def finetuning_callbacks(checkpoint_path, patience, verbose):
""" Callbacks for model training.
# Arguments:
checkpoint_path: Where weight checkpoints should be saved.
patience: Number of epochs with no improvement after which
training will be stopped.
# Returns:
Array with training callbacks that can be passed straight into
model.fit() or similar.
"""
cb_verbose = (verbose >= 2)
checkpointer = ModelCheckpoint(monitor='val_loss', filepath=checkpoint_path,
save_best_only=True, verbose=cb_verbose)
earlystop = EarlyStopping(monitor='val_loss', patience=patience,
verbose=cb_verbose)
return [checkpointer, earlystop]
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