create_model.py

def create_model():
    input_layer = tf.keras.layers.Input(shape=(224, 224, 3))
    base_model = tf.keras.applications.MobileNetV2(input_tensor=input_layer,
                                                   weights='imagenet',
                                                   include_top=False)
    base_model.trainable = False
    x = tf.keras.layers.GlobalAveragePooling2D()(base_model.output)
    x = tf.keras.layers.Dense(2, activation='softmax')(x)
    
    model = tf.keras.models.Model(inputs=input_layer, outputs=x)
    model.compile(optimizer='adam',
                  loss='sparse_categorical_crossentropy',
                  metrics=['acc'])
    return model