Skip to content

fix: correct final_value extraction in PPO compute_advantages #970

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

Open
dajiaohuang wants to merge 1 commit into
base: master
Choose a base branch
from
Open

fix: correct final_value extraction in PPO compute_advantages #970

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
8 changes: 5 additions & 3 deletions tf_agents/agents/ppo/ppo_agent.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -460,13 +460,15 @@ def compute_advantages(
advantages: Tensor of length (len(rewards) - 1), because the final
timestep is just used for next-step value prediction.
"""
# Arg value_preds was appended with final next_step value. Make tensors
# next_value_preds by stripping first and last elements respectively.
# Arg value_preds was appended with final next_step value. Extract the
# final value before stripping to get the correct final_value for GAE,
# then strip the last element to get the values sequence.
final_value_preds = value_preds[:, -1]
value_preds = value_preds[:, :-1]
if self._use_gae:
advantages = value_ops.generalized_advantage_estimation(
values=value_preds,
final_value=value_preds[:, -1],
final_value=final_value_preds,
rewards=rewards,
discounts=discounts,
td_lambda=self._lambda,
Expand Down
Loading