minimum example callbacks

min_callbacks_example.py

import tensorflow as tf

(x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data()
x_train = (x_train.reshape(60000, 784).astype('float32') / 255)
x_test = (x_test.reshape(10000, 784).astype('float32') / 255)


def initialize_model():
    model = tf.keras.Sequential()
    model.add(tf.keras.layers.Dense(300))
    model.add(tf.keras.layers.Dense(10, activation='softmax'))
    model.compile(optimizer=tf.keras.optimizers.Adam(),
                  loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True) ,
                  metrics=['accuracy'],
                  experimental_run_tf_function=False
                 )
    return model

def train_model(model):
    reduce_lr = tf.keras.callbacks.ReduceLROnPlateau(
        patience=3,
        monitor='val_loss'
    )

    early_stopping = tf.keras.callbacks.EarlyStopping(
      patience=4,
      monitor='val_loss'
      )
      
    callbacks=[early_stopping, reduce_lr]
    model.fit(x=x_train,
              y=y_train,
              batch_size=64,
              epochs=500,
              callbacks=[callbacks],
              validation_data=(x_test, y_test),
             )
    
model = initialize_model()
train_model(model)