conv_bn(kernelsize, inplanes, outplanes, activation = relu;
             rev = false, preact = false, use_bn = true, stride = 1, pad = 0, dilation = 1,
             groups = 1, [bias, weight, init], initβ = Flux.zeros32, initγ = Flux.ones32,
             ϵ = 1.0f-5, momentum = 1.0f-1)

Create a convolution + batch normalization pair with activation.

Arguments

• kernelsize: size of the convolution kernel (tuple)
• inplanes: number of input feature maps
• outplanes: number of output feature maps
• activation: the activation function for the final layer
• rev: set to true to place the batch norm before the convolution
• preact: set to true to place the activation function before the batch norm (only compatible with rev = false)
• use_bn: set to false to disable batch normalization (only compatible with rev = false and preact = false)
• stride: stride of the convolution kernel
• pad: padding of the convolution kernel
• dilation: dilation of the convolution kernel
• groups: groups for the convolution kernel
• bias, weight, init: initialization for the convolution kernel (see Flux.Conv)
• initβ, initγ: initialization for the batch norm (see Flux.BatchNorm)
• ϵ, momentum: batch norm parameters (see Flux.BatchNorm)