View source on GitHub
|
Tensorflow RL Agent RNN utilities.
This module provides helper functions that Agents can use to train RNN-based policies.
DynamicUnroll
The layer DynamicUnroll allows an Agent to train an RNN-based policy
by running an RNN over a batch of episode chunks from a replay buffer.
The agent creates a subclass of tf.contrib.rnn.LayerRNNCell or a Keras RNN
cell, such as tf.keras.layers.LSTMCell, instances of which
which can themselves be wrappers of RNNCell. Training this instance
involes passing it to DynamicUnroll constructor; and then pass a set of
episode tensors in the form of inputs.
See the unit tests in rnn_utils_test.py for more details.
Classes
class DynamicUnroll: Process a history of sequences that are concatenated without padding.