KerasCallback: Base R6 class for Keras callbacks
In dfalbel/keras: R Interface to 'Keras'

Description Format Details Value Fields Methods Examples

Base R6 class for Keras callbacks

An R6Class generator object

The logs named list that callback methods take as argument will contain keys for quantities relevant to the current batch or epoch.

Currently, the fit.keras.engine.training.Model() method for sequential models will include the following quantities in the logs that it passes to its callbacks:

on_epoch_end: logs include acc and loss, and optionally include val_loss (if validation is enabled in fit), and val_acc (if validation and accuracy monitoring are enabled).
on_batch_begin: logs include size, the number of samples in the current batch.
on_batch_end: logs include loss, and optionally acc (if accuracy monitoring is enabled).

KerasCallback.

params: Named list with training parameters (eg. verbosity, batch size, number of epochs...).
model: Reference to the Keras model being trained.

on_epoch_begin(epoch, logs): Called at the beginning of each epoch.
on_epoch_end(epoch, logs): Called at the end of each epoch.
on_batch_begin(batch, logs): Called at the beginning of each batch.
on_batch_end(batch, logs): Called at the end of each batch.
on_train_begin(logs): Called at the beginning of training.
on_train_end(logs): Called at the end of training.

## Not run: 
library(keras)

LossHistory <- R6::R6Class("LossHistory",
  inherit = KerasCallback,
  
  public = list(
  
    losses = NULL,

    on_batch_end = function(batch, logs = list()) {
      self$losses <- c(self$losses, logs[["loss"]])
    }
  )
)

## End(Not run)