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* fp8 operators for compressed communication

cast_to_fp8, cast_from_fp8, all_reduce_fp8

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* 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

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* 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

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* [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

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* [Hoxfix] Fix CUDA_DEVICE_MAX_CONNECTIONS for comm overlap

Co-authored-by: Edenzzzz <[email protected]>

* [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

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* [Feature] Enable PP + SP for llama (#5868)

* fix cross-PP-stage position id length diff bug

* fix typo

* fix typo

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* use a one cross entropy func for all shardformer models

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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

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for more information, see https://pre-commit.ci

* fix eval

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* [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 <[email protected]>

* [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'

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* 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 <[email protected]>

* [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

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* 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

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* [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

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* [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

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* [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 commit 2f9bce6686d1415a83d5726dc5ff02222c742582.

* [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

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* support auto distributed data loader

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* fix tp error

* remove unused parameters

* remove unused

* update inference

* update docs

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Co-authored-by: Michelle <[email protected]>
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

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Co-authored-by: YeAnbang <[email protected]>
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* [fp8]support all2all fp8 (#5953)

* support all2all fp8

* fix

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* [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

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* implement communication hook for FSDP params all-gather

* added unit test for fp8 operators

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* fixed some minor bugs observed in unit test

* add all_gather_into_tensor_flat_fp8

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* add skip the test if torch < 2.2.0

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* add skip the test if torch < 2.2.0

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* [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

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* [fp8]Moe support fp8 communication (#5977)

* fix

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* [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

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* support async all2all

* support async op for all gather

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* [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

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* fix

* zero fp8

* zero fp8

* Update requirements.txt

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* [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

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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

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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 <[email protected]>

* [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

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Co-authored-by: Edenzzzz <[email protected]>
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

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* [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 <[email protected]>

* [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 <[email protected]>

* [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

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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

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* [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

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* [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

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---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: duanjunwen <[email protected]>

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* zbv support zero

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---------

Co-authored-by: HangXu <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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16 changes: 0 additions & 16 deletions colossalai/booster/plugin/hybrid_parallel_plugin.py
Original file line number Diff line number Diff line change
Expand Up @@ -1166,22 +1166,6 @@ def __init__(
num_microbatch=num_microbatches,
microbatch_size=microbatch_size,
)
elif pp_style == "zbv":
self.scheduler = ZeroBubbleVPipeScheduler(
stage_manager=self.stage_manager,
schedule=scheduler_nodes,
num_model_chunks=num_model_chunks,
num_microbatch=num_microbatches,
microbatch_size=microbatch_size,
)
elif pp_style == "zbv":
self.scheduler = ZeroBubbleVPipeScheduler(
stage_manager=self.stage_manager,
schedule=scheduler_nodes,
num_model_chunks=num_model_chunks,
num_microbatch=num_microbatches,
microbatch_size=microbatch_size,
)
else:
raise NotImplementedError()
if sequence_parallelism_mode == "ring_attn":
Expand Down
18 changes: 12 additions & 6 deletions colossalai/pipeline/schedule/zero_bubble_pp.py
Original file line number Diff line number Diff line change
Expand Up @@ -500,12 +500,18 @@ def backward_b_step(
output_obj_ = [v for v in output_obj_ if isinstance(v, torch.Tensor) or v is None]
output_obj_grad_ = [v for v in output_obj_grad_ if isinstance(v, torch.Tensor) or v is None]

optimizer.backward_by_grad(
tensor=output_obj_,
grad=output_obj_grad_,
inputs=input_obj_,
retain_graph=True,
)
try:
ctx = optimizer.no_sync()
except AttributeError:
ctx = model_chunk.no_sync()

with ctx:
optimizer.backward_by_grad(
tensor=output_obj_,
grad=output_obj_grad_,
inputs=input_obj_,
retain_graph=True,
)

