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[zerobubble] rebase main (#6075)
* fp8 operators for compressed communication cast_to_fp8, cast_from_fp8, all_reduce_fp8 * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix typo * fix scaling algorithm in FP8 casting * support fp8 communication in pipeline parallelism * add fp8_communication flag in the script * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * shardformer fp8 * fix rebase * remove all to all * fix shardformer fp8 communication training degradation * [fp8] support all-gather flat tensor (#5932) * [fp8] add fp8 comm for low level zero * [test] add zero fp8 test case * [Feature] llama shardformer fp8 support (#5938) * add llama shardformer fp8 * Llama Shardformer Parity * fix typo * fix all reduce * fix pytest failure * fix reduce op and move function to fp8.py * fix typo * [FP8] rebase main (#5963) * add SimPO * fix dataloader * remove debug code * add orpo * fix style * fix colossalai, transformers version * fix colossalai, transformers version * fix colossalai, transformers version * fix torch colossalai version * update transformers version * [shardformer] DeepseekMoE support (#5871) * [Feature] deepseek moe expert parallel implement * [misc] fix typo, remove redundant file (#5867) * [misc] fix typo * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [Feature] deepseek support & unit test * [misc] remove debug code & useless print * [misc] fix typos (#5872) * [Feature] remove modeling file, use auto config. (#5884) * [misc] fix typos * [Feature] deepseek support via auto model, remove modeling file * [misc] delete useless file * [misc] fix typos * [Deepseek] remove redundant code (#5888) * [misc] fix typos * [Feature] deepseek support via auto model, remove modeling file * [misc] delete useless file * [misc] fix typos * [misc] remove redundant code * [Feature/deepseek] resolve comment. (#5889) * [misc] fix typos * [Feature] deepseek support via auto model, remove modeling file * [misc] delete useless file * [misc] fix typos * [misc] remove redundant code * [misc] mv module replacement into if branch * [misc] add some warning message and modify some code in unit test * [misc] fix typos --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [Hoxfix] Fix CUDA_DEVICE_MAX_CONNECTIONS for comm overlap Co-authored-by: Edenzzzz <wtan45@wisc.edu> * [Feat] Diffusion Model(PixArtAlpha/StableDiffusion3) Support (#5838) * Diffusion Model Inference support * Stable Diffusion 3 Support * pixartalpha support * [HotFix] CI,import,requirements-test for #5838 (#5892) * [Hot Fix] CI,import,requirements-test --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [Feature] Enable PP + SP for llama (#5868) * fix cross-PP-stage position id length diff bug * fix typo * fix typo * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * use a one cross entropy func for all shardformer models --------- Co-authored-by: Edenzzzz <wtan45@wisc.edu> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [ShardFormer] Add Ulysses Sequence Parallelism support for Command-R, Qwen2 and ChatGLM (#5897) * add benchmark for sft, dpo, simpo, orpo. Add benchmarking result. Support lora with gradient checkpoint * fix style * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix eval * hotfix citation * [zero] support all-gather overlap (#5898) * [zero] support all-gather overlap * [zero] add overlap all-gather flag * [misc] fix typo * [zero] update api * fix orpo cross entropy loss * [Auto Parallel]: Speed up intra-op plan generation by 44% (#5446) * Remove unnecessary calls to deepcopy * Build DimSpec's difference dict only once This change considerably speeds up construction speed of DimSpec objects. The difference_dict is the same for each DimSpec object, so a single copy of it is enough. * Fix documentation of DimSpec's difference method * [ShardFormer] fix qwen2 sp (#5903) * [compatibility] support torch 2.2 (#5875) * Support Pytorch 2.2.2 * keep build_on_pr file and update .compatibility * fix object_to_tensor usage when torch>=2.3.0 (#5820) * [misc] support torch2.3 (#5893) * [misc] support torch2.3 * [devops] update compatibility ci * [devops] update compatibility ci * [devops] add debug * [devops] add debug * [devops] add debug * [devops] add debug * [devops] remove debug * [devops] remove debug * [release] update version (#5912) * [plugin] support all-gather overlap for hybrid parallel (#5919) * [plugin] fixed all-gather overlap support for hybrid parallel * add kto * fix style, add kto data sample * [Examples] Add lazy init to OPT and GPT examples (#5924) Co-authored-by: Edenzzzz <wtan45@wisc.edu> * [ColossalChat] Hotfix for ColossalChat (#5910) * add ignore and tiny llama * fix path issue * run style * fix issue * update bash * add ignore and tiny llama * fix path issue * run style * fix issue * update bash * fix ddp issue * add Qwen 1.5 32B * refactor tokenization * [FIX BUG] UnboundLocalError: cannot access local variable 'default_conversation' where it is not associated with a value (#5931) * cannot access local variable 'default_conversation' where it is not associated with a value set default value for 'default_conversation' * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * fix test data * refactor evaluation * remove real data path * remove real data path * Add n_fused as an input from native_module (#5894) * [FIX BUG] convert env param to int in (#5934) * [Hotfix] Fix ZeRO typo #5936 Co-authored-by: Edenzzzz <wtan45@wisc.edu> * [Feature] Add a switch to control whether the model checkpoint needs to be saved after each epoch ends (#5941) * Add a switch to control whether the model checkpoint needs to be saved after each epoch ends * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * fix style * fix style * fix style * [shardformer] hotfix attn mask (#5945) * [shardformer] hotfix attn mask (#5947) * [Feat] Distrifusion Acceleration Support for Diffusion Inference (#5895) * Distrifusion Support source * comp comm overlap optimization * sd3 benchmark * pixart distrifusion bug fix * sd3 bug fix and benchmark * generation bug fix * naming fix * add docstring, fix counter and shape error * add reference * readme and requirement * [zero] hotfix update master params (#5951) * [release] update version (#5952) * [Chat] Fix lora (#5946) * fix merging * remove filepath * fix style * Update README.md (#5958) * [hotfix] Remove unused plan section (#5957) * remove readme * fix readme * update * [test] add mixtral for sequence classification * [test] add mixtral transformer test * [moe] fix plugin * [test] mixtra pp shard test * [chore] handle non member group * [zero] solve hang * [test] pass mixtral shardformer test * [moe] implement transit between non moe tp and ep * [zero] solve hang * [misc] solve booster hang