[WebLLM] Replace int64s with int32s in WebGPU kernels

[akaashrp]

This PR replaces int64s with int32s in the argsort and parallel_sampling_from_prob kernels when the target is WebGPU (since WGSL does not currently support i64)

[gemini-code-assist]

Summary of Changes

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This pull request refactors several GPU kernels, specifically in sampling and sorting routines, to conditionally utilize int32 data types instead of int64 when compiling for WebGPU targets. This modification is crucial for enhancing performance and ensuring broader compatibility on platforms where int64 operations might be less efficient or not fully supported by WebGPU. The changes are implemented with conditional logic, preserving int64 usage for other backend targets.

Highlights

• Conditional Integer Type Casting: The pull request introduces conditional logic to cast int64 types to int32 specifically when the compilation target is WebGPU. This affects variables and operations within sampling and sorting kernels.
• WebGPU Performance and Compatibility: By switching to int32 for WebGPU, the changes aim to improve performance and ensure broader compatibility, as int64 support can be less optimized or problematic on some WebGPU implementations.
• Target-Specific Code Generation: The modifications ensure that int64 types are preserved for other non-WebGPU targets, maintaining existing behavior and performance where int64 is preferred or necessary.

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[gemini-code-assist]

Code Review

This pull request updates WebGPU kernels to use int32 instead of int64, which is a necessary change for WebGPU compatibility. The changes look correct in principle.

My main feedback is about code duplication and repeated logic. In python/tvm/topi/gpu/sort.py, the logic to determine the integer type based on the target is repeated in several places, leading to code duplication. I've suggested refactoring these parts to define the data type once and reuse it. This pattern is already used in one part of the file, so applying it consistently would improve the code. A broader improvement would be to determine the target and dtype once at the top of the _sort_common function.

Similarly, in python/tvm/relax/backend/gpu_generic/sampling.py, the same expression to determine the integer type is repeated. I've left a comment suggesting to abstract this into a variable for better readability and maintainability.