def build_trainer(self, use_gpu: bool) -> SACTrainer:
actor_net_builder = self.actor_net_builder.value
# pyre-fixme[16]: `SAC` has no attribute `_actor_network`.
# pyre-fixme[16]: `SAC` has no attribute `_actor_network`.
self._actor_network = actor_net_builder.build_actor(
self.state_normalization_data, self.action_normalization_data)
critic_net_builder = self.critic_net_builder.value
# pyre-fixme[16]: `SAC` has no attribute `_q1_network`.
# pyre-fixme[16]: `SAC` has no attribute `_q1_network`.
self._q1_network = critic_net_builder.build_q_network(
self.state_normalization_data, self.action_normalization_data)
q2_network = (critic_net_builder.build_q_network(
self.state_normalization_data, self.action_normalization_data)
if self.use_2_q_functions else None)
value_network = None
if self.value_net_builder:
# pyre-fixme[16]: `Optional` has no attribute `value`.
# pyre-fixme[16]: `Optional` has no attribute `value`.
value_net_builder = self.value_net_builder.value
value_network = value_net_builder.build_value_network(
self.state_normalization_data)
trainer = SACTrainer(
actor_network=self._actor_network,
q1_network=self._q1_network,
value_network=value_network,
q2_network=q2_network,
# pyre-fixme[16]: `SACTrainerParameters` has no attribute `asdict`.
# pyre-fixme[16]: `SACTrainerParameters` has no attribute `asdict`.
**self.trainer_param.asdict(),
)
return trainer
def build_trainer(self) -> SACTrainer:
actor_net_builder = self.actor_net_builder.value
# pyre-fixme[16]: `SAC` has no attribute `_actor_network`.
# pyre-fixme[16]: `SAC` has no attribute `_actor_network`.
self._actor_network = actor_net_builder.build_actor(
self.state_normalization_data, self.action_normalization_data
)
critic_net_builder = self.critic_net_builder.value
# pyre-fixme[16]: `SAC` has no attribute `_q1_network`.
# pyre-fixme[16]: `SAC` has no attribute `_q1_network`.
self._q1_network = critic_net_builder.build_q_network(
self.state_normalization_data, self.action_normalization_data
)
q2_network = (
critic_net_builder.build_q_network(
self.state_normalization_data, self.action_normalization_data
)
if self.use_2_q_functions
else None
)
value_network = None
if self.value_net_builder:
# pyre-fixme[16]: `Optional` has no attribute `value`.
# pyre-fixme[16]: `Optional` has no attribute `value`.
value_net_builder = self.value_net_builder.value
value_network = value_net_builder.build_value_network(
self.state_normalization_data
)
if self.use_gpu:
self._q1_network.cuda()
if q2_network:
q2_network.cuda()
if value_network:
value_network.cuda()
self._actor_network.cuda()
# pyre-fixme[29]: `Type[reagent.training.sac_trainer.SACTrainer]` is not a
# function.
# pyre-fixme[29]: `Type[reagent.training.sac_trainer.SACTrainer]` is not a
# function.
trainer = SACTrainer(
actor_network=self._actor_network,
q1_network=self._q1_network,
value_network=value_network,
q2_network=q2_network,
use_gpu=self.use_gpu,
# pyre-fixme[16]: `SACTrainerParameters` has no attribute `asdict`.
# pyre-fixme[16]: `SACTrainerParameters` has no attribute `asdict`.
**self.trainer_param.asdict(),
)
return trainer
def build_trainer(self) -> SACTrainer:
actor_net_builder = self.actor_net_builder.value
# pyre-fixme[16]: `SAC` has no attribute `_actor_network`.
# pyre-fixme[16]: `SAC` has no attribute `_actor_network`.
self._actor_network = actor_net_builder.build_actor(
self.state_normalization_data, self.action_normalization_data
)
