GitLab

* fix script

* fix script

* fix chat nan

* fix chat nan

* feat: modify forward fn of critic and reward model

* feat: modify calc_action_log_probs

* to: add wandb in sft and rm trainer

* feat: update train_sft

* feat: update train_rm

* style: modify type annotation and add warning

* feat: pass tokenizer to ppo trainer

* to: modify trainer base and maker base

* feat: add wandb in ppo trainer

* feat: pass tokenizer to generate

* test: update generate fn tests

* test: update train tests

* fix: remove action_mask

* feat: remove unused code

* fix: fix wrong ignore_index

* fix: fix mock tokenizer

* chore: update requirements

* revert: modify make_experience

* fix: fix inference

* fix: add padding side

* style: modify _on_learn_batch_end

* test: use mock tokenizer

* fix: use bf16 to avoid overflow

* fix: fix workflow

* [chat] fix gemini strategy

* [chat] fix

* sync: update colossalai strategy

* fix: fix args and model dtype

* fix: fix checkpoint test

* fix: fix requirements

* fix: fix missing import and wrong arg

* fix: temporarily skip gemini test in stage 3

* style: apply pre-commit

* fix: temporarily skip gemini test in stage 1&2

---------
Co-authored-by: Mingyan Jiang <1829166702@qq.com>

* [misc] update pre-commit

* [misc] run pre-commit

* [misc] remove useless configuration files

* [misc] ignore cuda for clang-format

* update configuration of chatglm and add support in coati

* add unit test & update chatglm default config & fix bos index issue

* remove chatglm due to oom

* add dataset pkg in requirement-text

* fix parameter issue in test_models

* add ref in tokenize & rm unnessary parts

* separate source & target tokenization in chatglm

* add unit test to chatglm

* fix test dataset issue

* update truncation of chatglm

* fix Colossalai version

* fix colossal ai version in test

* 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

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

* fix typo colossalai/autochunk auto_parallel amp

* fix typo colossalai/auto_parallel nn utils etc.

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

* [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

* Add RoBERTa for RLHF Stage 2 & 3 (test)

RoBERTa for RLHF Stage 2 & 3 (still in testing)

* Revert "Add RoBERTa for RLHF Stage 2 & 3 (test)"

This reverts commit 06741d894dcbe958acd4e10d771f22275e20e368.

* Add RoBERTa for RLHF stage 2 & 3

1. add roberta folder under model folder
2. add  roberta option in train_reward_model.py
3. add some test in testci

* Update test_ci.sh

* Revert "Update test_ci.sh"

This reverts commit 9c7352b81766f3177d31eeec0ec178a301df966a.

* Add RoBERTa for RLHF Stage 2 & 3 (test)

RoBERTa for RLHF Stage 2 & 3 (still in testing)

* Revert "Add RoBERTa for RLHF Stage 2 & 3 (test)"

This reverts commit 06741d894dcbe958acd4e10d771f22275e20e368.

* Add RoBERTa for RLHF stage 2 & 3

1. add roberta folder under model folder
2. add  roberta option in train_reward_model.py
3. add some test in testci

* Update test_ci.sh

* Revert "Update test_ci.sh"

This reverts commit 9c7352b81766f3177d31eeec0ec178a301df966a.

* update roberta with coati

* chat ci update

* Revert "chat ci update"

This reverts commit 17ae7ae01fa752bd3289fc39069868fde99cf846.

* [Chat] fix the tokenizer "int too big to convert" error in SFT training

fix the tokenizer error during SFT training using Bloom and OPT