How to Compute Virtual Epochs in Tensorflow

snippet.py

NUM_TRAINING_EXAMPLES = 1000 * 1000
STOP_POINT = 14.3
TOTAL_TRAINING_EXAMPLES = int(STOP_POINT * NUM_TRAINING_EXAMPLES)
BATCH_SIZE = 100
NUM_CHECKPOINTS = 15
steps_per_epoch = (TOTAL_TRAINING_EXAMPLES // 
                   (BATCH_SIZE*NUM_CHECKPOINTS))
cp_callback = tf.keras.callbacks.ModelCheckpoint(...)
history = model.fit(trainds, 
                    validation_data=evalds,
                    epochs=NUM_CHECKPOINTS,
                    steps_per_epoch=steps_per_epoch, 
                    batch_size=BATCH_SIZE,
                    callbacks=[cp_callback])