Table of Contents  ▸  List of Commands  ▸  Neural Networks  ▸  nn_conv2dnnl

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nn_conv2dnnl

Arguments:

• out,in,nb_channels>0,_kernel_size>0,_stride>0,_dilation,_shrink>=0,_boundary_conditions,_activation,_learning_mode,_regularization>=0,_initialization

Description:

Add a conv2dnnl (2D convolutional layer followed by a normalization layer, then a non-linearity) to the current network.

boundary_conditions can be { 0:Dirichlet | 1:Neumann | 2:Periodic | 3:Mirror }.
learning_mode can be { 0:No learning | 1:Weights only | 2:Biases only | 3:Weights+biases }.
initialization can be { 0:Zero | 1:Identity | 2:Lecun-initialization | 3:He-initialization }.

Default values:

kernel_size=3, stride=1, dilation=1, shrink=0, boundary_conditions=1, activation=leakyrelu, learning_mode=3, regularization=0 and initialization=2.