Number of convolution filters to use.
Number of rows in the convolution kernel.
Number of columns in the convolution kernel.
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.
Either 'valid' or 'same'. Default is 'valid'.
Int array of length 2 corresponding to the step of the convolution in the height and width dimension. Also called strides elsewhere. Default is (1, 1).
Format of input data. Either DataFormat.NCHW (dimOrdering='th') or DataFormat.NHWC (dimOrdering='tf'). Default is NCHW.
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.
Whether to include a bias (i.e. make the layer affine rather than linear). Default is true.
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.
Whether to include a bias (i.
Whether to include a bias (i.e. make the layer affine rather than linear). Default is true.
Either 'valid' or 'same'.
Either 'valid' or 'same'. Default is 'valid'.
Format of input data.
Format of input data. Either DataFormat.NCHW (dimOrdering='th') or DataFormat.NHWC (dimOrdering='tf'). Default is NCHW.
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 columns in the convolution kernel.
Number of columns in the convolution kernel.
Number of convolution filters to use.
Number of convolution filters to use.
Number of rows in the convolution kernel.
Number of rows in the convolution kernel.
Int array of length 2 corresponding to the step of the convolution in the height and width dimension.
Int array of length 2 corresponding to the step of the convolution in the height and width dimension. Also called strides elsewhere. Default is (1, 1).
(Since version 0.3.0) please use recommended saveModule(path, overWrite)
Applies a 2D convolution over an input image composed of several input planes. You can also use Conv2D as an alias of this layer. The input of this layer should be 4D.
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), e.g. inputShape=Shape(3, 128, 128) for 128x128 RGB pictures.
Numeric type of parameter(e.g. weight, bias). Only support float/double now.