com.intel.analytics.zoo.pipeline.api.keras.layers
Number of convolution filters to use.
Length of the first, second and third dimensions in the convolution kernel. Cubic kernel.
Factor by which to subsample output. Also called strides elsewhere. Default is 1.
One of "same" or "valid". Also called padding elsewhere. Default is "valid".
An instance of Regularizer, (eg. L1 or L2 regularization), applied to the input weights matrices. Default is null.
An instance of Regularizer, (eg. L1 or L2 regularization), applied to the recurrent weights matrices. Default is null.
An instance of Regularizer, applied to the bias. Default is null.
Whether to return the full sequence or the last output in the output sequence. Default is false.
Whether the input sequence will be processed backwards. Default is false.
A Single Shape, does not include the batch dimension.
An instance of Regularizer, applied to the bias.
An instance of Regularizer, applied to the bias. Default is null.
One of "same" or "valid".
One of "same" or "valid". Also called padding elsewhere. Default is "valid".
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.
Whether the input sequence will be processed backwards. Default is false.
A Single Shape, does not include the batch dimension.
Number of convolution filters to use.
Length of the first, second and third dimensions in the convolution kernel.
Length of the first, second and third dimensions in the convolution kernel. Cubic kernel.
Whether to return the full sequence or the last output in the output sequence.
Whether to return the full sequence or the last output in the output sequence. Default is false.
Factor by which to subsample output.
Factor by which to subsample output. Also called strides elsewhere. Default is 1.
An instance of Regularizer, (eg.
An instance of Regularizer, (eg. L1 or L2 regularization), applied to 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)
Convolutional LSTM for 3D input. Note that currently only 'same' padding is supported. The convolution kernel for this layer is a cubic kernel with equal strides for all dimensions. The input of this layer should be 6D, i.e. (samples, time, channels, dim1, dim2, dim3), and 'CHANNEL_FIRST' (dimOrdering='th') is expected.
When using this layer as the first layer in a model, you need to provide the argument inputShape (a Single Shape, does not include the batch dimension).
The numeric type of parameter(e.g. weight, bias). Only support float/double now.