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* Revert "Revert "[RLlib] POC: `PGTrainer` class that works by sub-classing, not `trainer_template.py`. (#20055)" (#20284)"
This reverts commit 246787cdd9.
Co-authored-by: sven1977 <svenmika1977@gmail.com>
35 lines
1.2 KiB
Python
35 lines
1.2 KiB
Python
from typing import Type
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from ray.rllib.agents.trainer import Trainer
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from ray.rllib.agents.pg.default_config import DEFAULT_CONFIG
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from ray.rllib.agents.pg.pg_tf_policy import PGTFPolicy
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from ray.rllib.agents.pg.pg_torch_policy import PGTorchPolicy
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from ray.rllib.policy.policy import Policy
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from ray.rllib.utils.annotations import override
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from ray.rllib.utils.typing import TrainerConfigDict
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class PGTrainer(Trainer):
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"""Policy Gradient (PG) Trainer.
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Defines the distributed Trainer class for policy gradients.
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See `pg_[tf|torch]_policy.py` for the definition of the policy losses for
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TensorFlow and PyTorch.
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Detailed documentation:
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https://docs.ray.io/en/master/rllib-algorithms.html#pg
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Only overrides the default config- and policy selectors
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(`get_default_policy` and `get_default_config`). Utilizes
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the default `execution_plan()` of `Trainer`.
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"""
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@override(Trainer)
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def get_default_policy_class(self, config) -> Type[Policy]:
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return PGTorchPolicy if config.get("framework") == "torch" \
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else PGTFPolicy
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@classmethod
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@override(Trainer)
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def get_default_config(cls) -> TrainerConfigDict:
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return DEFAULT_CONFIG
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