GANLearner_from_learners: GAN Learner from learners
In fastai: Interface to 'fastai'

GANLearner_from_learners

R Documentation

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.