medium_base_network.py

INPUT_SHAPE = (INPUT_SIZE, INPUT_SIZE, 3)

def initialize_base_network():

    inputs = tf.keras.layers.Input(INPUT_SHAPE)
    base_model = tf.keras.applications.mobilenet_v2.MobileNetV2(input_shape=INPUT_SHAPE, include_top=False, weights='imagenet')
    
    base_model.trainable = True
    fine_tune_at = len(base_model.layers)-int(len(base_model.layers)*.10)
    for layer in base_model.layers[:fine_tune_at]:
        layer.trainable =  False
          
    x = base_model(inputs)
    x = tf.keras.layers.GlobalAveragePooling2D()(x)
    outputs=tf.keras.layers.Dense(64)(x)
    model = tf.keras.Model(inputs, outputs)
    
    return model