How to use the deepface.deepface.create_deepface function in deepface

"""
reduce_lr = keras.callbacks.ReduceLROnPlateau(monitor='val_loss', factor=0.1,
    patience=1, min_lr=0.0001, verbose=1) # mandatory step in training, as specified in paper
tensorboard = keras.callbacks.TensorBoard(TB_PATH)
checkpoints = keras.callbacks.ModelCheckpoint('weights.{epoch:02d}_{val_acc:.4f}.hdf5',
    monitor='val_acc', save_weights_only=True)

cbs = [reduce_lr, checkpoints, tensorboard]

"""
Construct the DeepFace
network with TPU strategy
"""
from deepface import deepface
with strategy.scope():
    model = deepface.create_deepface(IMAGE_SIZE, CHANNELS, NUM_CLASSES, LEARN_RATE, MOMENTUM)

"""
Train the model
"""
train_history = model.fit(train.data, steps_per_epoch=train_samples // BATCH_SIZE + 1,
    validation_data=val.data, validation_steps=val_samples // BATCH_SIZE + 1,
    callbacks=cbs, epochs=EPOCHS)
model.save('model.h5')

"""
Let's visualise how the
training went
"""
from matplotlib import pyplot as plt
def save_plots():
    """