by rename the variable * solve hang when parallel mode = pp + dp * [moe] implement submesh initialization * [moe] add mixtral dp grad scaling when not all experts are activated * [chore] manually revert unintended commit * [chore] trivial fix * [chore] arg pass & remove drop token * [test] add mixtral modelling test * [moe] implement tp * [moe] test deepseek * [moe] clean legacy code * [Feature] MoE Ulysses Support (#5918) * moe sp support * moe sp bug solve * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [chore] minor fix * [moe] init moe plugin comm setting with sp * moe sp + ep bug fix * [moe] finalize test (no pp) * [moe] full test for deepseek and mixtral (pp + sp to fix) * [chore] minor fix after rebase * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * [chore] solve moe ckpt test failure and some other arg pass failure * [moe] remove ops * [test] fix test: test_zero1_2 * [bug] fix: somehow logger hangs the program * [moe] deepseek moe sp support * [test] add check * [deepseek] replace attn (a workaround for bug in transformers) * [misc] skip redunant test * [misc] remove debug/print code * [moe] refactor mesh assignment * Revert "[moe] implement submesh initialization" This reverts commit2f9bce6686. * [chore] change moe_pg_mesh to private * [misc] remove incompatible test config * [misc] fix ci failure: change default value to false in moe plugin * [misc] remove useless condition * [chore] docstring * [moe] remove force_overlap_comm flag and add warning instead * [doc] add MoeHybridParallelPlugin docstring * [moe] solve dp axis issue * [chore] remove redundant test case, print string & reduce test tokens * [feat] Dist Loader for Eval (#5950) * support auto distributed data loader * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * support auto distributed data loader * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix tp error * remove unused parameters * remove unused * update inference * update docs * update inference --------- Co-authored-by: Michelle <qianranma8@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [lora] lora support hybrid parallel plugin (#5956) * lora support hybrid plugin * fix * fix * fix * fix * fp8 operators for compressed communication cast_to_fp8, cast_from_fp8, all_reduce_fp8 * fix scaling algorithm in FP8 casting * support fp8 communication in pipeline parallelism * add fp8_communication flag in the script * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix typo * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * shardformer fp8 * fix rebase * remove all to all * fix shardformer fp8 communication training degradation * [fp8] support all-gather flat tensor (#5932) * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * Update low_level_optim.py --------- Co-authored-by: YeAnbang <anbangy2@outlook.com> Co-authored-by: Haze188 <haze188@qq.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Edenzzzz <wenxuan.tan@wisc.edu> Co-authored-by: Edenzzzz <wtan45@wisc.edu> Co-authored-by: Runyu Lu <77330637+LRY89757@users.noreply.github.com> Co-authored-by: Guangyao Zhang <xjtu521@qq.com> Co-authored-by: YeAnbang <44796419+YeAnbang@users.noreply.github.com> Co-authored-by: Hongxin Liu <lhx0217@gmail.com> Co-authored-by: Stephan Kö <stephankoe@users.noreply.github.com> Co-authored-by: アマデウス <kurisusnowdeng@users.noreply.github.com> Co-authored-by: Tong Li <tong.li352711588@gmail.com> Co-authored-by: zhurunhua <1281592874@qq.com> Co-authored-by: Insu Jang <insujang@umich.edu> Co-authored-by: Gao, Ruiyuan <905370712@qq.com> Co-authored-by: hxwang <wang1570@e.ntu.edu.sg> Co-authored-by: Michelle <qianranma8@gmail.com> Co-authored-by: Wang Binluo <32676639+wangbluo@users.noreply.github.com> Co-authored-by: HangXu <hangxu0304@gmail.com> * [fp8]support all2all fp8 (#5953) * support all2all fp8 * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * fix * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [fp8] add fp8 linear (#5967) * [fp8] add fp8 linear * [test] fix fp8 linear test condition * [test] fix fp8 linear test condition * [test] fix fp8 linear test condition * [fp8] support fp8 amp for hybrid parallel plugin (#5975) * [fp8] support fp8 amp for hybrid parallel plugin * [test] add fp8 hook test * [fp8] fix fp8 linear compatibility * fix (#5976) * [Feature]: support FP8 communication in DDP, FSDP, Gemini (#5928) * support fp8_communication in the Torch DDP grad comm, FSDP grad comm, and FSDP params comm * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * implement communication hook for FSDP params all-gather * added unit test for fp8 operators * support fp8 communication in GeminiPlugin * update training scripts to support fsdp and fp8 communication * fixed some minor bugs observed in unit test * add all_gather_into_tensor_flat_fp8 * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * add skip the test if torch < 2.2.0 * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * add skip the test if torch < 2.2.0 * add skip the test if torch < 2.2.0 * add fp8_comm flag * rebase latest fp8 operators * rebase latest fp8 operators * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [test ci]Feature/fp8 comm (#5981) * fix * fix * fix * [fp8] support gemini plugin (#5978) * [fp8] refactor hook * [fp8] support gemini plugin * [example] add fp8 option for llama benchmark * [fp8] use torch compile (torch >= 2.3.0) (#5979) * [fp8] use torch compile (torch >= 2.4.0) * [fp8] set use_fast_accum in linear * [chore] formal version check * [chore] fix sig * [fp8]Moe support fp8 communication (#5977) * fix * support moe fp8 * fix * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * fix * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * fix * fix fix fi * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [fp8] support hybrid parallel plugin (#5982) * support fp8 comm for qwen2 model * support fp8 comm for qwen2 model * support fp8 comm for qwen2 model * fp8 * fix * bert and bloom * chatglm and command * gpt2,gptj,bert, falcon,blip2 * mistral,opy,sam,t5,vit,whisper * fix * fix * fix * [fp8] refactor fp8 linear with compile (#5993) * [fp8] refactor fp8 linear with compile * [fp8] fix linear test * [fp8] fix linear test * [fp8] support asynchronous FP8 communication (#5997) * fix * fix * fix * support async all2all * support async op for all gather * fix * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [fp8] update torch.compile for linear_fp8 to >= 2.4.0 (#6004) * [fp8] linear perf enhancement * [fp8]update reduce-scatter test (#6002) * fix * fix * fix * fix * [fp8] add use_fp8 option for MoeHybridParallelPlugin (#6009) * [fp8] zero support fp8 linear. (#6006) * fix * fix * fix * zero fp8 * zero fp8 * Update requirements.txt * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix the merge * fix the merge * fix the merge * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix the merge * fix * fix * fix the merge * fix * fix * fix * fix * fix * fix the merge * fix * fix * fix * fix * [fp8] Merge feature/fp8_comm to main branch of Colossalai (#6016) * add SimPO * fix dataloader * remove debug code * add orpo * fix style * fix colossalai, transformers version * fix colossalai, transformers version * fix colossalai, transformers version * fix torch colossalai version * update transformers version * [shardformer] DeepseekMoE support (#5871) * [Feature] deepseek moe expert parallel implement * [misc] fix typo, remove redundant file (#5867) * [misc] fix typo * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [Feature] deepseek support & unit test * [misc] remove debug code & useless print * [misc] fix typos (#5872) * [Feature] remove modeling file, use auto config. (#5884) * [misc] fix typos * [Feature] deepseek support via auto model, remove modeling file * [misc] delete useless file * [misc] fix typos * [Deepseek] remove redundant code (#5888) * [misc] fix typos * [Feature] deepseek support via auto model, remove modeling file * [misc] delete useless file * [misc] fix typos * [misc] remove redundant code * [Feature/deepseek] resolve comment. (#5889) * [misc] fix typos * [Feature] deepseek support via auto model, remove modeling file * [misc] delete useless file * [misc] fix typos * [misc] remove redundant code * [misc] mv module replacement into if branch * [misc] add some warning message and modify some code in unit test * [misc] fix typos --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [Hoxfix] Fix CUDA_DEVICE_MAX_CONNECTIONS for comm overlap Co-authored-by: Edenzzzz <wtan45@wisc.edu> * [Feat] Diffusion Model(PixArtAlpha/StableDiffusion3) Support (#5838) * Diffusion Model Inference support * Stable Diffusion 3 Support * pixartalpha support * [HotFix] CI,import,requirements-test for #5838 (#5892) * [Hot Fix] CI,import,requirements-test --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [Feature] Enable PP + SP for llama (#5868) * fix cross-PP-stage position id length diff bug * fix typo * fix typo * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * use a one cross entropy func for all shardformer models --------- Co-authored-by: Edenzzzz <wtan45@wisc.edu> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [ShardFormer] Add Ulysses Sequence Parallelism support for Command-R, Qwen2 and ChatGLM (#5897) * add benchmark for sft, dpo, simpo, orpo. Add benchmarking result. Support lora with gradient checkpoint * fix style * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix eval * hotfix citation * [zero] support all-gather overlap (#5898) * [zero] support all-gather overlap * [zero] add overlap all-gather flag * [misc] fix typo * [zero] update api * fix orpo cross entropy loss * [Auto Parallel]: Speed up intra-op plan generation by 44% (#5446) * Remove unnecessary calls to deepcopy * Build DimSpec's difference dict only once This change considerably speeds up construction speed of DimSpec objects. The difference_dict is the same for each DimSpec object, so a single copy of it is enough. * Fix documentation of DimSpec's difference method * [ShardFormer] fix qwen2 sp (#5903) * [compatibility] support torch 2.2 (#5875) * Support Pytorch 2.2.2 * keep build_on_pr file and update .compatibility * fix object_to_tensor usage when torch>=2.3.0 (#5820) * [misc] support torch2.3 (#5893) * [misc] support torch2.3 * [devops] update compatibility ci * [devops] update compatibility ci * [devops] add debug * [devops] add debug * [devops] add debug * [devops] add debug * [devops] remove debug * [devops] remove debug * [release] update version (#5912) * [plugin] support all-gather overlap for hybrid parallel (#5919) * [plugin] fixed all-gather overlap support for hybrid parallel * add kto * fix style, add kto data sample * [Examples] Add lazy init to OPT and GPT examples (#5924) Co-authored-by: Edenzzzz <wtan45@wisc.edu> * [ColossalChat] Hotfix for ColossalChat (#5910) * add ignore and tiny llama * fix path issue * run style * fix issue * update bash * add ignore and tiny llama * fix path issue * run style * fix issue * update bash * fix ddp issue * add Qwen 1.5 32B * refactor tokenization * [FIX BUG] UnboundLocalError: cannot access local variable 'default_conversation' where it is not associated with a value (#5931) * cannot access local variable 'default_conversation' where it is not associated with a value set default value for 'default_conversation' * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * fix test data * refactor evaluation * remove real data path * remove real data path * Add n_fused as an input from native_module (#5894) * [FIX BUG] convert env param to int in (#5934) * [Hotfix] Fix ZeRO typo #5936 Co-authored-by: Edenzzzz <wtan45@wisc.edu> * [Feature] Add a switch to control whether the model checkpoint needs to be saved after each epoch ends (#5941) * Add a switch to control whether the model checkpoint needs to be saved after each epoch ends * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * fix style * fix style * fix style * [shardformer] hotfix attn mask (#5945) * [shardformer] hotfix attn mask (#5947) * [Feat] Distrifusion Acceleration Support for Diffusion Inference (#5895) * Distrifusion Support source * comp comm overlap optimization * sd3 benchmark * pixart distrifusion bug fix * sd3 bug fix and benchmark * generation bug fix * naming fix * add docstring, fix counter and shape error * add reference * readme and requirement * [zero] hotfix update master params (#5951) * [release] update version (#5952) * [Chat] Fix lora (#5946) * fix merging * remove filepath * fix style * Update README.md (#5958) * [hotfix] Remove unused plan section (#5957) * remove readme * fix readme * update * [test] add mixtral for sequence classification * [test] add mixtral transformer test * [moe] fix plugin * [test] mixtra pp shard test * [chore] handle non member group * [zero] solve hang * [test] pass mixtral shardformer test * [moe] implement transit between non moe tp and ep * [zero] solve hang * [misc] solve booster hang by rename the variable * solve hang when parallel mode = pp + dp * [moe] implement submesh initialization * [moe] add mixtral dp grad scaling when not all experts are activated * [chore] manually revert unintended commit * [chore] trivial fix * [chore] arg pass & remove drop token * [test] add mixtral modelling test * [moe] implement tp * [moe] test deepseek * [moe] clean legacy code * [Feature] MoE Ulysses Support (#5918) * moe sp support * moe sp bug solve * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [chore] minor fix * [moe] init moe plugin comm setting with sp * moe sp + ep bug fix * [moe] finalize test (no pp) * [moe] full