[RLlib] Use config (not self.config) in Learner.compute_loss_for_module to prepare these for multi-agent-capability.
#45053
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sven1977
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ArturNiederfahrenhorst,
maxpumperla,
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simonsays1980
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…ics_do_over_03_learner_on_new_metrics_logger Signed-off-by: sven1977 <svenmika1977@gmail.com> # Conflicts: # rllib/algorithms/ppo/ppo_learner.py # rllib/algorithms/ppo/tf/ppo_tf_learner.py # rllib/algorithms/ppo/torch/ppo_torch_learner.py
sven1977
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simonsays1980
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May 2, 2024
| @@ -72,7 +72,7 @@ def compute_loss_for_module( | |||
| trajectory_len=rollout_frag_or_episode_len, | |||
| recurrent_seq_len=recurrent_seq_len, | |||
| ) | |||
| if self.config.enable_env_runner_and_connector_v2: | |||
| if config.enable_env_runner_and_connector_v2: | |||
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I wonder, if the new env runners work on APPO/IMPALA. In my test case they do not in the MA case where a list of episodes is tried to be compressed_if_needed
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IMPALA and APPO are WIP on the new EnvRunners, officially not supported yet.
https://docs.ray.io/en/master/rllib/rllib-new-api-stack.html
| @@ -61,7 +61,7 @@ def compute_loss_for_module( | |||
| ).squeeze() | |||
|
|
|||
| # Use double Q learning. | |||
| if self.config.double_q: | |||
| if config.double_q: | |||
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Great catch. I had the same changed in another PR on the side. This would have been led to some bugs in MA off-policy.
| ).items() | ||
| } | ||
| ) | ||
| for module_id in set(loss_per_module.keys()) - {ALL_MODULES}: |
…self_config_in_learner_compute_loss Signed-off-by: sven1977 <svenmika1977@gmail.com> # Conflicts: # rllib/algorithms/sac/torch/sac_torch_learner.py
harborn
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…_module` to prepare these for multi-agent-capability. (ray-project#45053)
peytondmurray
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May 13, 2024
…_module` to prepare these for multi-agent-capability. (ray-project#45053) Signed-off-by: pdmurray <peynmurray@gmail.com>
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…_module` to prepare these for multi-agent-capability. (ray-project#45053) Signed-off-by: Ryan O'Leary <ryanaoleary@google.com>
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…_module` to prepare these for multi-agent-capability. (ray-project#45053)
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Use
config(notself.config) inLearner.compute_loss_for_moduleto prepare these for multi-agent-capability.compute_gradientsto NOT use DEFAULT_POLICY anymore, but to actually loop through the different RLModules.Why are these changes needed?
Related issue number
Checks
git commit -s) in this PR.scripts/format.shto lint the changes in this PR.method in Tune, I've added it in
doc/source/tune/api/under thecorresponding
.rstfile.