,15 +4008,6 @@ def save_model(self, output_dir: str | None = None, _internal_call: bool = False
             if self.args.should_save:
                 self._save(output_dir, state_dict=state_dict)
             Path(os.path.join(output_dir, "user_content.pt")).touch()
-        # We are in N-D parallelism if we have parallelism_config set, so we check accelerate if we're on a to_save rank
-        elif getattr(self.accelerator, "parallelism_config", None) is not None:
-            # DeepSpeed SP already handles checkpoint saving below, so skip manual save in that case
-            pc = getattr(self.accelerator, "parallelism_config")
-            if self.accelerator.should_save_model and not (pc.sp_enabled and pc.sp_backend == "deepspeed"):
-                self._save(output_dir)
-        # If we drop to here, we're in 1D parallelism, so all ranks need to go to `save_pretrained`
-        elif (tp_size := getattr(self.model, "_tp_size", 0)) is not None and tp_size > 1:
-            self._save(output_dir)
         elif self.is_fsdp_enabled:
             if "FULL_STATE_DICT" in str(self.accelerator.state.fsdp_plugin.state_dict_type):
                 state_dict = self.accelerator.get_state_dict(self.model)