UnetBlock {fastai}

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

Value

None