tf_agents.trajectories.truncation
Stay organized with collections
Save and categorize content based on your preferences.
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.
|
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[]]