test for deepseek and mixtral (pp + sp to fix) * [chore] minor fix after rebase * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * [chore] solve moe ckpt test failure and some other arg pass failure * [moe] remove ops * [test] fix test: test_zero1_2 * [bug] fix: somehow logger hangs the program * [moe] deepseek moe sp support * [test] add check * [deepseek] replace attn (a workaround for bug in transformers) * [misc] skip redunant test * [misc] remove debug/print code * [moe] refactor mesh assignment * Revert "[moe] implement submesh initialization" This reverts commit2f9bce6686. * [chore] change moe_pg_mesh to private * [misc] remove incompatible test config * [misc] fix ci failure: change default value to false in moe plugin * [misc] remove useless condition * [chore] docstring * [moe] remove force_overlap_comm flag and add warning instead * [doc] add MoeHybridParallelPlugin docstring * [moe] solve dp axis issue * [chore] remove redundant test case, print string & reduce test tokens * [feat] Dist Loader for Eval (#5950) * support auto distributed data loader * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * support auto distributed data loader * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix tp error * remove unused parameters * remove unused * update inference * update docs * update inference --------- Co-authored-by: Michelle <qianranma8@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [lora] lora support hybrid parallel plugin (#5956) * lora support hybrid plugin * fix * fix * fix * fix * Support overall loss, update KTO logging * [Docs] clarify launch port Co-authored-by: Edenzzzz <wtan45@wisc.edu> * [Hotfix] README link (#5966) * update ignore * update readme * run style * update readme * [Hotfix] Avoid fused RMSnorm import error without apex (#5985) Co-authored-by: Edenzzzz <wtan45@wisc.edu> * [Chat] fix readme (#5989) * fix readme * fix readme, tokenization fully tested * fix readme, tokenization fully tested * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: root <root@notebook-8f919155-6035-47b4-9c6f-1be133b9e2c9-0.notebook-8f919155-6035-47b4-9c6f-1be133b9e2c9.colossal-ai.svc.cluster.local> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * fix sync condition (#6000) * [plugin] add cast inputs option for zero (#6003) * [pre-commit.ci] pre-commit autoupdate (#5995) updates: - [github.com/psf/black-pre-commit-mirror: 24.4.2 → 24.8.0](https://github.com/psf/black-pre-commit-mirror/compare/24.4.2...24.8.0) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [misc] Bypass the huggingface bug to solve the mask mismatch problem (#5991) * [Feature] Zigzag Ring attention (#5905) * halfway * fix cross-PP-stage position id length diff bug * fix typo * fix typo * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * unified cross entropy func for all shardformer models * remove redundant lines * add basic ring attn; debug cross entropy * fwd bwd logic complete * fwd bwd logic complete; add experimental triton rescale * precision tests passed * precision tests passed * fix typos and remove misc files * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * add sp_mode to benchmark; fix varlen interface * update softmax_lse shape by new interface * change tester name * remove buffer clone; support packed seq layout * add varlen tests * fix typo * all tests passed * add dkv_group; fix mask * remove debug statements --------- Co-authored-by: Edenzzzz <wtan45@wisc.edu> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [misc] update compatibility (#6008) * [misc] update compatibility * [misc] update requirements * [devops] disable requirements cache * [test] fix torch ddp test * [test] fix rerun on address in use * [test] fix lazy init * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix the merge * fix the merge * overlap kv comm with output rescale (#6017) Co-authored-by: Edenzzzz <wtan45@wisc.edu> * fix the merge * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix the merge * fix * fix * fix the merge * fix * [misc] Use dist logger in plugins (#6011) * use dist logger in plugins * remove trash * print on rank 0 --------- Co-authored-by: Edenzzzz <wtan45@wisc.edu> * fix * fix * fix * fix * fix the merge * fix * fix * fix * fix --------- Co-authored-by: YeAnbang <anbangy2@outlook.com> Co-authored-by: Haze188 <haze188@qq.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Edenzzzz <wenxuan.tan@wisc.edu> Co-authored-by: Edenzzzz <wtan45@wisc.edu> Co-authored-by: Runyu Lu <77330637+LRY89757@users.noreply.github.com> Co-authored-by: Guangyao Zhang <xjtu521@qq.com> Co-authored-by: YeAnbang <44796419+YeAnbang@users.noreply.github.com> Co-authored-by: Hongxin Liu <lhx0217@gmail.com> Co-authored-by: Stephan Kö <stephankoe@users.noreply.github.com> Co-authored-by: アマデウス <kurisusnowdeng@users.noreply.github.com> Co-authored-by: Tong Li <tong.li352711588@gmail.com> Co-authored-by: zhurunhua <1281592874@qq.com> Co-authored-by: Insu Jang <insujang@umich.edu> Co-authored-by: Gao, Ruiyuan <905370712@qq.com> Co-authored-by: hxwang <wang1570@e.ntu.edu.sg> Co-authored-by: Michelle <qianranma8@gmail.com> Co-authored-by: root <root@notebook-8f919155-6035-47b4-9c6f-1be133b9e2c9-0.notebook-8f919155-6035-47b4-9c6f-1be133b9e2c9.colossal-ai.svc.cluster.local> * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update train_dpo.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update low_level_zero_plugin.py * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * [CI] Remove triton version for compatibility bug; update req torch >=2.2 (#6018) * remove triton version * remove torch 2.2 * remove torch 2.1 * debug * remove 2.1 build tests * require torch >=2.2 --------- Co-authored-by: Edenzzzz <wtan45@wisc.edu> * [plugin] hotfix zero plugin (#6036) * [plugin] hotfix zero plugin * [plugin] hotfix zero plugin * [Colossal-LLaMA] Refactor latest APIs (#6030) * refactor latest code * update api * add dummy dataset * update Readme * add setup * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * update files * add PP support * update arguments * update argument * reorg folder * update version * remove IB infor * update utils * update readme * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * update save for zero * update save * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * add apex * update --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * add fused norm (#6038) * [FP8] unsqueeze scale to make it compatible with torch.compile (#6040) * [colossalai/checkpoint_io/...] fix bug in load_state_dict_into_model; format error msg (#6020) * fix bug in load_state_dict_into_model; format error msg * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update utils.py to support checking missing_keys * Update general_checkpoint_io.py fix bug in