Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We鈥檒l occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

[chatgpt] fix trainer generate kwargs #3166

Merged
merged 1 commit into from
Mar 17, 2023
Merged

[chatgpt] fix trainer generate kwargs #3166

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
20 changes: 12 additions & 8 deletions applications/ChatGPT/chatgpt/trainer/ppo.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -63,6 +63,7 @@ def __init__(self,
**generate_kwargs) -> None:
experience_maker = NaiveExperienceMaker(actor, critic, reward_model, initial_model, kl_coef)
replay_buffer = NaiveReplayBuffer(train_batch_size, buffer_limit, buffer_cpu_offload)
generate_kwargs = _set_default_generate_kwargs(strategy, generate_kwargs, actor)
super().__init__(strategy, experience_maker, replay_buffer, experience_batch_size, max_epochs, tokenizer,
sample_replay_buffer, dataloader_pin_memory, callbacks, **generate_kwargs)
self.actor = actor
Expand All @@ -73,7 +74,6 @@ def __init__(self,

self.actor_optim = actor_optim
self.critic_optim = critic_optim
self._set_default_generate_kwargs(generate_kwargs, actor)

def training_step(self, experience: Experience) -> Dict[str, float]:
self.actor.train()
Expand Down Expand Up @@ -102,11 +102,15 @@ def training_step(self, experience: Experience) -> Dict[str, float]:

return {'actor_loss': actor_loss.item(), 'critic_loss': critic_loss.item()}

def _set_default_generate_kwargs(self, generate_kwargs: dict, actor: Actor) -> None:
origin_model = self.strategy._unwrap_actor(actor)
# use huggingface models method directly
if 'prepare_inputs_fn' not in generate_kwargs and hasattr(origin_model, 'prepare_inputs_for_generation'):
generate_kwargs['prepare_inputs_fn'] = origin_model.prepare_inputs_for_generation

if 'update_model_kwargs_fn' not in generate_kwargs:
generate_kwargs['update_model_kwargs_fn'] = update_model_kwargs_fn
def _set_default_generate_kwargs(strategy: Strategy, generate_kwargs: dict, actor: Actor) -> None:
origin_model = strategy._unwrap_actor(actor)
new_kwargs = {**generate_kwargs}
# use huggingface models method directly
if 'prepare_inputs_fn' not in generate_kwargs and hasattr(origin_model, 'prepare_inputs_for_generation'):
new_kwargs['prepare_inputs_fn'] = origin_model.prepare_inputs_for_generation

if 'update_model_kwargs_fn' not in generate_kwargs:
new_kwargs['update_model_kwargs_fn'] = update_model_kwargs_fn

return new_kwargs