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fix: multiple bugs in RoPE cache, data preprocessing, and top-k/top-p filtering - #410
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dajiaohuang wants to merge 2 commits into
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dajiaohuang wants to merge 2 commits into
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… filtering - Fix RotaryPositionalEmbedding cache not invalidating on device/dtype change (prevents device mismatch errors when moving model across devices, per issue shiyu-coder#375) - Fix data preprocessing bug where existing 'amount' column was overwritten with zeros when 'volume' column was missing (both predict() and predict_batch() methods) - Fix top_k_top_p_filtering early return which prevented combining top-k and top-p filtering together
The volume column is guaranteed present by the fill immediately above in both predict() and predict_batch(), so the nested 'if self.vol_col in df.columns' branches are unreachable. Remove them while preserving the computed amount field.
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Summary
amountcolumn whenKronosPredictor.predict()orpredict_batch()fills a missingvolumecolumn.top_kandtop_pintop_k_top_p_filteringwhen both are requested.RotaryPositionalEmbedding.cos_cachedandsin_cachedwhen sequence length, device, or dtype changes, avoiding stale RoPE cache entries during device reuse.The RoPE change addresses only the minor cache/device-reuse code note in #375. It does not resolve the broader evaluation, calibration, ranking, or research questions in that issue.
Validation
Python AST syntax parsing passed for the relevant Python files. No runtime/model behavior, full test-suite, or upstream CI result is claimed here.