trainer

Source code: tianshou/highlevel/trainer.py

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class EpochStopCallback

Callback which is called after the test phase of each epoch in order to determine whether training should stop early.

get_trainer_fn(context: TrainingContext) → Callable[[float], bool]

abstract should_stop(mean_rewards: float, context: TrainingContext) → bool

Determines whether training should stop.

Parameters:

• mean_rewards – the average undiscounted returns of the testing result

• context – the training context

Returns:

True if the goal has been reached and training should stop, False otherwise

class EpochStopCallbackRewardThreshold(threshold: float | None = None)

Stops training once the mean rewards exceed the given reward threshold or the threshold that is specified in the gymnasium environment (i.e. env.spec.reward_threshold).

should_stop(mean_rewards: float, context: TrainingContext) → bool

Determines whether training should stop.

Parameters:

• mean_rewards – the average undiscounted returns of the testing result

• context – the training context

Returns:

True if the goal has been reached and training should stop, False otherwise

class EpochTestCallback

Callback which is called at the beginning of the test phase of each epoch.

abstract callback(epoch: int, env_step: int | None, context: TrainingContext) → None

get_trainer_fn(context: TrainingContext) → Callable[[int, int | None], None]

class EpochTestCallbackDQNSetEps(eps_test: float)

Sets the epsilon value for DQN-based policies at the beginning of the test stage in each epoch.

callback(epoch: int, env_step: int | None, context: TrainingContext) → None

class EpochTrainCallback

Callback which is called at the beginning of each epoch, i.e. prior to the data collection phase of each epoch.

abstract callback(epoch: int, env_step: int, context: TrainingContext) → None

get_trainer_fn(context: TrainingContext) → Callable[[int, int], None]

class EpochTrainCallbackDQNEpsLinearDecay(eps_train: float, eps_train_final: float, decay_steps: int = 1000000)

Sets the epsilon value for DQN-based policies at the beginning of the training stage in each epoch, using a linear decay in the first decay_steps steps.

callback(epoch: int, env_step: int, context: TrainingContext) → None

class EpochTrainCallbackDQNSetEps(eps_test: float)

Sets the epsilon value for DQN-based policies at the beginning of the training stage in each epoch.

callback(epoch: int, env_step: int, context: TrainingContext) → None

class TrainerCallbacks(epoch_train_callback: EpochTrainCallback | None = None, epoch_test_callback: EpochTestCallback | None = None, epoch_stop_callback: EpochStopCallback | None = None)

Container for callbacks used during training.

epoch_stop_callback: EpochStopCallback | None = None

epoch_test_callback: EpochTestCallback | None = None

epoch_train_callback: EpochTrainCallback | None = None

class TrainingContext(policy: TPolicy, envs: Environments, logger: BaseLogger)