Number of convolution filters to use.
Length of the first dimension in the convolution kernel.
Length of the second dimension in the convolution kernel.
Length of the third dimension 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 3. Factor by which to subsample output. Also called strides elsewhere. Default is (1, 1, 1).
Format of the input data. Please use "CHANNEL_FIRST" (dimOrdering='th').
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 the input data.
Format of the input data. Please use "CHANNEL_FIRST" (dimOrdering='th').
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.
Length of the first dimension in the convolution kernel.
Length of the first dimension in the convolution kernel.
Length of the second dimension in the convolution kernel.
Length of the second dimension in the convolution kernel.
Length of the third dimension in the convolution kernel.
Length of the third dimension in the convolution kernel.
Number of convolution filters to use.
Number of convolution filters to use.
Int array of length 3.
Int array of length 3. Factor by which to subsample output. Also called strides elsewhere. Default is (1, 1, 1).
(Since version 0.3.0) please use recommended saveModule(path, overWrite)
Applies convolution operator for filtering windows of three-dimensional inputs. You can also use Conv3D as an alias of this layer. Data format currently supported for this layer is 'CHANNEL_FIRST' (dimOrdering='th'). The input of this layer should be 5D.
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, 10, 128, 128) 10 frames of 128x128 RGB pictures.
Numeric type of parameter(e.g. weight, bias). Only support float/double now.