missing_keys error message * retrigger tests --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [Hotfix] Remove deprecated install (#6042) * remove deprecated install * remove unused folder * [fp8] optimize all-gather (#6043) * [fp8] optimize all-gather * [fp8] fix all gather fp8 ring * [fp8] enable compile * [fp8] fix all gather fp8 ring * [fp8] fix linear hook (#6046) * [fp8] disable all_to_all_fp8 in intranode (#6045) * enhance all_to_all_fp8 with internode comm control * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * disable some fp8 ops due to performance issue * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [release] update version (#6041) * [release] update version * [devops] update comp test * [devops] update comp test debug * [devops] debug comp test * [devops] debug comp test * [devops] debug comp test * [devops] debug comp test * [devops] debug comp test * [Feature] Split cross-entropy computation in SP (#5959) * halfway * fix cross-PP-stage position id length diff bug * fix typo * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * unified cross entropy func for all shardformer models * remove redundant lines * add basic ring attn; debug cross entropy * fwd bwd logic complete * fwd bwd logic complete; add experimental triton rescale * precision tests passed * precision tests passed * fix typos and remove misc files * update softmax_lse shape by new interface * change tester name * remove buffer clone; support packed seq layout * add varlen tests * fix typo * all tests passed * add dkv_group; fix mask * remove debug statements * adapt chatglm, command-R, qwen * debug * halfway * fix cross-PP-stage position id length diff bug * fix typo * fix typo * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * unified cross entropy func for all shardformer models * remove redundant lines * add basic ring attn; debug cross entropy * fwd bwd logic complete * fwd bwd logic complete; add experimental triton rescale * precision tests passed * precision tests passed * fix typos and remove misc files * add sp_mode to benchmark; fix varlen interface * update softmax_lse shape by new interface * add varlen tests * fix typo * all tests passed * add dkv_group; fix mask * remove debug statements * add comments * q1 index only once * remove events to simplify stream sync * simplify forward/backward logic * 2d ring forward passed * 2d ring backward passed * fixes * fix ring attn loss * 2D ring backward + llama passed * merge * update logger * fix typo * rebase * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix typo * remove typos * fixes * support GPT --------- Co-authored-by: Edenzzzz <wtan45@wisc.edu> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [hotfix] moe hybrid parallelism benchmark & follow-up fix (#6048) * [example] pass use_fp8_comm flag to all plugins * [example] add mixtral benchmark * [moe] refine assertion and check * [moe] fix mixtral & add more tests * [moe] consider checking dp * sp group and moe_dp_group * [mixtral] remove gate tp & add more tests * [deepseek] fix tp & sp for deepseek * [mixtral] minor fix * [deepseek] add deepseek benchmark * [fp8] hotfix backward hook (#6053) * [fp8] hotfix backward hook * [fp8] hotfix pipeline loss accumulation * [doc] update sp doc (#6055) * update sp doc * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * fix * fix --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * fix the sp * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix the attn * fix * fix * fix * fix * [zerobubble]Support ZeroBubble Pipeline (#6034) * [feat] add zerobubble pp (just a frame now); add POC test for dx_dw; add test for zerobubble; * [feat] add dw test; * [fix] fix weight not close; * [update] update text; * [feat] add test run_fwd_bwd automatic scheduling; * [feat] split communication and calculation; fix pop empty send_bwd_buffer error; * [feat] add test for p & p grad; * [feat] add comments for ZBV func; * [fix] rm useless assign and comments; * [fix] fix ci test; add pytest; * [feat] add run_fwd_bwd_with_microbatch (replace input) & test; add p&p.grad assert close test & all pass; * [feat] add apply v_schedule graph; p & p.grad assert err exist; * [fix] update * [feat] fix ci; add assert; * [feat] fix poc format * [feat] fix func name & ci; add comments; * [fix] fix poc test; add comments in poc; * [feat] add optim backward_b_by_grad * [feat] fix optimizer bwd b & w; support return accum loss & output * [feat] add fwd_bwd_step, run_fwd_only; * [fix] fix optim bwd; add license for v_schedule; remove redundant attributes; fix schedule loop "while"--> "for"; add communication dict; * [fix] fix communication_map; * [feat] update test; rm comments; * [fix] rm zbv in hybridplugin * [fix] fix optim bwd; * [fix] fix optim bwd; * [fix] rm output.data after send fwd; * [fix] fix bwd step if condition; remove useless comments and format info; * [fix] fix detach output & release output; * [fix] rm requir_grad for output; * [fix] fix requir grad position and detach position and input&output local buffer append position; * [feat] add memory assertation; * [fix] fix mem check; * [fix] mem assertation' * [fix] fix mem assertation * [fix] fix mem; use a new model shape; only assert mem less and equal than theo; * [fix] fix model zoo import; * [fix] fix redundant detach & clone; add buffer assertation in the end; * [fix] add output_obj_grad assert None at bwd b step; replace input_obj.require_grad_ with treemap; * [fix] update optim state dict assert (include param group & state); fix mem assert after add optim; * [fix] add testcase with microbatch 4; * [fp8] fix missing fp8_comm flag in mixtral (#6057) * fix * fix * fix * [fp8] Disable all_gather intranode. Disable Redundant all_gather fp8 (#6059) * all_gather only internode, fix pytest * fix cuda arch <89 compile pytest error * fix pytest failure * disable all_gather_into_tensor_flat_fp8 * fix fp8 format * fix pytest * fix conversations * fix chunk tuple to list * [doc] FP8 training and communication document (#6050) * Add FP8 training and communication document * add fp8 docstring for plugins * fix typo * fix typo * fix * fix * [moe] add parallel strategy for shared_expert && fix test for deepseek (#6063) * [ColossalEval] support for vllm (#6056) * support vllm * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * modify vllm and update readme * run pre-commit * remove dupilicated lines and refine code * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * update param name * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * refine code * update readme * refine code * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * [release] update version (#6062) * [feat] add zerobubble pp (just a frame now); add POC test for dx_dw; add test for zerobubble; * [update] update