com.intel.analytics.zoo.pipeline.api.keras.layers
Hidden unit size. Dimension of internal projections and final output.
Activation function to use. You can also pass in corresponding string representations such as 'relu' or 'sigmoid', etc. for simple activations in the factory method. Default is 'tanh'.
Whether to return the full sequence or only return the last output in the output sequence. Default is false.
Whether the input sequence will be processed backwards. Default is false.
An instance of Regularizer, (eg. L1 or L2 regularization), applied to the input weights matrices. Default is null.
An instance of Regularizer, applied the recurrent weights matrices. Default is null.
An instance of Regularizer, applied to the bias. Default is null.
A Single Shape, does not include the batch dimension.
Activation function to use.
Activation function to use. You can also pass in corresponding string representations such as 'relu' or 'sigmoid', etc. for simple activations in the factory method. Default is 'tanh'.
An instance of Regularizer, applied to the bias.
An instance of Regularizer, applied to the bias. Default is null.
Build graph: some other modules point to current module
Build graph: some other modules point to current module
upstream variables
Variable containing current module
Whether the input sequence will be processed backwards.
A Single Shape, does not include the batch dimension.
Hidden unit size.
Whether to return the full sequence or only return the last output in the output sequence.
An instance of Regularizer, applied the recurrent weights matrices.
An instance of Regularizer, applied the recurrent weights matrices. Default is null.
An instance of Regularizer, (eg.
An instance of Regularizer, (eg. L1 or L2 regularization), applied to the input weights matrices. Default is null.
(Since version 0.3.0) please use recommended saveModule(path, overWrite)
A fully-connected recurrent neural network cell. The output is to be fed back to input. The input of this layer should be 3D, i.e. (batch, time steps, input dim).
When you use this layer as the first layer of a model, you need to provide the argument inputShape (a Single Shape, does not include the batch dimension).
Numeric type of parameter(e.g. weight, bias). Only support float/double now.