layer_partial_conv_2d: Partial convolution layer 2D
In ANTsX/ANTsRNet: Neural Networks for Medical Image Processing

View source: R/customConvolutionLayers.R

layer_partial_conv_2d

R Documentation

Partial convolution layer 2D

Description

Creates an 2D partial convolution layer

Usage

layer_partial_conv_2d(
  object,
  filters,
  kernelSize,
  strides = c(1L, 1L),
  padding = "valid",
  dataFormat = "channels_last",
  dilationRate = c(1L, 1L),
  activation = NULL,
  kernelInitializer = "glorot_uniform",
  biasInitializer = "zeros",
  kernelRegularizer = NULL,
  biasRegularizer = NULL,
  activityRegularizer = NULL,
  useBias = TRUE,
  trainable = TRUE
)

Arguments

`object`	Object to compose layer with. This is either a keras::keras_model_sequential to add the layer to, or another Layer which this layer will call.
`filters`	number of filters
`kernelSize`	kernel size
`strides`	strides
`padding`	padding
`dataFormat`	format
`dilationRate`	dilate rate
`activation`	activation
`kernelInitializer`	kernel initializer
`biasInitializer`	bias initializer
`kernelRegularizer`	kernel regularizer
`biasRegularizer`	bias regularizer
`activityRegularizer`	activity regularizer
`useBias`	use bias
`trainable`	Whether the layer weights will be updated during training.