079bf3cb26
[misc] update pre-commit and run all files ( #4752 )
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* [misc] update pre-commit
* [misc] run pre-commit
* [misc] remove useless configuration files
* [misc] ignore cuda for clang-format
2023-09-19 14:20:26 +08:00
da4f7b855f
[chat] fix bugs and add unit tests ( #4213 )
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* style: rename replay buffer
Experience replay is typically for off policy algorithms.
Use this name in PPO maybe misleading.
* fix: fix wrong zero2 default arg
* test: update experience tests
* style: rename zero_pad fn
* fix: defer init in CycledDataLoader
* test: add benchmark test
* style: rename internal fn of generation
* style: rename internal fn of lora
* fix: remove unused loss fn
* fix: remove unused utils fn
* refactor: remove generate_with_actor fn
* fix: fix type annotation
* test: add models tests
* fix: skip llama due to long execution time
* style: modify dataset
* style: apply formatter
* perf: update reward dataset
* fix: fix wrong IGNORE_INDEX in sft dataset
* fix: remove DataCollatorForSupervisedDataset
* test: add dataset tests
* style: apply formatter
* style: rename test_ci to test_train
* feat: add llama in inference
* test: add inference tests
* test: change test scripts directory
* fix: update ci
* fix: fix typo
* fix: skip llama due to oom
* fix: fix file mod
* style: apply formatter
* refactor: remove duplicated llama_gptq
* style: apply formatter
* to: update rm test
* feat: add tokenizer arg
* feat: add download model script
* test: update train tests
* fix: modify gemini load and save pretrained
* test: update checkpoint io test
* to: modify nproc_per_node
* fix: do not remove existing dir
* fix: modify save path
* test: add random choice
* fix: fix sft path
* fix: enlarge nproc_per_node to avoid oom
* fix: add num_retry
* fix: make lora config of rm and critic consistent
* fix: add warning about lora weights
* fix: skip some gpt2 tests
* fix: remove grad ckpt in rm and critic due to errors
* refactor: directly use Actor in train_sft
* test: add more arguments
* fix: disable grad ckpt when using lora
* fix: fix save_pretrained and related tests
* test: enable zero2 tests
* revert: remove useless fn
* style: polish code
* test: modify test args
2023-08-02 10:17:36 +08:00
caa4433072
[NFC] fix format of application/Chat/coati/trainer/utils.py ( #4273 )
2023-07-26 14:12:57 +08:00
b03d64d010
[chat] refactor trainer class ( #4080 )
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* 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
2023-06-29 10:48:09 +08:00
2a951955ad
[chat] refactor trainer ( #3648 )
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* [chat] ppo trainer remove useless args
* [chat] update examples
* [chat] update benchmark
* [chat] update examples
* [chat] fix sft training with wandb
* [chat] polish docstr
2023-04-26 18:11:49 +08:00
e355144375
[chatgpt] Detached PPO Training ( #3195 )
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* 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
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Co-authored-by: csric <richcsr256@gmail.com>
2023-04-17 14:46:50 +08:00
b0ce5a1032
[Coati] first commit ( #3283 )
2023-03-28 20:25:36 +08:00
Hongxin Liu