Returns a TimeStep
with step_type
set to StepType.LAST
.
tf_agents.trajectories.time_step.truncation(
observation: tf_agents.typing.types.NestedTensorOrArray
,
reward: tf_agents.typing.types.NestedTensorOrArray
,
discount: tf_agents.typing.types.Float
= 1.0,
outer_dims: Optional[types.Shape] = None
) -> tf_agents.trajectories.time_step.TimeStep
If discount
is a scalar, and observation
contains Tensors,
then discount
will be broadcasted to match the outer dimensions.
Args |
observation
|
A NumPy array, tensor, or a nested dict, list or tuple of
arrays or tensors.
|
reward
|
A NumPy array, tensor, or a nested dict, list or tuple of
arrays or tensors.
|
discount
|
(optional) A scalar, or 1D NumPy array, or tensor.
|
outer_dims
|
(optional) If provided, it will be used to determine the
batch dimensions.
|