UnetBlock: UnetBlock
In fastai: Interface to 'fastai'

UnetBlock

R Documentation

UnetBlock

Description

A quasi-UNet block, using 'PixelShuffle_ICNR upsampling'.

Usage

UnetBlock(
  up_in_c,
  x_in_c,
  hook,
  final_div = TRUE,
  blur = FALSE,
  act_cls = nn()$ReLU,
  self_attention = FALSE,
  init = nn()$init$kaiming_normal_,
  norm_type = NULL,
  ks = 3,
  stride = 1,
  padding = NULL,
  bias = NULL,
  ndim = 2,
  bn_1st = TRUE,
  transpose = FALSE,
  xtra = NULL,
  bias_std = 0.01,
  dilation = 1,
  groups = 1,
  padding_mode = "zeros"
)

Arguments

`up_in_c`	up_in_c parameter
`x_in_c`	x_in_c parameter
`hook`	The hook is set to this intermediate layer to store the output needed for this block.
`final_div`	final div
`blur`	blur is used to avoid checkerboard artifacts at each layer.
`act_cls`	activation
`self_attention`	self_attention determines if we use a self-attention layer
`init`	initializer
`norm_type`	normalization type
`ks`	kernel size
`stride`	stride
`padding`	padding mode
`bias`	bias
`ndim`	number of dimensions
`bn_1st`	batch normalization 1st
`transpose`	transpose
`xtra`	xtra
`bias_std`	bias standard deviation
`dilation`	dilation
`groups`	groups
`padding_mode`	The mode of padding