tf.compat.v1.keras.layers.CuDNNGRU

Fast GRU implementation backed by cuDNN.

Inherits From: RNN, Layer, Module

tf.compat.v1.keras.layers.CuDNNGRU(
    units,
    kernel_initializer='glorot_uniform',
    recurrent_initializer='orthogonal',
    bias_initializer='zeros',
    kernel_regularizer=None,
    recurrent_regularizer=None,
    bias_regularizer=None,
    activity_regularizer=None,
    kernel_constraint=None,
    recurrent_constraint=None,
    bias_constraint=None,
    return_sequences=False,
    return_state=False,
    go_backwards=False,
    stateful=False,
    **kwargs
)

More information about cuDNN can be found on the NVIDIA developer website. Can only be run on GPU.

units Positive integer, dimensionality of the output space. kernel_initializer Initializer for the kernel weights matrix, used for the linear transformation of the inputs. recurrent_initializer Initializer for the recurrent_kernel weights matrix, used for the linear transformation of the recurrent state. bias_initializer Initializer for the bias vector. kernel_regularizer Regularizer function applied to the kernel weights matrix. recurrent_regularizer Regularizer function applied to the recurrent_kernel weights matrix. bias_regularizer Regularizer function applied to the bias vector. activity_regularizer Regularizer function applied to the output of the layer (its "activation"). kernel_constraint Constraint function applied to the kernel weights matrix. recurrent_constraint Constraint function applied to the recurrent_kernel weights matrix. bias_constraint Constraint function applied to the bias vector. return_sequences Boolean. Whether to return the last output in the output sequence, or the full sequence. return_state Boolean. Whether to return the last state in addition to the output. go_backwards Boolean (default False). If True, process the input sequence backwards and return the reversed sequence. stateful Boolean (default False). If True, the last state for each sample at index i in a batch will be used as initial state for the sample of index i in the following batch.

cell

states

Methods

get_losses_for

View source

get_losses_for(
    inputs=None
)

reset_states

View source

reset_states(
    states=None
)

Reset the recorded states for the stateful RNN layer.

Can only be used when RNN layer is constructed with stateful = True. Args: states: Numpy arrays that contains the value for the initial state, which will be feed to cell at the first time step. When the value is None, zero filled numpy array will be created based on the cell state size.

Raises

AttributeError When the RNN layer is not stateful. ValueError When the batch size of the RNN layer is unknown. ValueError When the input numpy array is not compatible with the RNN layer state, either size wise or dtype wise.