The size of the bias.
An instance of Regularizer, (eg. L1 or L2 regularization), applied to the input weights matrices. Default is null.
A Single Shape, does not include the batch dimension.
Build graph: some other modules point to current module
Build graph: some other modules point to current module
upstream variables
Variable containing current module
A Single Shape, does not include the batch dimension.
The size of the bias.
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)
This layer has a weight with given size. The weight will be multiplied element-wise to the input. If the element number of the weight matches the input, a simple element-wise multiplication will be done. Or the bias will be expanded to the same size of the input. The expand means repeat on unmatched singleton dimension (if some unmatched dimension isn't singleton dimension, an error will be raised).
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).
Remark: This layer is from Torch and wrapped in Keras style.
The numeric type of parameter(e.g. weight, bias). Only support float/double now.