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[chat]: update rm, add wandb and fix bugs (#4471)

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* 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>
This commit is contained in:
Wenhao Chen
2023-09-20 15:53:58 +08:00
committed by GitHub
parent 07c2e3d09c
commit 7b9b86441f
36 changed files with 382 additions and 332 deletions
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4
applications/Chat/benchmarks/benchmark_opt_lora_dummy.py
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@@ -138,6 +138,7 @@ def main(args):
tokenizer = AutoTokenizer.from_pretrained("facebook/opt-350m")
tokenizer.pad_token = tokenizer.eos_token
tokenizer.padding_side = "left"
(actor, actor_optim), (critic, critic_optim) = strategy.prepare((actor, actor_optim), (critic, critic_optim))
@@ -154,6 +155,7 @@ def main(args):
initial_model,
actor_optim,
critic_optim,
tokenizer=tokenizer,
ptx_coef=0,
train_batch_size=args.train_batch_size,
offload_inference_models=args.offload_inference_models,
@@ -162,8 +164,6 @@ def main(args):
temperature=1.0,
top_k=50,
use_cache=True,
pad_token_id=tokenizer.pad_token_id,
eos_token_id=tokenizer.eos_token_id,
callbacks=[performance_evaluator],
)