[fix] Handle transposed w13_weight

[gjsheu]

In a latest PR within the sglang repository, layer.w13_weight was transposed. This PR is intended to adapt to those changes.

[gemini-code-assist]

Summary of Changes

Hello @gjsheu, 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 provides a critical fix to adapt the sgl_kernel_npu module to a recent change in the sglang repository where the layer.w13_weight tensor was transposed. The changes ensure that the swiglu_oai functions correctly interpret the dimensions of w13_weight, preventing potential runtime errors and maintaining compatibility with the updated tensor structure.

Highlights

• w13_weight dimension handling: Adjusted the unpacking of layer.w13_weight.size() in swiglu_oai_native to correctly account for a transposed w13_weight, changing E, N, _ to E, _, N.
• w13_weight shape access: Modified the index used to access layer.w13_weight.shape from [1] to [2] when passing the dimension to swiglu_oai_triton, aligning with the new w13_weight transposition.

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[gemini-code-assist]

Code Review

This pull request correctly adapts to the transposed w13_weight by updating the dimension indexing in swiglu_oai_native and swiglu_oai. The changes appear correct. I've added a couple of suggestions to improve code clarity and maintainability by handling an unused variable and avoiding a magic number.