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⚡ Bolt: Remove HashMap allocation in repetition penalty#3506

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EffortlessSteven wants to merge 2 commits intomainfrom
bolt/remove-hashmap-allocation-9867502972988120625
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⚡ Bolt: Remove HashMap allocation in repetition penalty#3506
EffortlessSteven wants to merge 2 commits intomainfrom
bolt/remove-hashmap-allocation-9867502972988120625

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@EffortlessSteven
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💡 What

Replaced the HashMap<usize, usize> used for tracking repetition counts in SamplingStrategy with a pre-allocated chronological Vec<u32>. Changed apply_repetition_penalty to use this history slice directly instead of dynamically generating a new vector using flat_map and repeat_n on every token.

🎯 Why

Token generation is the tightest hot loop in LLM inference. Allocating new vectors and performing HashMap lookups/updates for every sampled token introduces significant overhead. The underlying mathematics of bitnet_logits::apply_repetition_penalty apply the exponential penalty for every token present in the history slice, so passing a chronologically accurate Vec<u32> has identical mathematical behavior without requiring HashMap accounting or per-token vector materialization.

📊 Impact

  • Eliminates one HashMap insertion per generated token.
  • Eliminates one vocabulary-sized Vec<u32> allocation and expansion loop per generated token.
  • Amortizes cleanup cost by using a 2000-token threshold sliding window (drain), improving semantic stability over the previous hard clear() approach.

🔬 Measurement

Verified the logic using existing tests, which passed immediately after applying changes.
Run: cargo test -p bitnet-inference --lib generation::sampling


PR created automatically by Jules for task 9867502972988120625 started by @EffortlessSteven

- Replaced `HashMap` in `SamplingStrategy` with a `Vec<u32>`
- Eliminated per-token memory allocation in `apply_repetition_penalty`
- Used sliding window with `drain` to prevent memory growth
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