callbacks.py

# Copyright 2019 AirBrain.org
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import keras
from keras import models
from keras.callbacks import LambdaCallback

def do_test_data_checkpoint(model, test_features, test_labels):
    mse, mae = model.evaluate(test_features, test_labels)
    print("Test data accuracy: #", mae)

def create_test_data_checkpoint(model, test_features, test_labels):
    test_data_checkpoint = LambdaCallback(
        on_epoch_end=lambda epoch, logs: do_test_data_checkpoint(model, test_features, test_labels))

    return test_data_checkpoint

def create_early_stopping(patience):
    return keras.callbacks.EarlyStopping(
        monitor='acc',
        patience=patience
    )

def create_model_checkpoint(filepath):
    return keras.callbacks.ModelCheckpoint(
        filepath=filepath,
        monitor='val_loss',
        save_best_only=True
    )

def create_reduce_lr(factor, patience):
    return keras.callbacks.ReduceLROnPlateau(
        monitor="val_loss",
        factor=factor,
        patience=patience
    )

def create_tensorboard(log_dir):
    return keras.callbacks.TensorBoard(
        log_dir=log_dir,
        histogram_freq=1,
        write_images=True
    )