GitLab

Co-authored-by: Yuanchen Xu <yuanchen.xu00@gmail.com>

* [NFC] polish colossalai/context/random/__init__.py code style

* [NFC] polish applications/Chat/coati/models/utils.py code style

Co-authored-by: henryqin1997 <henryqin1997@gamil.com>

Co-authored-by: Yuanchen Xu <yuanchen.xu00@gmail.com>

test t5

* feat: remove on_learn_epoch fn as not used

* revert: add _on_learn_epoch fn

* feat: remove NaiveStrategy

* test: update train_prompts tests

* fix: remove prepare_llama_tokenizer_and_embedding

* test: add lora arg

* feat: remove roberta support in train_prompts due to runtime errs

* feat: remove deberta & roberta in rm as not used

* test: remove deberta and roberta tests

* feat: remove deberta and roberta models as not used

* fix: remove calls to roberta

* fix: remove prepare_llama_tokenizer_and_embedding

* chore: update transformers version

* docs: update transformers version

* fix: fix actor inference

* fix: fix ci

* feat: change llama pad token to unk

* revert: revert ddp setup_distributed

* fix: change llama pad token to unk

* revert: undo unnecessary changes

* fix: use pip to install transformers

* feat: remove on_learn_epoch fn as not used

* revert: add _on_learn_epoch fn

* to: remove the use of NaiveStrategy

* test: remove NaiveStrategy tests

* feat: remove NaiveStrategy

* style: modify comments and params

* feat: split ColossalAIStrategy into LowLevelZeroStrategy and GeminiStrategy

* fix: remove naive

* fix: align with modified colossal strategy

* fix: fix ddp _try_init_dist arg

* to: add SLTrainer

* refactor: refactor RMTrainer and SFTTrainer

* fix: fix init file

* feat: remove on_learn_epoch fn as not used

* fix: align with modified gemini arguments

* to: add OnPolicyTrainer

* revert: add _on_learn_epoch fn

* refactor: refactor PPOTrainer

* style: rename PPOTrainer argument

* fix: align with modified PPO arguments

* test: align with modified train_prompts arguments

* chore: modify train_prompts

* docs: align with modified arguments

* fix: remove unnecessary output

* fix: move dataloader to fit fn of SLTrainer

* fix: move dataloader to fit fn of OnPolicyTrainer

* fix: modify usage of prompt and pretrain dataloader

* fix chat eval

* fix utils

* fix utils

* add comment

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Co-authored-by: Qianran Ma <qianranm@luchentech.com>

* refactor: adapt boost API in base and naive strategies

* fix: initialize plugin after setup_distributed

* fix: fix save_pretrained fn

* refactor: adapt boost API in DDPStrategy

* to: add _post_init check

* to: fix ddp backward, modify ddp dataloader and unwrap

* feat: adapt boost API in ColossalAIStrategy

* fix: call setup_distributed before use get_current_device

* fix: fix save_model and save_optimizer

* test: remove save_sharded_optimizer test

* style: apply formatter

* fix: fix stage check and add comments

* feat: allow dict type arg in strategy.prepare

* to: temporarily remove lr_scheduler for testing

* style: simplify init of ColossalAIStrategy

* fix: fix lr_scheduler in sft and rm

* style: modify comments

* test: add train_prompts tests

* fix: fix inference only case and use in train_prompts

* test: skip failed tests in ci

* style: fix CodeFactor check

* fix: do not use model.to('cpu') with GeminiPlugin

* test: enable colossalai_gemini tests

* test: set CUDA_VISIBLE_DEVICES in ci

* docs: add note

Co-authored-by: Yuanchen Xu <yuanchen.xu00@gmail.com>

* refactor: separate log_probs fn from Actor forward fn

* refactor: separate generate fn from Actor class

* feat: update unwrap_model and get_base_model
* unwrap_model returns model not wrapped by Strategy
* get_base_model returns HF model for Actor, Critic and RewardModel

* feat: simplify Strategy.prepare

* style: remove get_base_model method of Actor

* perf: tokenize text in batches

* refactor: move calc_action_log_probs to utils of model

* test: update test with new forward fn

* style: rename forward fn args

* fix: do not unwrap model in save_model fn of naive strategy

* test: add gemini test for train_prompts

* fix: fix _set_default_generate_kwargs

Co-authored-by: Yuanchen Xu <yuanchen.xu00@gmail.com>

* Detached ppo (#9)

* run the base

* working on dist ppo

* sync

* detached trainer

* update detached trainer. no maker update function

* facing init problem

* 1 maker 1 trainer detached run. but no model update

* facing cuda problem

* fix save functions

* verified maker update

* nothing

* add ignore

* analyize loss issue

* remove some debug codes

* facing 2m1t stuck issue

* 2m1t verified

* do not use torchrun

* working on 2m2t

* working on 2m2t

* initialize strategy in ray actor env

* facing actor's init order issue

* facing ddp model update issue (need unwarp ddp)

* unwrap ddp actor

* checking 1m2t stuck problem

* nothing

* set timeout for trainer choosing. It solves the stuck problem!

* delete some debug output

* rename to sync with upstream

* rename to sync with upstream

* coati rename

* nothing

* I am going to detach the replaybuffer from trainer and make it a Ray Actor. Two benefits: 1. support TP trainer. 2. asynchronized buffer operations

* experience_maker_holder performs target-revolving _send_experience() instead of length comparison.

* move code to ray subfolder

* working on pipeline inference

* apply comments

* working on pipeline strategy. in progress.