# Format output_obj_grad
input_obj_grad = {}
Expand Down
20 changes: 11 additions & 9 deletions colossalai/shardformer/policies/llama.py
Original file line number Diff line number Diff line change
Expand Up @@ -261,9 +261,9 @@ def get_held_layers(self) -> List[Module]:
held_layers.append(module.embed_tokens)
for start_idx, end_idx in stage_indices:
held_layers.extend(module.layers[start_idx:end_idx])
if stage_manager.use_zbv and stage_manager.is_first_stage(ignore_chunk=True):
held_layers.append(module.norm)
elif stage_manager.is_last_stage(ignore_chunk=True):
if (stage_manager.use_zbv and stage_manager.is_first_stage(ignore_chunk=True)) or (
not stage_manager.use_zbv and stage_manager.is_last_stage(ignore_chunk=True)
):
held_layers.append(module.norm)

else:
Expand Down Expand Up @@ -355,13 +355,15 @@ def get_held_layers(self) -> List[Module]:
"""Get pipeline layers for current stage."""
stage_manager = self.pipeline_stage_manager
held_layers = super().get_held_layers()
if stage_manager.use_zbv and stage_manager.is_first_stage(ignore_chunk=True):
held_layers.append(self.model.lm_head)
elif stage_manager.is_last_stage(ignore_chunk=True):
if (stage_manager.use_zbv and stage_manager.is_first_stage(ignore_chunk=True)) or (
not stage_manager.use_zbv and stage_manager.is_last_stage(ignore_chunk=True)
):
held_layers.append(self.model.lm_head)
return held_layers

def get_shared_params(self) -> List[Dict[int, Tensor]]:
if self.pipeline_stage_manager is not None and self.pipeline_stage_manager.use_zbv:
return []
llama_model = self.model.model
if self.pipeline_stage_manager and self.pipeline_stage_manager.num_stages > 1:
if (
Expand Down Expand Up @@ -415,9 +417,9 @@ def get_held_layers(self) -> List[Module]:
"""Get pipeline layers for current stage."""
stage_manager = self.pipeline_stage_manager
held_layers = super().get_held_layers()
if stage_manager.use_zbv and stage_manager.is_first_stage(ignore_chunk=True):
held_layers.append(self.model.score)
elif stage_manager.is_last_stage(ignore_chunk=True):
if (stage_manager.use_zbv and stage_manager.is_first_stage(ignore_chunk=True)) or (
not stage_manager.use_zbv and stage_manager.is_last_stage(ignore_chunk=True)
):
held_layers.append(self.model.score)
return held_layers

Expand Down
4 changes: 4 additions & 0 deletions tests/test_pipeline/test_schedule/test_zerobubble_pp.py
Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
from contextlib import nullcontext
from copy import deepcopy
from functools import partial
from typing import Tuple
Expand Down Expand Up @@ -72,6 +73,9 @@ def forward(
else:
return {"hidden_states": held_layers(hidden_states)}

def no_sync(self):
return nullcontext()


def assert_optim_param_groups(optim_base_param_groups, optim_pp_param_groups):
for (key_base, val_base), (key_pp, val_pp) in zip(optim_base_param_groups.items(), optim_pp_param_groups.items()):
Expand Down
25 changes: 18 additions & 7 deletions tests/test_shardformer/test_model/test_shard_llama.py
Original file line number Diff line number Diff line change
Expand Up @@ -114,14 +114,12 @@ def check_forward_backward(model_fn, data_gen_fn, output_transform_fn, loss_fn,

# check last hidden state & loss
check_flag = False
if stage_manager is None:
if (
(stage_manager is None)
or (stage_manager.use_zbv and stage_manager.is_first_stage(ignore_chunk=True))
or (not stage_manager.use_zbv and stage_manager.is_last_stage(ignore_chunk=True))
):
check_flag = True
else:
if stage_manager.use_zbv:
if stage_manager.is_first_stage(ignore_chunk=True):
check_flag = True
elif stage_manager.is_last_stage(ignore_chunk=True):
check_flag = True
if check_flag:
if test_config["precision"] == "fp32":
atol, rtol = 1e-5, 1e-3
Expand Down Expand Up @@ -292,6 +290,19 @@ def check_forward_backward(model_fn, data_gen_fn, output_transform_fn, loss_fn,
"enable_gradient_checkpointing": True,
"parallel_output": False,
},
{
"tp_size": 2,
"pp_size": 2,
"pp_style": "zbv",
"num_model_chunks": 2,
"num_microbatches": 4,
"enable_all_optimization": False,
"precision": "fp16",
"zero_stage": 1,
"initial_scale": 1,
"enable_gradient_checkpointing": True,
"parallel_output": False,
},
],
)
def run_llama_test(test_config):
Expand Down

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