Create a custom callback

This callback is constructed with anonymous functions that will be called at the appropriate time. Note that the callbacks expects positional arguments, as:

  • on_epoch_begin and on_epoch_end expect two positional arguments: epoch, logs

  • on_batch_begin and on_batch_end expect two positional arguments: batch, logs

  • on_train_begin and on_train_end expect one positional argument: logs

callback_lambda(on_epoch_begin = NULL, on_epoch_end = NULL,
  on_batch_begin = NULL, on_batch_end = NULL, on_train_begin = NULL,
  on_train_end = NULL)

Arguments

on_epoch_begin

called at the beginning of every epoch.
on_epoch_end

called at the end of every epoch.
on_batch_begin

called at the beginning of every batch.
on_batch_end

called at the end of every batch.
on_train_begin

called at the beginning of model training.
on_train_end

called at the end of model training.

See also

Other callbacks: callback_csv_logger, callback_early_stopping, callback_learning_rate_scheduler, callback_model_checkpoint, callback_progbar_logger, callback_reduce_lr_on_plateau, callback_remote_monitor, callback_tensorboard, callback_terminate_on_naan