* remove pipeline code. clean this branch

* update remote parameters by state_dict. no test

* nothing

* state_dict sharding transfer

* merge debug branch

* gemini _unwrap_model fix

* simplify code

* simplify code & fix LoRALinear AttributeError

* critic unwrapped state_dict

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Co-authored-by: csric <richcsr256@gmail.com>

* [chat] add perfomance evaluator and fix bugs (#10)

* [chat] add performance evaluator for ray

* [chat] refactor debug arg

* [chat] support hf config

* [chat] fix generation

* [chat] add 1mmt dummy example

* [chat] fix gemini ckpt

* split experience to send (#11)
Co-authored-by: csric <richcsr256@gmail.com>

* [chat] refactor trainer and maker (#12)

* [chat] refactor experience maker holder

* [chat] refactor model init

* [chat] refactor trainer args

* [chat] refactor model init

* [chat] refactor trainer

* [chat] refactor experience sending logic and training loop args (#13)

* [chat] refactor experience send logic

* [chat] refactor trainer

* [chat] refactor trainer

* [chat] refactor experience maker

* [chat] refactor pbar

* [chat] refactor example folder (#14)

* [chat] support quant (#15)

* [chat] add quant

* [chat] add quant example

* prompt example (#16)

* prompt example

* prompt load csv data

* remove legacy try

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Co-authored-by: csric <richcsr256@gmail.com>

* [chat] add mmmt dummy example and refactor experience sending (#17)

* [chat] add mmmt dummy example

* [chat] refactor naive strategy

* [chat] fix struck problem

* [chat] fix naive strategy

* [chat] optimize experience maker sending logic

* [chat] refactor sending assignment

* [chat] refactor performance evaluator (#18)

* Prompt Example & requires_grad state_dict & sharding state_dict (#19)

* prompt example

* prompt load csv data

* remove legacy try

* maker models require_grad set to False

* working on zero redundancy update

* mmmt_prompt example; naive strategy requires_grad state_dict & sharding; maker model requires_no_grad.

* remove legacy examples

* remove legacy examples

* remove replay buffer tp state. bad design

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Co-authored-by: csric <richcsr256@gmail.com>

* state_dict sending adapts to new unwrap function (#20)

* prompt example

* prompt load csv data

* remove legacy try

* maker models require_grad set to False

* working on zero redundancy update

* mmmt_prompt example; naive strategy requires_grad state_dict & sharding; maker model requires_no_grad.

* remove legacy examples

* remove legacy examples

* remove replay buffer tp state. bad design

* opt benchmark

* better script

* nothing

* [chat] strategy refactor unwrap model

* [chat] strategy refactor save model

* [chat] add docstr

* [chat] refactor trainer save model

* [chat] fix strategy typing

* [chat] refactor trainer save model

* [chat] update readme

* [chat] fix unit test

* working on lora reconstruction

* state_dict sending adapts to new unwrap function

* remove comments

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Co-authored-by: csric <richcsr256@gmail.com>
Co-authored-by: ver217 <lhx0217@gmail.com>

* [chat-ray] add readme (#21)

* add readme

* transparent graph

* add note background

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Co-authored-by: csric <richcsr256@gmail.com>

* [chat] get images from url (#22)

* Refactor/chat ray (#23)

* [chat] lora add todo

* [chat] remove unused pipeline strategy

* [chat] refactor example structure

* [chat] setup ci for ray

* [chat-ray] Support LoRA trainer. LoRA weights reconstruction. (#24)

* lora support prototype

* lora support

* 1mmt lora & remove useless code

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Co-authored-by: csric <richcsr256@gmail.com>

* [chat] fix test ci for ray

* [chat] fix test ci requirements for ray

* [chat] fix ray runtime env

* [chat] fix ray runtime env

* [chat] fix example ci docker args

* [chat] add debug info in trainer

* [chat] add nccl debug info

* [chat] skip ray test

* [doc] fix typo

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Co-authored-by: csric <59389055+CsRic@users.noreply.github.com>
Co-authored-by: csric <richcsr256@gmail.com>

Co-authored-by: Yuanchen Xu <yuanchen.xu00@gmail.com>

* fix a bug when the config file contains one category but the answer file doesn't contains that category

* fix Chinese prompt file

* support gpt-3.5-turbo and gpt-4 evaluation

* polish and update README

* resolve pr comments

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Co-authored-by: Yuanchen Xu <yuanchen.xu00@gmail.com>

* fix typo colossalai/autochunk auto_parallel amp

* fix typo colossalai/auto_parallel nn utils etc.

* fix typo colossalai/auto_parallel autochunk fx/passes  etc.

* fix typo docs/

* change placememt_policy to placement_policy in docs/ and examples/

* fix typo colossalai/ applications/

* add functions for gpt evaluation

* add automatic eval

Update eval.py

* using jload and modify the type of answers1 and answers2

* Update eval.py

Update eval.py

* Update evaluator.py

* support gpt evaluation

* update readme.md

update README.md

update READNE.md

modify readme.md

* add Chinese example for config, battle prompt and evaluation prompt file

* remove GPT-4 config

* remove sample folder

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Co-authored-by: Yuanchen Xu <yuanchen.xu00@gmail.com>
Co-authored-by: Camille Zhong <44392324+Camille7777@users.noreply.github.com>

* fix typo colossalai/autochunk auto_parallel amp

* fix typo colossalai/auto_parallel nn utils etc.

Co-authored-by: github-actions <github-actions@github.com>

Co-authored-by: Yuanchen Xu <yuanchen.xu00@gmail.com>

* fix spelling error with examples/comminity/

* fix spelling error with tests/

* fix some spelling error with tests/ colossalai/ etc.

Co-authored-by: jiangwen <zxl265370@antgroup.com>

* fix gemini strategy bug

* add comment

* add comment

* better solution