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* add mixtral auto policy & move pipeline forward code to modeling folder
* [moe refactor] modify kernel test without Route Class
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* fix typos
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* fix typo
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* remove some useless code
* fix typo & unify global variable XX_AXIS logic without using -1
* fix typo & prettifier the code
* remove print code & support zero 2 test
* remove useless code
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* fix typo
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* [moe refactor] change test model from fake moe model to mixtral moe layer and remove useless test
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* [moe refactor] fix unit import error
* [moe refactor] fix circular import issues
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* [Feature] MoE refactor with newest version of ZeRO (#5801)
* [zero] remove redundant members in BucketStore (#5802)
* [zero] align api with previous version
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* [moe refactor] update unit test with the refactored ZeRO and remove useless test
* move moe checkpoint to checkpoint folder and exchange global axis to class member
* update moe hybrid parallel plugin with newest version of zero & fix zero working/master params bug
* fix zero unit test
* Add an assertion to prevent users from using it incorrectly
* [hotfix]Solve the compatibility issue of zero refactor (#5823)
* [moe refactor] update unit test with the refactored ZeRO and remove useless test
* move moe checkpoint to checkpoint folder and exchange global axis to class member
* update moe hybrid parallel plugin with newest version of zero & fix zero working/master params bug
* fix zero unit test
* Add an assertion to prevent users from using it incorrectly
* Modify function parameter names to resolve compatibility issues
* [zero] fix missing hook removal (#5824)
* [MoE] Resolve .github conflict (#5829)
* [Fix/Example] Fix Llama Inference Loading Data Type (#5763)
* [fix/example] fix llama inference loading dtype
* revise loading dtype of benchmark llama3
* [release] update version (#5752)
* [release] update version
* [devops] update compatibility test
* [devops] update compatibility test
* [devops] update compatibility test
* [devops] update compatibility test
* [test] fix ddp plugin test
* [test] fix gptj and rpc test
* [devops] fix cuda ext compatibility
* [inference] fix flash decoding test
* [inference] fix flash decoding test
* fix (#5765)
* [test] Fix/fix testcase (#5770)
* [fix] branch for fix testcase;
* [fix] fix test_analyzer & test_auto_parallel;
* [fix] remove local change about moe;
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* [Hotfix] Add missing init file in inference.executor (#5774)
* [CI/tests] simplify some test case to reduce testing time (#5755)
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* [ci/tests] continue to remove test case to reduce ci time cost
* restore some test config
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* [misc] update dockerfile (#5776)
* [misc] update dockerfile
* [misc] update dockerfile
* [devops] fix docker ci (#5780)
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* modified according to the opinions of review
* add Citation
* change _block_tables tolist
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Co-authored-by: Edenzzzz <wtan45@wisc.edu>
* [Test/CI] remove test cases to reduce CI duration (#5753)
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Some tests might depend on the size of model (num of chunks)
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* [CI] smaller test model for two mwo the two modifid cases
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* [fix] remove local change about moe;
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* [fix] fix test_hf_albert & test_hf_gpt;
* [gemini] optimize reduce scatter d2h copy (#5760)
* [gemini] optimize reduce scatter d2h copy
* [fix] fix missing reduce variable
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* [gemini] missing sync
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* [gemini] further optimize with async all reduce
* [fix] pass flag from manager to chunk
* Allow building cuda extension without a device. (#5535)
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* [misc] fix dist logger (#5782)
* [install]fix setup (#5786)
* fix
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* [misc] update requirements (#5787)
* [shardformer] fix import (#5788)
* upgrade colossal-chat support tp_group>1, add sp for sft
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* fix training script
* fix ci
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* fix transformers version
* remove duplicated test
* fix datasets version
* remove models that require huggingface auth from ci
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* Fix tests and naming
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* [shardformer] fix modeling of bloom and falcon (#5796)
* [test] fix qwen2 pytest distLarge (#5797)
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* [Gemini] Use async stream to prefetch and h2d data moving (#5781)
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* Remove redundant code
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* [gemini] quick fix on possible async operation
* [gemini] quick fix on possible async operation
* [shardformer] upgrade transformers to 4.39.3 (#5815)
* [shardformer]upgrade transformers for gpt2/gptj/whisper (#5807)
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---------
Co-authored-by: ver217 <lhx0217@gmail.com>
* [shardformer]upgrade transformers for mistral (#5808)
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* fix
* fix
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fix
* fix
* fix
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fix
* fix
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* fix
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* Support 4d parallel + flash attention (#5789)
* support tp + sp + pp
* remove comments
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* [zero] fix hook bug
* [zero] add low level optimizer back (#5839)
* [zero] fix param & refactor
* [zero] add back original low level opt
* [zero] remove moe related
* [zero] pass zero tests
* [zero] refactor
* [chore] add del func back
* [zero] comments and naming (#5840)
* [zero] modify api (#5843)
* [zero] modify api
* [test] remove _grad_store access in tests
* [test] fix (#5857)
* [CI] skip openmoe CI check
* [CI] fox pre-commit
* [zero] remove redundant memebr init (#5862)
* [misc] remove useless code, modify the pg mesh implementation
* [misc] remove useless code, modify the pg mesh implementation
* [misc] use tempfile
* resolve conflict with main branch
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* [misc] remove useless code
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* update to fully overlap, still debugging
* improve interface
* fixed deadlock bug
* debug NaN loss
* (experimental) use one comm group for send_fw_recv_fw to fix NaN
