GANLearner_from_learners {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