text; * [feat] add test run_fwd_bwd automatic scheduling; * [feat] fix poc format * [fix] fix poc test; add comments in poc; * [feat] add optim backward_b_by_grad * [feat] fix optimizer bwd b & w; support return accum loss & output * [fix] fix optim bwd; add license for v_schedule; remove redundant attributes; fix schedule loop "while"--> "for"; add communication dict; * [feat] update test; rm comments; * [fix] rm zbv in hybridplugin * [fix] fix optim bwd; * [fix] fix optim bwd; * [fix] rm output.data after send fwd; * [fix] fix bwd step if condition; remove useless comments and format info; * [fix] fix mem check; * [fix] fix mem assertation * [fix] fix mem; use a new model shape; only assert mem less and equal than theo; * [fix] fix model zoo import; * [feat] moehybrid support zerobubble; * [fix] fix zerobubble pp for shardformer type input; * [fix] fix require_grad & deallocate call; * [fix] fix mem assert; * [fix] fix fwd branch, fwd pass both micro_batch & internal_inputs' * [fix] fix pipeline util func deallocate --> release_tensor_data; fix bwd_b loss bwd branch; * [fix] fix zerobubble; support shardformer model type; * [fix] fix test_pipeline_utils ci; * [plugin] hybrid support zero bubble pipeline (#6060) * hybrid support zbv * fix fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * Update zero_bubble_pp.py * fix * fix-ci * fix [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * fix * fix * fix * [zerobubble]Support ZeroBubble Pipeline (#6034) * [feat] add zerobubble pp (just a frame now); add POC test for dx_dw; add test for zerobubble; * [feat] add dw test; * [fix] fix weight not close; * [update] update text; * [feat] add test run_fwd_bwd automatic scheduling; * [feat] split communication and calculation; fix pop empty send_bwd_buffer error; * [feat] add test for p & p grad; * [feat] add comments for ZBV func; * [fix] rm useless assign and comments; * [fix] fix ci test; add pytest; * [feat] add run_fwd_bwd_with_microbatch (replace input) & test; add p&p.grad assert close test & all pass; * [feat] add apply v_schedule graph; p & p.grad assert err exist; * [fix] update * [feat] fix ci; add assert; * [feat] fix poc format * [feat] fix func name & ci; add comments; * [fix] fix poc test; add comments in poc; * [feat] add optim backward_b_by_grad * [feat] fix optimizer bwd b & w; support return accum loss & output * [feat] add fwd_bwd_step, run_fwd_only; * [fix] fix optim bwd; add license for v_schedule; remove redundant attributes; fix schedule loop "while"--> "for"; add communication dict; * [fix] fix communication_map; * [feat] update test; rm comments; * [fix] rm zbv in hybridplugin * [fix] fix optim bwd; * [fix] fix optim bwd; * [fix] rm output.data after send fwd; * [fix] fix bwd step if condition; remove useless comments and format info; * [fix] fix detach output & release output; * [fix] rm requir_grad for output; * [fix] fix requir grad position and detach position and input&output local buffer append position; * [feat] add memory assertation; * [fix] fix mem check; * [fix] mem assertation' * [fix] fix mem assertation * [fix] fix mem; use a new model shape; only assert mem less and equal than theo; * [fix] fix model zoo import; * [fix] fix redundant detach & clone; add buffer assertation in the end; * [fix] add output_obj_grad assert None at bwd b step; replace input_obj.require_grad_ with treemap; * [fix] update optim state dict assert (include param group & state); fix mem assert after add optim; * [fix] add testcase with microbatch 4; * hybrid support zbv * fix fix * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update zero_bubble_pp.py * fix * fix-ci * fix [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci fix * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * fix * fix * fix * fix * fix * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * fix * fix * fix --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: duanjunwen <935724073@qq.com> * [feat] add zerobubble pp (just a frame now); add POC test for dx_dw; add test for zerobubble; * [update] update text; * [feat] add test run_fwd_bwd automatic scheduling; * [feat] fix poc format * [fix] fix poc test; add comments in poc; * [feat] add optim backward_b_by_grad * [feat] fix optimizer bwd b & w; support return accum loss & output * [fix] fix optim bwd; add license for v_schedule; remove redundant attributes; fix schedule loop "while"--> "for"; add communication dict; * [feat] update test; rm comments; * [fix] fix optim bwd; * [fix] fix optim bwd; * [fix] rm output.data after send fwd; * [fix] fix bwd step if condition; remove useless comments and format info; * [fix] fix mem check; * [fix] fix mem assertation * [fix] fix mem; use a new model shape; only assert mem less and equal than theo; * [fix] fix model zoo import; * [fix] fix mem assert; * [fix] fix fwd branch, fwd pass both micro_batch & internal_inputs' * [plugin] hybrid support zero bubble pipeline (#6060) * hybrid support zbv * fix fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * Update zero_bubble_pp.py * fix * fix-ci * fix [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * fix * fix * fix * [zerobubble]Support ZeroBubble Pipeline (#6034) * [feat] add zerobubble pp (just a frame now); add POC test for dx_dw; add test for zerobubble; * [feat] add dw test; * [fix] fix weight not close; * [update] update text; * [feat] add test run_fwd_bwd automatic scheduling; * [feat] split communication and calculation; fix pop empty send_bwd_buffer error; * [feat] add test for p & p grad; * [feat] add comments for ZBV func; * [fix] rm useless assign and comments; * [fix] fix ci test; add pytest; * [feat] add run_fwd_bwd_with_microbatch (replace input) & test; add p&p.grad assert close test & all pass; * [feat] add apply v_schedule graph; p & p.grad assert err exist; * [fix] update * [feat] fix ci; add assert; * [feat] fix poc format * [feat] fix func name & ci; add comments; * [fix] fix poc test; add comments in poc; * [feat] add optim backward_b_by_grad * [feat] fix optimizer bwd b & w; support return accum loss & output * [feat] add fwd_bwd_step, run_fwd_only; * [fix] fix optim bwd; add license for v_schedule; remove redundant attributes; fix schedule loop "while"--> "for"; add communication dict; * [fix] fix communication_map; * [feat] update test; rm comments; * [fix] rm zbv in hybridplugin * [fix] fix optim bwd; * [fix] fix optim bwd; * [fix] rm output.data after send fwd; * [fix] fix bwd step if condition; remove useless comments and format info; * [fix] fix detach output & release output; * [fix] rm requir_grad for output; * [fix] fix requir grad position and detach position and input&output local buffer append position; * [feat] add memory assertation; * [fix] fix mem check; * [fix] mem assertation' * [fix] fix mem assertation * [fix] fix mem; use a new model shape; only assert mem less and equal than theo; * [fix] fix model zoo import; * [fix] fix redundant detach & clone; add buffer assertation in the end; * [fix] add output_obj_grad assert None at bwd b step; replace input_obj.require_grad_ with treemap; * [fix] update optim state dict assert (include param group & state); fix mem assert after add optim; * [fix] add testcase with microbatch 4; * hybrid support zbv * fix fix * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update zero_bubble_pp.py * fix * fix-ci * fix [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci fix * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * fix * fix * fix * fix * fix * fix * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * fix * fix * fix --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: duanjunwen <935724073@qq.