fix missing enable_pdl argument in trtllm-gen fp4 moe

[IwakuraRein]

📌 Description

Fix the missing enable_pdl argument introduced in #1446 .

🔍 Related Issues

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Reviewer Notes

[gemini-code-assist]

Summary of Changes

Hello @IwakuraRein, 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 addresses a regression introduced in a previous change by adding the enable_pdl argument to several Mixture-of-Experts (MoE) related function signatures within flashinfer/fused_moe/core.py. This ensures that the enable_pdl argument is properly propagated and utilized for trtllm-gen fp4 moe operations, resolving a missing argument issue.

Highlights

• Function Signature Update: The enable_pdl: Optional[bool] = None argument was added to the signature of the _fake_cutlass_fused_moe_sm100 function.
• Function Signature Update: The enable_pdl: Optional[bool] = None argument was added to the signature of the _fake_trtllm_fp8_per_tensor_scale_moe function.
• Function Signature Update: The enable_pdl: Optional[bool] = None argument was added to the signature of the _fake_trtllm_fp8_block_scale_moe function.
• Function Signature Update: The enable_pdl: Optional[bool] and output: Optional[torch.Tensor] arguments were added to the signature of the _fake_trtllm_fp4_block_scale_moe function.
• Function Signature Update: The enable_pdl: Optional[bool] = None and output: Optional[torch.Tensor] = None arguments were added to the signature of the trtllm_fp4_block_scale_moe function.
• Argument Propagation Fix: The enable_pdl argument is now correctly passed from trtllm_fp4_block_scale_moe to its internal call to _fake_trtllm_fp4_block_scale_moe.

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[gemini-code-assist]

Code Review

This pull request correctly adds the missing enable_pdl argument to several fused MoE functions, ensuring it's propagated as intended. The changes are straightforward and address the issue described. I've pointed out one minor issue in a fake operator's signature where default values for new arguments are missing, which could cause issues with torch.compile.