fix(easy/rainbow-table): align hash helpers with uint32 iterative semantics#237
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agicy wants to merge 1 commit intoAlphaGPU:mainfrom
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fix(easy/rainbow-table): align hash helpers with uint32 iterative semantics#237agicy wants to merge 1 commit intoAlphaGPU:mainfrom
agicy wants to merge 1 commit intoAlphaGPU:mainfrom
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…tive semantics The FNV-1a hash is applied iteratively R times, so the helper's input and output must be consistently typed as unsigned 32-bit integers. - CUDA: change `fnv1a_hash` input to `unsigned int` and mask to `0xFFu` - Mojo: change `fnv1a_hash` input/mask to `UInt32` - JAX/CuTe: remove internal casting so the helper expects normalized state - PyTorch/Triton: left unchanged due to framework specific constraints Resolves AlphaGPU#214
agicy
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ishaan-arya,
kunal-mansukhani and
shxjames
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Summary
Resolves #214.
The Rainbow Table challenge requires R rounds of iterative hashing, meaning the output of one round feeds directly into the next. Several starter templates previously declared their
fnv1a_hashhelpers with signed integers or performed internal type casting, creating an inconsistent internal state.This PR ensures the hash helpers consistently operate on unsigned 32-bit integers, leaving initial type normalization to the caller.
Changes
fnv1a_hash(int input)tounsigned int. Used0xFFu.fnv1a_hash(input: Int32)toUInt32.astype/cute.Uint32) from the helper body. Added Python type hints to CuTe.(Note: PyTorch uses
int64to bypass missinguint32bitwise op support in the framework. Triton remains untyped per Triton DSL conventions. Both are left unchanged.)