* cleaned up interfaces; use one batch p2p for all
* clean up; removed the double p2p batch case
* p2p test passsed
* improve overlap: send fwd before backward
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* tentatively use 2 p2p batches
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* [feat] Add distributed lamb; minor fixes in DeviceMesh (#5476)
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* [hotfix] Improve tester precision by removing ZeRO on vanilla lamb (#5576)
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* [optim] add distributed came (#5526)
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* test CAME zero pass
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* test distributed came passed
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* minor fix of test came
* minor fix of dist_came and test
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* [optim] Distributed Adafactor (#5484)
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* [feature] update optimize readme;
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* [feature] Add transformers_bert model zoo in testcase;
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* [feature] add API Reference & Sample to optimizer Readme; add state check for bert exam;
* [feature] modify user documentation;
* [fix] fix readme format issue;
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* [fix] fix percision issue;
* [feature] add distributed rms;
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* [feature] Extract distributed rms function;
* [feature] add booster + lowlevelzeroPlugin in test;
* [feature] add Start_with_booster_API case in md; add Supporting Information in md;
* [fix] Also remove state movement in base adafactor;
* [feature] extract factor function;
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* [fix] add tp=False and zero=True in logic;
* [fix] fix use zero logic;
* [feature] add row residue logic in column parallel factor;
* [feature] add check optim state func;
* [feature] Remove duplicate logic;
* [feature] update optim state check func and percision test bug;
* [fix] update/fix optim state; Still exist percision issue;
* [fix] Add use_zero check in _rms; Add plugin support info in Readme; Add Dist Adafactor init Info;
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* [feature] uodate Readme;
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* [fix] fix logic in _rms;
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* [Feature] refractor dist came; fix percision error; add low level zero test with bert model zoo; (#5676)
* [feature] daily update;
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* [Feature] Add Galore (Adam, Adafactor) and distributed GaloreAdamW8bit (#5570)
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* tests passed; located svd precision issue in fwd-bwd; banned these tests
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* sequence parallel optimization
* validate sequence parallel in llama (code to be polished)
* shardformer api writing
* integrate sequence parallel in ShardFormer
* fix pp bugs and sp bugs for LlaMa model
* integrating ring-based sequence parallelism into ShardFormer
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Co-authored-by: linsj20 <linsj20@mails.tsinghua.edu.cn>
* fix bugs when useing sp and flashattention together
* fix operation function name
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* clarify sp process group
* fix compatibility bugs in moe plugin
* fix fused linear bugs
* fix linear layer test
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* modify shard data dimension (meant to be dim=-1)
* support megtron-style sp and distributed attn for llama model
* [shardformer] add megatron sp to llama
* support llama7B 128k with distributed attention
* [shardformer] robustness enhancement
* add block attn
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* fix sp compatability
* finish sp mode 3 support for gpt
* using all_to_all_single when batch size is 1
* support mode 2 sp in gpt2 (#5)
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* support llama7B 128k with distributed attention
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* fix sp compatability
* refactor ring implementation
* support mode 2 sp in gpt2
* polish code
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* automatically enable flash attn when using sp mode 2 and 3 in llama
* inplace attn mask
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* polish code
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* fix gemini checkpoint io
* loose tensor checking atol and rtol
* add comment
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* fix zero grad
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* fix conflict
* update split and gather auto grad func
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* polish code (part 1)
* polish code (part 2)
* polish code (part 2.5)
* polish code (part 3)
* sequence parallel: inside text split
* miscellaneous minor fixes
* polish code
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* sequence parallel: inside text split
* miscellaneous minor fixes
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* fix llama and gpt sp
* polish code
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* remove zero_stage and unbind the grad sync for alltoall sp
* add 2d group creation test
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* fix: simplify merge_batch
* fix: use return_outputs=False to eliminate extra memory consumption
* feat: add return_outputs warning
* style: remove `return_outputs=False` as it is the default value
* test: add more p2p tests
* fix: remove send_forward_recv_forward as p2p op list need to use the same group
* fix: make send and receive atomic
* feat: update P2PComm fn
* feat: add metadata cache in 1f1b
* feat: add metadata cache in interleaved pp
* feat: modify is_xx_stage fn
* revert: add _broadcast_object_list
* feat: add interleaved pp in llama policy
* feat: set NCCL_BUFFSIZE in HybridParallelPlugin
* fix 3d checkpoint load when booster boost without optimizer
fix 3d checkpoint load when booster boost without optimizer
* test ci
* revert ci
* fix
fix
* [shardformer] implement policy for all GPT-J models and test
* [shardformer] support interleaved pipeline parallel for bert finetune
* [shardformer] shardformer support falcon (#4883)
* [shardformer]: fix interleaved pipeline for bert model (#5048)
* [hotfix]: disable seq parallel for gptj and falcon, and polish code (#5093)
* Add Mistral support for Shardformer (#5103)
* [shardformer] add tests to mistral (#5105)
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* [feature] support no master weights for low level zero plugin
* [feature] support no master weights for low level zero plugin, remove data copy when no master weights
* remove data copy and typecasting when no master weights
* not load weights to cpu when using no master weights
* fix grad: use fp16 grad when no master weights
* only do not update working param when no master weights
* fix: only do not update working param when no master weights
* fix: passing params in dict format in hybrid plugin
* fix: remove extra params (tp_process_group) in hybrid_parallel_plugin
Wang Binluo