A nest of tensor_spec.TensorSpec representing the
input observations.
preprocessing_layers
(Optional.) A nest of tf.keras.layers.Layer
representing preprocessing for the different observations. All of these
layers must not be already built. For more details see the documentation
of networks.EncodingNetwork.
preprocessing_combiner
(Optional.) A keras layer that takes a flat list
of tensors and combines them. Good options include
tf.keras.layers.Add and tf.keras.layers.Concatenate(axis=-1). This
layer must not be already built. For more details see the documentation
of networks.EncodingNetwork.
conv_layer_params
Optional list of convolution layers parameters, where
each item is a length-three tuple indicating (filters, kernel_size,
stride).
input_fc_layer_params
Optional list of fully_connected parameters, where
each item is the number of units in the layer. This is applied before
the LSTM cell.
input_dropout_layer_params
Optional list of dropout layer parameters,
where each item is the fraction of input units to drop. The dropout
layers are interleaved with the fully connected layers; there is a
dropout layer after each fully connected layer, except if the entry in
the list is None. This list must have the same length of
input_fc_layer_params, or be None.
lstm_size
An iterable of ints specifying the LSTM cell sizes to use.
output_fc_layer_params
Optional list of fully_connected parameters, where
each item is the number of units in the layer. This is applied after the
LSTM cell.
activation_fn
Activation function, e.g. tf.keras.activations.relu,.
dtype
The dtype to use by the convolution, LSTM, and fully connected
layers.
name
A string representing name of the network.
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.