mirror of
https://github.com/hpcaitech/ColossalAI.git
synced 2025-08-19 08:27:23 +00:00
b5f0566363
* 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>
57 lines
1.6 KiB
YAML
57 lines
1.6 KiB
YAML
name: Run ChatGPT examples
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on:
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pull_request:
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types: [synchronize, opened, reopened]
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paths:
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- 'applications/Chat/coati/**'
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- 'applications/Chat/requirements.txt'
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- 'applications/Chat/setup.py'
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- 'applications/Chat/examples/**'
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jobs:
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tests:
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name: Run ChatGPT examples
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if: |
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github.event.pull_request.draft == false &&
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github.base_ref == 'main' &&
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github.event.pull_request.base.repo.full_name == 'hpcaitech/ColossalAI'
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runs-on: [self-hosted, gpu]
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container:
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image: hpcaitech/pytorch-cuda:1.12.0-11.3.0
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options: --gpus all --rm -v /data/scratch/github_actions/chat:/data/scratch/github_actions/chat --shm-size=10.24gb
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timeout-minutes: 30
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defaults:
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run:
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shell: bash
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steps:
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- name: Checkout ColossalAI
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uses: actions/checkout@v2
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- name: Install ColossalAI and ChatGPT
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run: |
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pip install -e .
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cd applications/Chat
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pip install -v .
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pip install -r examples/requirements.txt
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- name: Install Transformers
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run: |
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cd applications/Chat
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git clone https://github.com/hpcaitech/transformers
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cd transformers
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pip install -v .
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- name: Execute Examples
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run: |
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cd applications/Chat
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rm -rf ~/.cache/colossalai
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./examples/test_ci.sh
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env:
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NCCL_SHM_DISABLE: 1
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MAX_JOBS: 8
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SFT_DATASET: /data/scratch/github_actions/chat/data.json
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PROMPT_PATH: /data/scratch/github_actions/chat/prompts_en.jsonl
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PRETRAIN_DATASET: /data/scratch/github_actions/chat/alpaca_data.json
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