[TorchAcc] Update padding strategy when using persistent cache #2464
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anw90
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Nov 18, 2024
swift/torchacc_utils.py
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| @@ -30,6 +30,15 @@ def get_bucket_sizes(max_length: int) -> List[int]: | |||
| if os.getenv('TORCHACC_DATA_BUCKETS') is not None: | |||
| bucket_sizes = [int(x) for x in os.getenv('TORCHACC_DATA_BUCKETS').split(',')] | |||
| bucket_sizes.append(max_length) | |||
| elif os.getenv('TORCHACC_CACHE_PATH') is not None: # padding strategy when persistent cache is enabled | |||
| p = 1.4 | |||
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Maybe we could add an environment variable for the p.
swift/torchacc_utils.py
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| @@ -30,6 +30,15 @@ def get_bucket_sizes(max_length: int) -> List[int]: | |||
| if os.getenv('TORCHACC_DATA_BUCKETS') is not None: | |||
| bucket_sizes = [int(x) for x in os.getenv('TORCHACC_DATA_BUCKETS').split(',')] | |||
| bucket_sizes.append(max_length) | |||
| elif os.getenv('TORCHACC_CACHE_PATH') is not None: # padding strategy when persistent cache is enabled | |||
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Could we replace the else block with this logic as defualt bucketing strategy?
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…actor3 * commit '2bbc325ca789592197d2004bb0ffc47cc39c0317': (140 commits) fix fix update safe_ddp_context fix fix update row_processor support glm-edge & glm-edge-v (#2526) fix open-o1 support qwq-32b-preview (#2520) support mPLUG-Owl3 241101 (#2515) fix latex-ocr (#2510) support batch flattening collator (#2499) fix eval_dataset no (#2497) Support marco o1 (#2496) Fix preprocess num proc (#2492) fix awq quant device_map (#2488) Update Common QA (#2475) fix kto (#2478) update padding strategy for persistent cache (#2464) fix qwen2vl pt infer (#2463) ... # Conflicts: # docs/source/Instruction/命令行参数.md # docs/source/LLM/人类偏好对齐训练文档.md # docs/source/Multi-Modal/index.md # docs/source/Multi-Modal/qwen2-vl最佳实践.md # docs/source/Multi-Modal/人类偏好对齐训练文档.md # docs/source_en/Instruction/Command-line-parameters.md # docs/source_en/Instruction/Common-QA.md # docs/source_en/LLM/Human-Preference-Alignment-Training-Documentation.md # docs/source_en/Multi-Modal/qwen2-vl-best-practice.md
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PR type
PR information
Optimize padding strategy when persistent cache is enabled, so we can enjoy performance boost with little extra compilaiton.
Experiment results
Around 10% e2e performance improvement for TorchAcc backend.