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’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

🫔 [GRPO] Pass wrapped model to unwrap_model_for_generation for DeepSpeed Stage-3 compatibility #2871

Merged
merged 2 commits into from
Feb 28, 2025
Merged

🫔 [GRPO] Pass wrapped model to unwrap_model_for_generation for DeepSpeed Stage-3 compatibility #2871

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
fa4bd36
fix: pass wrapped model for unwrap_model_for_generation
kiddj Feb 15, 2025
dc9079c
Merge branch 'main' into fix-deepspeed-stage3-integration
qgallouedec Feb 28, 2025
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
4 changes: 2 additions & 2 deletions trl/trainer/grpo_trainer.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -655,7 +655,7 @@ def _get_per_token_logps(self, model, input_ids, attention_mask, logits_to_keep)
@profiling_decorator
def _move_model_to_vllm(self):
with unwrap_model_for_generation(
self.model, self.accelerator, gather_deepspeed3_params=self.args.ds3_gather_for_generation
self.model_wrapped, self.accelerator, gather_deepspeed3_params=self.args.ds3_gather_for_generation
) as unwrapped_model:
if is_compiled_module(unwrapped_model):
unwrapped_model = unwrapped_model._orig_mod
Expand Down Expand Up @@ -754,7 +754,7 @@ def _generate_and_score_completions(
prompt_completion_ids = torch.cat([prompt_ids, completion_ids], dim=1)
else:
# Regular generation path
with unwrap_model_for_generation(self.model, self.accelerator) as unwrapped_model:
with unwrap_model_for_generation(self.model_wrapped, self.accelerator) as unwrapped_model:
prompt_completion_ids = unwrapped_model.generate(
prompt_ids, attention_mask=prompt_mask, generation_config=self.generation_config
)
Expand Down
Loading