GANLearner_wgan: Wgan

In fastai: Interface to 'fastai'

Wgan

Description

Create a WGAN from 'data', 'generator' and 'critic'.

Usage

GANLearner_wgan(
  dls,
  generator,
  critic,
  switcher = NULL,
  clip = 0.01,
  switch_eval = FALSE,
  gen_first = FALSE,
  show_img = TRUE,
  cbs = NULL,
  metrics = NULL,
  opt_func = Adam(),
  lr = 0.001,
  splitter = trainable_params,
  path = NULL,
  model_dir = "models",
  wd = NULL,
  wd_bn_bias = FALSE,
  train_bn = TRUE,
  moms = list(0.95, 0.85, 0.95)
)

Arguments

dls	dataloader
generator	generator
critic	critic
switcher	switcher
clip	clip value
switch_eval	switch evaluation
gen_first	generator first
show_img	show image or not
cbs	callbacks
metrics	metrics
opt_func	optimization function
lr	learning rate
splitter	splitter
path	path
model_dir	model directory
wd	weight decay
wd_bn_bias	weight decay bn bias
train_bn	It controls if BatchNorm layers are trained even when they are supposed to be frozen according to the splitter.
moms	momentums

Value

None

Examples

## Not run: 

learn = GANLearner_wgan(dls, generator, critic, opt_func = partial(Adam(), mom=0.))


## End(Not run)

fastai documentation built on June 22, 2024, 11:15 a.m.