tf.keras.layers.StackedRNNCells

Wrapper allowing a stack of RNN cells to behave as a single cell.

Inherits From: Layer, Operation

tf.keras.layers.StackedRNNCells(
    cells, **kwargs
)

Used to implement efficient stacked RNNs.

cells List of RNN cell instances.

Example:

batch_size = 3
sentence_length = 5
num_features = 2
new_shape = (batch_size, sentence_length, num_features)
x = np.reshape(np.arange(30), new_shape)

rnn_cells = [keras.layers.LSTMCell(128) for _ in range(2)]
stacked_lstm = keras.layers.StackedRNNCells(rnn_cells)
lstm_layer = keras.layers.RNN(stacked_lstm)

result = lstm_layer(x)

input Retrieves the input tensor(s) of a symbolic operation.

Only returns the tensor(s) corresponding to the first time the operation was called.

output Retrieves the output tensor(s) of a layer.

Only returns the tensor(s) corresponding to the first time the operation was called.

output_size

state_size

Methods

from_config

View source

@classmethod
from_config(
    config, custom_objects=None
)

Creates an operation from its config.

This method is the reverse of get_config, capable of instantiating the same operation from the config dictionary.

if "dtype" in config and isinstance(config["dtype"], dict):
    policy = dtype_policies.deserialize(config["dtype"])

Args
config A Python dictionary, typically the output of get_config.

Returns
An operation instance.

get_initial_state

View source

get_initial_state(
    batch_size=None
)