GANLearner_from_learners: GAN Learner from learners

In fastai: Interface to 'fastai'

GAN Learner from learners

Description

Create a GAN from 'learn_gen' and 'learn_crit'.

Usage

GANLearner_from_learners(
  gen_learn,
  crit_learn,
  switcher = NULL,
  weights_gen = NULL,
  gen_first = FALSE,
  switch_eval = TRUE,
  show_img = TRUE,
  clip = NULL,
  cbs = NULL,
  metrics = NULL,
  loss_func = 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

gen_learn	generator learner
crit_learn	discriminator learner
switcher	switcher
weights_gen	weights generator
gen_first	generator first
switch_eval	switch evaluation
show_img	show image or not
clip	clip value
cbs	Cbs is one or a list of Callbacks to pass to the Learner.
metrics	It is an optional list of metrics, that can be either functions or Metrics.
loss_func	loss function
opt_func	The function used to create the optimizer
lr	learning rate
splitter	It is a function that takes self.model and returns a list of parameter groups (or just one parameter group if there are no different parameter groups).
path	The folder where to work
model_dir	Path and model_dir are used to save and/or load models.
wd	It is the default weight decay used when training the model.
wd_bn_bias	It controls if weight decay is applied to BatchNorm layers and bias.
train_bn	It controls if BatchNorm layers are trained even when they are supposed to be frozen according to the splitter.
moms	The default momentums used in Learner$fit_one_cycle.

Value

None

fastai documentation built on March 31, 2023, 11:41 p.m.