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: HangXu <hangxu0304@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: GuangyaoZhang <xjtu521@qq.com> Co-authored-by: Hongxin Liu <lhx0217@gmail.com> Co-authored-by: YeAnbang <anbangy2@outlook.com> Co-authored-by: Haze188 <haze188@qq.com> Co-authored-by: Edenzzzz <wenxuan.tan@wisc.edu> Co-authored-by: Edenzzzz <wtan45@wisc.edu> Co-authored-by: Runyu Lu <77330637+LRY89757@users.noreply.github.com> Co-authored-by: YeAnbang <44796419+YeAnbang@users.noreply.github.com> Co-authored-by: Stephan Kö <stephankoe@users.noreply.github.com> Co-authored-by: アマデウス <kurisusnowdeng@users.noreply.github.com> Co-authored-by: Tong Li <tong.li352711588@gmail.com> Co-authored-by: zhurunhua <1281592874@qq.com> Co-authored-by: Insu Jang <insujang@umich.edu> Co-authored-by: Gao, Ruiyuan <905370712@qq.com> Co-authored-by: hxwang <wang1570@e.ntu.edu.sg> Co-authored-by: Michelle <qianranma8@gmail.com> Co-authored-by: Wang Binluo <32676639+wangbluo@users.noreply.github.com> Co-authored-by: wangbluo <2538539015@qq.com> Co-authored-by: root <root@notebook-8f919155-6035-47b4-9c6f-1be133b9e2c9-0.notebook-8f919155-6035-47b4-9c6f-1be133b9e2c9.colossal-ai.svc.cluster.local> Co-authored-by: duanjunwen <935724073@qq.com> Co-authored-by: Camille Zhong <44392324+Camille7777@users.noreply.github.com>
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@@ -7,6 +7,7 @@ import torch.distributed as dist
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from colossalai.accelerator import get_accelerator
|
||||
from colossalai.quantization.fp8 import all_gather_fp8
|
||||
|
||||
|
||||
class TensorState(Enum):
|
||||
@@ -166,6 +167,7 @@ class Chunk:
|
||||
self.grad_chunk = None
|
||||
# the async all-reduce/reduce-scatter work of this grad chunk (None means sync)
|
||||
self.grad_reduce_work = None
|
||||
self.fp8_communication = False
|
||||
|
||||
@property
|
||||
def memory_usage(self) -> Dict[str, int]:
|
||||
@@ -521,9 +523,18 @@ class Chunk:
|
||||
|
||||
alloc_storage(self.cuda_global_chunk)
|
||||
assert self.cuda_global_chunk.is_contiguous()
|
||||
work = dist.all_gather_into_tensor(
|
||||
self.cuda_global_chunk, self.cuda_shard, self.torch_pg, async_op=async_op
|
||||
)
|
||||
if self.fp8_communication:
|
||||
work = all_gather_fp8(
|
||||
list(self.cuda_global_chunk.chunk(self.pg_size)),
|
||||
self.cuda_shard,
|
||||
self.torch_pg,
|
||||
fp8_format="e4m3",
|
||||
async_op=async_op,
|
||||
)
|
||||
else:
|
||||
work = dist.all_gather_into_tensor(
|
||||
self.cuda_global_chunk, self.cuda_shard, self.torch_pg, async_op=async_op
|
||||
)
|
||||
|
||||
self.cuda_shard = None
|
||||
self.is_gathered = True
|
||||
|
||||
@@ -26,6 +26,7 @@ class ChunkManager:
|
||||
init_device: Optional[torch.device] = None,
|
||||
reuse_fp16_chunk: bool = True,
|
||||
max_prefetch: int = 0,
|
||||
fp8_communication: bool = False,
|
||||
) -> None:
|
||||
self.device = init_device or get_accelerator().get_current_device()
|
||||
self.dp_degree_chunk_size_dict: Dict[int, int] = dict()
|
||||
@@ -44,6 +45,7 @@ class ChunkManager:
|
||||
self.accumulating_grads = False
|
||||
self.overflow_counter = torch.tensor([0], dtype=torch.int, device=get_accelerator().get_current_device())
|
||||
self._prefetch_stream = get_accelerator().Stream() if max_prefetch else None
|
||||
self.fp8_communication = fp8_communication
|
||||
|
||||
def register_tensor(
|
||||
self,
|
||||
@@ -101,6 +103,8 @@ class ChunkManager:
|
||||
extra_dp_group=extra_dp_group,
|
||||
**chunk_kwargs,
|
||||
)
|
||||
if self.fp8_communication:
|
||||
chunk.fp8_communication = True
|
||||
|
||||
chunk_group.append(chunk)
|
||||
chunk.append_tensor(tensor)
|
||||
|
||||
@@ -15,6 +15,7 @@ from colossalai.checkpoint_io.utils import StateDictSharder, gather_distributed_
|
||||
from colossalai.interface import ModelWrapper
|
||||
from colossalai.lazy import LazyTensor
|
||||
from colossalai.logging import get_dist_logger
|
||||
from colossalai.quantization.fp8_hook import FP8Hook
|
||||
from colossalai.tensor.colo_parameter import ColoParameter
|
||||
from colossalai.tensor.d_tensor import (
|
||||
distribute_tensor,
|
||||
@@ -98,6 +99,8 @@ class GeminiDDP(ModelWrapper):
|
||||
extra_dp_group: Optional[ProcessGroup] = None,
|
||||
verbose: bool = False,
|
||||
enable_async_reduce: bool = True,
|
||||
fp8_communication: bool = False,
|
||||
use_fp8: bool = False,
|
||||
) -> None:
|
||||
assert mixed_precision in (torch.float16, torch.bfloat16)
|
||||
reuse_fp16_chunk = master_weights if not enable_gradient_accumulation else False
|
||||
@@ -122,6 +125,8 @@ class GeminiDDP(ModelWrapper):
|
||||
verbose=verbose,
|
||||
max_prefetch=max_prefetch,
|
||||
)
|
||||
if fp8_communication:
|
||||
self.chunk_manager.fp8_communication = True
|
||||
self.gemini_manager = GeminiManager(
|
||||
placement_policy,
|
||||
self.chunk_manager,
|
||||
@@ -135,6 +140,9 @@ class GeminiDDP(ModelWrapper):
|
||||
)
|
||||
self.force_outputs_fp32 = force_outputs_fp32
|
||||
self.param_op_hook = GeminiZeROHook(self.gemini_manager)
|
||||
self.hooks = [self.param_op_hook]
|
||||
if use_fp8:
|
||||
self.hooks.append(FP8Hook())
|
||||
self.fp32_params: List[torch.Tensor] = list()
|
||||
self.fp16_params: List[ColoParameter] = list()
|
||||
self.grads_device: Dict[torch.Tensor, torch.device] = dict()
|
||||
@@ -307,7 +315,7 @@ class GeminiDDP(ModelWrapper):
|
||||
outputs = self._inference_forward(*args, **kwargs)
|
||||
else:
|
||||
self.gemini_manager.pre_iter(*args)
|
||||
with ColoParamOpHookManager.use_hooks(self.param_op_hook):
|
||||
with ColoParamOpHookManager.use_hooks(*self.hooks):
|
||||
outputs = self.module(*args, **kwargs)
|
||||
|
||||
if self.force_outputs_fp32:
|
||||
@@ -316,7 +324,7 @@ class GeminiDDP(ModelWrapper):
|
||||
|
||||
def _inference_forward(self, *args, **kwargs):
|
||||
"""This function is only triggered for inference."""