critic_net_builder = self.critic_net_builder.value
# pyre-fixme[16]: `SAC` has no attribute `_q1_network`.
# pyre-fixme[16]: `SAC` has no attribute `_q1_network`.
self._q1_network = critic_net_builder.build_q_network(
self.state_normalization_data, self.action_normalization_data
)
q2_network = (
critic_net_builder.build_q_network(
self.state_normalization_data, self.action_normalization_data
)
if self.use_2_q_functions
else None
)
value_network = None
if self.value_net_builder:
# pyre-fixme[16]: `Optional` has no attribute `value`.
# pyre-fixme[16]: `Optional` has no attribute `value`.
value_net_builder = self.value_net_builder.value
value_network = value_net_builder.build_value_network(
self.state_normalization_data
)
if self.use_gpu:
self._q1_network.cuda()
if q2_network:
q2_network.cuda()
if value_network:
value_network.cuda()
self._actor_network.cuda()
trainer = SACTrainer(
self._q1_network,
self._actor_network,
self.trainer_param,
value_network=value_network,
q2_network=q2_network,
use_gpu=self.use_gpu,
)
return trainer
def build_trainer(
self,
normalization_data_map: Dict[str, NormalizationData],
use_gpu: bool,
reward_options: Optional[RewardOptions] = None,
) -> SACTrainer:
actor_net_builder = self.actor_net_builder.value
actor_network = actor_net_builder.build_actor(
self.state_feature_config,
normalization_data_map[NormalizationKey.STATE],
normalization_data_map[NormalizationKey.ACTION],
)
critic_net_builder = self.critic_net_builder.value
q1_network = critic_net_builder.build_q_network(
normalization_data_map[NormalizationKey.STATE],
normalization_data_map[NormalizationKey.ACTION],
)
q2_network = (
critic_net_builder.build_q_network(
normalization_data_map[NormalizationKey.STATE],
normalization_data_map[NormalizationKey.ACTION],
)
if self.use_2_q_functions
else None
)
value_network = None
value_net_builder = self.value_net_builder
if value_net_builder:
value_net_builder = value_net_builder.value
value_network = value_net_builder.build_value_network(
normalization_data_map[NormalizationKey.STATE]
)
trainer = SACTrainer(
actor_network=actor_network,
q1_network=q1_network,
value_network=value_network,
q2_network=q2_network,
# pyre-fixme[16]: `SACTrainerParameters` has no attribute `asdict`.
# pyre-fixme[16]: `SACTrainerParameters` has no attribute `asdict`.
**self.trainer_param.asdict(),
)
return trainer
def build_trainer(self) -> SACTrainer:
actor_net_builder = self.actor_net_builder.value
# pyre-fixme[16]: `SoftActorCritic` has no attribute `_actor_network`.
# pyre-fixme[16]: `SoftActorCritic` has no attribute `_actor_network`.
self._actor_network = actor_net_builder.build_actor(
self.get_normalization_data(NormalizationKey.STATE),
self.get_normalization_data(NormalizationKey.ACTION),
)
critic_net_builder = self.critic_net_builder.value
q1_network = critic_net_builder.build_q_network(
self.state_normalization_parameters,
self.action_normalization_parameters)
q2_network = (critic_net_builder.build_q_network(
self.state_normalization_parameters,
self.action_normalization_parameters,
) if self.use_2_q_functions else None)
value_network = None
if self.value_net_builder:
# pyre-fixme[16]: `Optional` has no attribute `value`.
# pyre-fixme[16]: `Optional` has no attribute `value`.
value_net_builder = self.value_net_builder.value
value_network = value_net_builder.build_value_network(
self.get_normalization_data(NormalizationKey.STATE))
if self.use_gpu:
q1_network.cuda()
if q2_network:
q2_network.cuda()
if value_network:
value_network.cuda()
self._actor_network.cuda()
trainer = SACTrainer(
q1_network,
self._actor_network,
self.trainer_param,
value_network=value_network,
q2_network=q2_network,
use_gpu=self.use_gpu,
)
return trainer