[gpt-oss] flashinfer attention sink init

[zyongye]

No description provided.

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[gemini-code-assist]

Code Review

This pull request introduces support for attention sinks in the FlashInfer backend by adding a sinks parameter to FlashInferImpl. My review focuses on improving the robustness of input validation. The current implementation uses assert statements, which can be disabled in production environments. I've suggested replacing them with explicit checks that raise ValueError for better error handling and consistency with the surrounding code.

[gemini-code-assist]

Using assert for input validation is generally discouraged as assertions can be disabled with the -O flag, which would bypass these checks. It's more robust to use explicit if conditions and raise a ValueError for invalid inputs. This also aligns with the error handling style used elsewhere in this file, such as in FlashInferBackend.validate_head_size.

            if sinks.shape[0] != num_heads:
                raise ValueError(
                    "Sinks must have the same number of heads as the number of "
                    f"heads in the layer. Expected {num_heads}, but got "
                    f"{sinks.shape[0]}."
                )
            if sinks.dtype != torch.float32:
                raise ValueError("Sinks must be of type float32, but got "
                                 f"{sinks.dtype}.")

[WoosukKwon]

I think this suggestion makes sense actually. @zyongye Can you please submit a follow-up PR to add this?