7 Commits (711e2b4c00d68083af64dd2422f33c3b08d42856)

Author	SHA1	Message	Date
Wenhao Chen	153b957a1b	[chat] refactor strategy class with booster api (#3987) ... * 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	1 year ago
Hongxin Liu	b5f0566363	[chat] add distributed PPO trainer (#3740) ... * 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 --------- 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 --------- 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 --------- 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 --------- 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 --------- 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 --------- 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 --------- Co-authored-by: csric <59389055+CsRic@users.noreply.github.com> Co-authored-by: csric <richcsr256@gmail.com>	1 year ago
Hongxin Liu	7bd0bee8ea	[chat] add opt attn kernel (#3655) ... * [chat] add opt attn kernel * [chat] disable xformer during fwd	2 years ago
Hongxin Liu	2a951955ad	[chat] refactor trainer (#3648) ... * [chat] ppo trainer remove useless args * [chat] update examples * [chat] update benchmark * [chat] update examples * [chat] fix sft training with wandb * [chat] polish docstr	2 years ago
Hongxin Liu	50793b35f4	[gemini] accelerate inference (#3641) ... * [gemini] support don't scatter after inference * [chat] update colossalai strategy * [chat] fix opt benchmark * [chat] update opt benchmark * [gemini] optimize inference * [test] add gemini inference test * [chat] fix unit test ci * [chat] fix ci * [chat] fix ci * [chat] skip checkpoint test	2 years ago
Yuanchen	1ec0d386a9	reconstruct chat trainer and fix training script (#3588) ... Co-authored-by: Yuanchen Xu <yuanchen.xu00@gmail.com>	2 years ago
Fazzie-Maqianli	b0ce5a1032	[Coati] first commit (#3283)	2 years ago