tf_agents.agents.data_converter.AsTrajectory

Class that validates and converts other data types to Trajectory.

tf_agents.agents.data_converter.AsTrajectory(
    data_context: tf_agents.agents.data_converter.DataContext,
    sequence_length: typing.Optional[int] = None,
    num_outer_dims: te.Literal[1, 2] = 2
)

Note that validation and conversion allows values to contain dictionaries with extra keys as compared to the the specs in the data context. These additional entries / observations are ignored and dropped during conversion.

This non-strict checking allows users to provide additional info and observation keys at input without having to manually prune them before converting.

Args
data_context	An instance of DataContext, typically accessed from the TFAgent.data_context property.
sequence_length	The required time dimension value (if any), typically determined by the subclass of TFAgent.
num_outer_dims	Expected number of outer dimensions. Either 1 or 2. If 1, call expects an outer batch dimension. If 2, then call expects the two outer dimensions [batch, time].

Methods

__call__

View source

__call__(
    value: typing.Any
) -> tf_agents.trajectories.Trajectory

Convers value to a Trajectory. Performs data validation and pruning.

• If value is already a Trajectory, only validation is performed.
• If value is a Transition with tensors containing two ([B, T]) outer dims, then it is simply repackaged to a Trajectory and then validated.
• If value is a Transition with tensors containing one ([B]) outer dim, a ValueError is raised.

Args
value	A Trajectory or Transition object to convert.

Returns
A validated and pruned Trajectory.

Raises
TypeError	If value is not one of Trajectory or Transition.
ValueError	If value has structure that doesn't match the converter's spec.
TypeError	If value has a structure that doesn't match the converter's spec.
ValueError	If value is a Transition without a time dimension, as training Trajectories typically have batch and time dimensions.