Fast LSTM implementation backed by cuDNN.
tf.keras.layers.CuDNNLSTM(
units, kernel_initializer='glorot_uniform', recurrent_initializer='orthogonal',
bias_initializer='zeros', unit_forget_bias=True, 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.
Arguments |
units
|
Positive integer, dimensionality of the output space.
|
kernel_initializer
|
Initializer for the kernel weights matrix, used for
the linear transformation of the inputs.
|
unit_forget_bias
|
Boolean. If True, add 1 to the bias of the forget gate
at initialization. Setting it to true will also force
bias_initializer="zeros" . This is recommended in Jozefowicz et
al.
|
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.
|
Methods
get_initial_state
View source
get_initial_state(
inputs
)
reset_states
View source
reset_states(
states=None
)