tf.keras.layers.CuDNNLSTM
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 | |
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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. |
Attributes | |
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cell | |
states |
Methods
get_initial_state
get_initial_state( inputs )
reset_states
reset_states( states=None )
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/keras/layers/CuDNNLSTM