It is a TF-Agents network that can be used to process nested inputs.
Stateful Keras layers (e.g. LSTMCell, RNN, LSTM, TF-Agents DynamicUnroll)
are all supported. The state_spec of NestMap has a structure matching
that of nested_layers.
A nest of layers and/or networks. These will be used to
process the inputs (input nest structure will have to match this
structure). Any layers that are subclasses of
tf.keras.layers.{RNN,LSTM,GRU,...} are wrapped in
tf_agents.keras_layers.RNNWrapper.
input_spec
(Optional.) A nest of tf.TypeSpec representing the input
observations. The structure of input_spec must match that of
nested_layers.
name
(Optional.) Network name.
Raises
TypeError
If any of the layers are not instances of keras Layer.
ValueError
If input_spec is provided but its nest structure does
not match that of nested_layers.
RuntimeError
If not tf.executing_eagerly(); as this is required to
be able to create deep copies of layers in layers.
Attributes
input_tensor_spec
Returns the spec of the input to the network of type InputSpec.
layers
Get the list of all (nested) sub-layers used in this Network.
(Optional). Override or provide an input tensor spec
when creating variables.
**kwargs
Other arguments to network.call(), e.g. training=True.
Returns
Output specs - a nested spec calculated from the outputs (excluding any
batch dimensions). If any of the output elements is a tfp Distribution,
the associated spec entry returned is a DistributionSpec.
Raises
ValueError
If no input_tensor_spec is provided, and the network did
not provide one during construction.
Total length of printed lines (e.g. set this to adapt the
display to different terminal window sizes).
positions
Relative or absolute positions of log elements in each line.
If not provided, defaults to [.33, .55, .67, 1.].
print_fn
Print function to use. Defaults to print. It will be called
on each line of the summary. You can set it to a custom function in
order to capture the string summary.