|
||||
fwd_ctx = ColoParamOpHookManager.use_hooks(self.param_op_hook)
|
||||
fwd_ctx = ColoParamOpHookManager.use_hooks(*self.hooks)
|
||||
if not self.scatter_after_inference:
|
||||
# gather all chunks
|
||||
for chunk in self.chunk_manager.get_chunks(self.fp16_params):
|
||||
@@ -369,7 +377,7 @@ class GeminiDDP(ModelWrapper):
|
||||
|
||||
def backward(self, loss: torch.Tensor):
|
||||
self._pre_backward()
|
||||
with self.param_op_hook.switch_to_backward(), ColoParamOpHookManager.use_hooks(self.param_op_hook):
|
||||
with self.param_op_hook.switch_to_backward(), ColoParamOpHookManager.use_hooks(*self.hooks):
|
||||
loss.backward()
|
||||
self._post_backward()
|
||||
|
||||
|
||||
@@ -4,6 +4,8 @@ import torch
|
||||
import torch.distributed as dist
|
||||
from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
|
||||
|
||||
from colossalai.quantization.fp8 import all_gather_fp8
|
||||
|
||||
|
||||
class TensorBucket:
|
||||
def __init__(self, size):
|
||||
@@ -61,11 +63,14 @@ class TensorBucket:
|
||||
for old, new in zip(self._bucket, unflattened_tensor_list):
|
||||
old.copy_(new)
|
||||
|
||||
def all_gather(self, group=None):
|
||||
def all_gather(self, group=None, fp8_communication: bool = False):
|
||||
flat = self.flatten()
|
||||
buffers = [torch.empty_like(flat) for _ in range(dist.get_world_size(group))]
|
||||
dist.all_gather(buffers, flat, group=group)
|
||||
unflat_buffers = [self.unflatten(buffer) for buffer in buffers]
|
||||
buffer = torch.empty(flat.numel() * dist.get_world_size(group), device=flat.device, dtype=flat.dtype)
|
||||
if fp8_communication:
|
||||
all_gather_fp8(list(buffer.chunk(dist.get_world_size(group))), flat, group=group, fp8_format="e4m3")
|
||||
else:
|
||||
dist.all_gather_into_tensor(buffer, flat, group=group)
|
||||
unflat_buffers = [self.unflatten(buffer) for buffer in buffer.chunk(dist.get_world_size(group))]
|
||||
# transpose the list of list
|
||||
unflat_buffers = list(map(list, zip(*unflat_buffers)))
|
||||
for unflat_shards, tensor in zip(unflat_buffers, self._bucket):
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# this code is inspired by the DeepSpeed library and implemented with our own design from scratch
|
||||
import copy
|
||||
from contextlib import contextmanager
|
||||
from contextlib import contextmanager, nullcontext
|
||||
from functools import partial
|
||||
from typing import Dict, Iterator, List, Optional, Tuple
|
||||
from weakref import proxy
|
||||
@@ -20,6 +20,7 @@ from colossalai.amp.naive_amp.mixed_precision_mixin import (
|
||||
)
|
||||
from colossalai.interface import OptimizerWrapper
|
||||
from colossalai.logging import get_dist_logger
|
||||
from colossalai.quantization.fp8 import all_gather_fp8, all_reduce_fp8, reduce_scatter_fp8
|
||||
from colossalai.tensor.moe_tensor.api import is_moe_tensor
|
||||
|
||||
from ._utils import calculate_global_norm_from_list, has_inf_or_nan, release_param_grad, sync_tensor
|
||||
@@ -86,6 +87,8 @@ class LowLevelZeroOptimizer(OptimizerWrapper):
|
||||
forced_dtype: Optional[torch.dtype] = None,
|
||||
master_weights: bool = True, # master weights
|
||||
overlap_allgather: bool = False,
|
||||
fp8_communication: bool = False,
|
||||
backward_context=None,
|
||||
):
|
||||
super(LowLevelZeroOptimizer, self).__init__(optim=optimizer)
|
||||
|
||||
@@ -127,6 +130,8 @@ class LowLevelZeroOptimizer(OptimizerWrapper):
|
||||
self._overlap_allgather = overlap_allgather
|
||||
self._reduce_bucket_size = reduce_bucket_size
|
||||
self._communication_dtype = communication_dtype
|
||||
self._fp8_communication = fp8_communication
|
||||
self._backward_context = backward_context
|
||||
|
||||
# gradient clipping
|
||||
self._clip_grad_norm = clip_grad_norm
|
||||
@@ -330,7 +335,10 @@ class LowLevelZeroOptimizer(OptimizerWrapper):
|
||||
flat_grads = flat_grads.to(self._communication_dtype)
|
||||
|
||||
if not self._partition_grads:
|
||||
dist.all_reduce(flat_grads, group=bucket_store.torch_pg)
|
||||
if self._fp8_communication:
|
||||
all_reduce_fp8(flat_grads, group=bucket_store.torch_pg)
|
||||
else:
|
||||
dist.all_reduce(flat_grads, group=bucket_store.torch_pg)
|
||||
if flat_grads.dtype != grad_dtype:
|
||||
flat_grads = flat_grads.to(grad_dtype)
|
||||
|
||||
@@ -340,7 +348,14 @@ class LowLevelZeroOptimizer(OptimizerWrapper):
|
||||
else:
|
||||
flat_grads_list = list(flat_grads.split(len(flat_grads) // bucket_store.world_size))
|
||||
received_grad = torch.zeros_like(flat_grads_list[0])
|
||||
dist.reduce_scatter(received_grad, flat_grads_list, group=bucket_store.torch_pg)
|
||||
if self._fp8_communication:
|
||||
reduce_scatter_fp8(
|
||||
received_grad,
|
||||
flat_grads_list,
|
||||
group=bucket_store.torch_pg,
|
||||
)
|
||||
else:
|
||||
dist.reduce_scatter(received_grad, flat_grads_list, group=bucket_store.torch_pg)
|
||||
|
||||
if received_grad.dtype != grad_dtype:
|
||||
received_grad = received_grad.to(grad_dtype)
|
||||
@@ -416,7 +431,9 @@ class LowLevelZeroOptimizer(OptimizerWrapper):
|
||||
if self.mixed_precision_mixin is not None:
|
||||
loss = self.mixed_precision_mixin.pre_backward(loss)
|
||||
|
||||
loss.backward(inputs=inputs, retain_graph=retain_graph)
|
||||
ctx = nullcontext() if self._backward_context is None else self._backward_context()
|
||||
with ctx:
|
||||
loss.backward(inputs=inputs, retain_graph=retain_graph)
|
||||
|
||||
if not self.require_grad_sync:
|
||||
return
|
||||
@@ -567,18 +584,26 @@ class LowLevelZeroOptimizer(OptimizerWrapper):
|
||||
set_all_gather_handle(working_param, handle)
|
||||
else:
|
||||
if param_to_gather.numel() > self.pg_to_tensor_bucket[pg].max_size:
|
||||
dist.all_gather_into_tensor(padded_working_param, param_to_gather, pg)
|
||||
if self._fp8_communication:
|
||||
all_gather_fp8(
|
||||
list(padded_working_param.chunk(dist.get_world_size(pg))),
|
||||
param_to_gather,
|
||||
pg,
|
||||
fp8_format="e4m3",
|
||||
)
|
||||
else:
|
||||
dist.all_gather_into_tensor(padded_working_param, param_to_gather, pg)
|
||||
continue
|
||||
try:
|
||||
self.pg_to_tensor_bucket[pg].add_to_bucket(param_to_gather, write_back_tensor=working_param)
|
||||
except RuntimeError:
|
||||
self.pg_to_tensor_bucket[pg].all_gather(pg)
|
||||
self.pg_to_tensor_bucket[pg].all_gather(pg, fp8_communication=self._fp8_communication)
|
||||
self.pg_to_tensor_bucket[pg].add_to_bucket(param_to_gather, write_back_tensor=working_param)
|
||||
self.optim.param_groups[group_id]["params"] = self._master_param_groups_of_current_rank[group_id]
|
||||
if not self._overlap_allgather:
|
||||
for pg, tensor_bucket in self.pg_to_tensor_bucket.items():
|
||||
if not tensor_bucket.is_empty():
|
||||
tensor_bucket.all_gather(pg)
|
||||
tensor_bucket.all_gather(pg, fp8_communication=self._fp8_communication)
|
||||
|
||||
def _compute_grad_norm(self, dp_pg: ProcessGroup, gradients: List[Tensor], norm_type: int = 2) -> float:
|
||||
r"""
|
||||
|
||||
Reference in New Issue
Block a user