com.intel.analytics.zoo.pipeline.api.keras.layers
Number of convolution kernels to use.
The extension (spatial or temporal) of each filter.
Initialization method for the weights of the layer. Default is Xavier. You can also pass in corresponding string representations such as 'glorot_uniform' or 'normal', etc. for simple init methods in the factory method.
Activation function to use. Default is null. You can also pass in corresponding string representations such as 'relu' or 'sigmoid', etc. for simple activations in the factory method.
Factor by which to subsample output. Integer. Default is 1.
Factor for kernel dilation. Also called filter_dilation elsewhere. Integer. Default is 1.
An instance of Regularizer, (eg. L1 or L2 regularization), applied to the input 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. Default is null. You can also pass in corresponding string representations such as 'relu' or 'sigmoid', etc. for simple activations in the factory method.
Factor for kernel dilation.
Factor for kernel dilation. Also called filter_dilation elsewhere. Integer. Default is 1.
An instance of Regularizer, applied to the bias.
An instance of Regularizer, applied to the bias. Default is null.
The extension (spatial or temporal) of each filter.
The extension (spatial or temporal) of each filter.
Build graph: some other modules point to current module
Build graph: some other modules point to current module
upstream variables
Variable containing current module
Initialization method for the weights of the layer.
Initialization method for the weights of the layer. Default is Xavier. You can also pass in corresponding string representations such as 'glorot_uniform' or 'normal', etc. for simple init methods in the factory method.
A Single Shape, does not include the batch dimension.
A Single Shape, does not include the batch dimension.
Number of convolution kernels to use.
Number of convolution kernels to use.
Factor by which to subsample output.
Factor by which to subsample output. Integer. Default is 1.
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)
Applies an atrous convolution operator for filtering neighborhoods of 1-D inputs. A.k.a dilated convolution or convolution with holes. Bias will be included in this layer. Border mode currently supported for this layer is 'valid'. You can also use AtrousConv1D as an alias of this layer. The input of this layer should be 3D.
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.