[Cherry-Pick][RL][BugFix][Optimization] Support chunked part files loading and fix model path format in IPC snapshot strategy(#6852)

[wikilsh]

Motivation

Cherry-pick from develop branch PR #6852 to release/2.4.

In RL training elastic recovery via IPC snapshot, two issues existed in _update_ipc_snapshot:

1. Memory spike: Loading a single large .pdparams file in one shot causes a significant memory spike, risking OOM during recovery.
2. Ambiguous file naming: The snapshot path used model_state.tp{rank}{id} without a separator between rank and id, causing naming ambiguity (e.g., rank=1, id=234 and rank=12, id=34 both produce tp1234). Additionally, the rank was previously hardcoded as tp0, causing all ranks to load rank-0's shard in multi-process scenarios.

Modifications

Refactored _update_ipc_snapshot in fastdeploy/rl/dynamic_weight_manager.py with a four-level loading priority:

1. Chunked part files (model_state.tp{rank}.{id}.part{N}.pdparams): Load multiple smaller shards sequentially in ascending numeric order, releasing memory between each chunk via gc.collect() to avoid memory spike.
2. Single full file (model_state.tp{rank}.{id}.pdparams): Standard single-file loading with corrected naming format (dot separator added).
3. Legacy format fallback (model_state.tp0{id}.pdparams): Backward-compatible fallback for checkpoints saved in the old format, ensuring smooth rolling upgrades.
4. Shared directory fallback (/shared_ipc_meta/...): Oldest legacy fallback path preserved for compatibility.

Key fixes:

• Add dot separator in snapshot file name: tp{rank}{id} → tp{rank}.{id} to eliminate naming ambiguity
• Replace hardcoded tp0 with paddle.distributed.get_rank() so each rank loads its own shard correctly
• Add legacy format (Priority 3) as a transitional fallback to avoid load failures on existing checkpoints
• Raise FileNotFoundError with clear message when no snapshot is found in any candidate path

Usage or Command

During RL elastic recovery, the trainer will automatically select the appropriate loading strategy based on available snapshot files. No additional configuration is needed.

To generate chunked part files on the trainer side, split the full state dict and save as:
model_state.tp{rank}.{id}.part0.pdparams
model_state.tp{rank}.{id}.part1.pdparams
...

Accuracy Tests

This PR only modifies the weight loading path and chunking strategy in _update_ipc_snapshot. It does not affect model forward computation or kernel logic. No accuracy regression is expected.

Checklist

• Add at least a tag in the PR title.
• Format your code, run pre-commit before commit.
• Add unit tests. Please write the reason in this PR if no unit tests.

  Added tests/rl/test_update_ipc_snapshot.py covering all 4 loading priority branches and the error path.

• Provide accuracy results.
• If the current PR is submitting to the release branch, make sure the PR has been submitted to the develop branch, then cherry-pick it to the release branch with the [Cherry-Pick] PR tag.

  Original PR: [RL][BugFix][Optimization] Support chunked part files loading and fix model path format in IPC snapshot strategy #6852

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Codecov Report

❌ Patch coverage is 85.18519% with 8 lines in your changes missing coverage. Please review.
⚠️ Please upload report for BASE (release/2.4@7f5f211). Learn more about missing BASE report.

Files with missing lines	Patch %	Lines
fastdeploy/rl/dynamic_weight_manager.py	85.18%	6 Missing and 2 partials ⚠️

Additional details and impacted files

@@              Coverage Diff               @@
##             release/2.4    #6909   +/-   ##
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  Files                  ?      333           
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  Hits                   ?    23997           
  Misses                 ?    16673           
  Partials               ?     1883           

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