* 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
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* [Feature] deepseek support via auto model, remove modeling file
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* [Feature/deepseek] resolve comment. (#5889)
* [misc] fix typos
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* [Hoxfix] Fix CUDA_DEVICE_MAX_CONNECTIONS for comm overlap
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* [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
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* [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
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* 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)
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* [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 <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
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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
* 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
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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
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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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 2f9bce6686.
* [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
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* support auto distributed data loader
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* fix tp error
* remove unused parameters
* remove unused
* update inference
* update docs
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* [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
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* fix typo
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* shardformer fp8
* fix rebase
* remove all to all
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* [fp8] support all-gather flat tensor (#5932)
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* fix
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* fix test bugs
* add do sample test
* del useless lines
* fix comments
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* delete version tag
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* add
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* Revert "add"
This reverts commit b9305fb024.
* clean requirements
* modify example inference struct
* add test ci scripts
* mark test_infer as submodule
* rm deprecated cls & deps
* import of HAS_FLASH_ATTN
* prune inference tests to be run
* prune triton kernel tests
* increment pytest timeout mins
* revert import path in openmoe
* [misc] remove config arg from initialize
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* [plugin] add npu support for ddp
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* [devops] fix doc test ci
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* optimize flashdecodingattention: refactor code with different key cache layout(from [num_blocks, num_kv_heads, block_size, head_size] to [num_blocks, num_kv_heads, head_size/x, block_size, x])
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* feat flash decoding for paged attention
* refactor flashdecodingattention
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* Adapted to the baichuan2-7B model
* modified according to the review comments.
* Modified the method of obtaining random weights.
* modified according to the review comments.
* change mlp layewr 'NOTE'
* add cuda KVCache kernel
* annotation benchmark_kvcache_copy
* add use cuda
* fix import path
* move benchmark scripts to example/
* rm benchmark codes in test_kv_cache_memcpy.py
* rm redundancy codes
* rm redundancy codes
* pr was modified according to the review