Int > 0. Size of the vocabulary.
Int >= 0. Dimension of the dense embedding.
Initialization method for the weights of the layer. Default is RandomUniform. You can also pass in corresponding string representations such as 'uniform' or 'normal', etc. for simple init methods in the factory method.
An instance of Regularizer, (eg. L1 or L2 regularization), applied to the embedding matrix. 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
Initialization method for the weights of the layer.
Initialization method for the weights of the layer. Default is RandomUniform. You can also pass in corresponding string representations such as 'uniform' or 'normal', etc. for simple init methods in the factory method.
Int > 0.
Int > 0. Size of the vocabulary.
Int >= 0.
Int >= 0. Dimension of the dense embedding.
(Since version 0.3.0) please use recommended saveModule(path, overWrite)
Turn positive integers (indexes) into dense vectors of fixed size. The input of this layer should be 2D.
This layer can only be used as the first layer in 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.