[Core][V1] Support sharded state loading

[aarnphm]

This PR removes the oracles check for sharded state for v1.

However, it seems like the save sharded weights doesn't work with fp8 checkpoint (I tested with qwen3-235b-a22b) but after removing some of the exception with debug, the models weights seems to be loaded correctly.
So I added a strict options to --model-loader-extra-config to lax these checks for fp8 checkpoint.

I think this would be a good starting point before adding specific code path for loading quantized weights.

I'm currently in the progress of debugging this, but this should halves the loading time comparing with the default safetensors implementations.

Signed-off-by: Aaron Pham [email protected]

[gemini-code-assist]

Summary of Changes

Hello @aarnphm, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request primarily focuses on enabling and enhancing the flexibility of sharded state loading within the v1 engine. By removing a previous restriction and introducing a configurable 'strict' mode for the model loader, it aims to facilitate faster and more robust model loading, particularly for checkpoint formats that might not perfectly align with the expected state dictionary.

Highlights

• Sharded State Loading Enabled for V1 Engine: I have removed the explicit check in vllm/engine/arg_utils.py that previously prevented the v1 engine from utilizing sharded state loading. This change enables the use of sharded state for faster model loading.
• Flexible Checkpoint Loading with 'strict' Option: I introduced a new strict option to the ShardedStateLoader in vllm/model_executor/model_loader/sharded_state_loader.py. This option, configurable via --model-loader-extra-config, allows the loader to proceed even if some keys are missing from the loaded state dictionary when strict is set to False. This addresses issues with certain checkpoint types, such as FP8, that might have discrepancies.
• Improved Error Handling for Missing Keys: The load_weights method in sharded_state_loader.py now conditionally raises a ValueError for missing keys based on the strict flag. If strict is False, missing keys are logged at debug level instead of immediately raising an error, providing more flexibility during model loading.

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[gemini-code-assist]

Code Review

This pull request introduces sharded state loading for the v1 engine, enhancing loading performance. It also adds a strict loading option to handle incomplete checkpoints during debugging. I suggest changing the logging level for missing keys from debug to warning when not in strict mode to improve user awareness of potential loading issues.

[github-actions]

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