tf_agents.trajectories.truncation
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Returns a TimeStep with step_type set to StepType.LAST.
tf_agents.trajectories.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.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. If not, the batch dimensions will be inferred by reward's
shape.
|
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Last updated 2024-04-26 UTC.
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View source on GitHub