这似乎是 Tensorflow 2.7 使用时的一个错误model.save
与参数结合save_format="tf"
,这是默认设置的。各层RandomFlip
, RandomRotation
, RandomZoom
, and RandomContrast
导致问题的原因是它们不可序列化。有趣的是,Rescaling
可以毫无问题地保存图层。解决方法是简单地使用较旧的 Keras H5 格式保存模型model.save("test", save_format='h5')
:
import tensorflow as tf
import numpy as np
class RandomColorDistortion(tf.keras.layers.Layer):
def __init__(self, contrast_range=[0.5, 1.5],
brightness_delta=[-0.2, 0.2], **kwargs):
super(RandomColorDistortion, self).__init__(**kwargs)
self.contrast_range = contrast_range
self.brightness_delta = brightness_delta
def call(self, images, training=None):
if not training:
return images
contrast = np.random.uniform(
self.contrast_range[0], self.contrast_range[1])
brightness = np.random.uniform(
self.brightness_delta[0], self.brightness_delta[1])
images = tf.image.adjust_contrast(images, contrast)
images = tf.image.adjust_brightness(images, brightness)
images = tf.clip_by_value(images, 0, 1)
return images
def get_config(self):
config = super(RandomColorDistortion, self).get_config()
config.update({"contrast_range": self.contrast_range, "brightness_delta": self.brightness_delta})
return config
input_shape_rgb = (256, 256, 3)
data_augmentation_rgb = tf.keras.Sequential(
[
tf.keras.layers.RandomFlip("horizontal"),
tf.keras.layers.RandomFlip("vertical"),
tf.keras.layers.RandomRotation(0.5),
tf.keras.layers.RandomZoom(0.5),
tf.keras.layers.RandomContrast(0.5),
RandomColorDistortion(name='random_contrast_brightness/none'),
]
)
input_shape = (256, 256, 3)
padding = 'same'
kernel_size = 3
model = tf.keras.Sequential([
tf.keras.layers.Input(input_shape),
data_augmentation_rgb,
tf.keras.layers.Rescaling((1./255)),
tf.keras.layers.Conv2D(16, kernel_size, padding=padding, activation='relu', strides=1,
data_format='channels_last'),
tf.keras.layers.MaxPooling2D(),
tf.keras.layers.BatchNormalization(),
tf.keras.layers.Conv2D(32, kernel_size, padding=padding, activation='relu'), # best 4
tf.keras.layers.MaxPooling2D(),
tf.keras.layers.BatchNormalization(),
tf.keras.layers.Conv2D(64, kernel_size, padding=padding, activation='relu'), # best 3
tf.keras.layers.MaxPooling2D(),
tf.keras.layers.BatchNormalization(),
tf.keras.layers.Conv2D(128, kernel_size, padding=padding, activation='relu'), # best 3
tf.keras.layers.MaxPooling2D(),
tf.keras.layers.BatchNormalization(),
tf.keras.layers.Flatten(),
tf.keras.layers.Dense(128, activation='relu'), # best 1
tf.keras.layers.Dropout(0.1),
tf.keras.layers.Dense(128, activation='relu'), # best 1
tf.keras.layers.Dropout(0.1),
tf.keras.layers.Dense(64, activation='relu'), # best 1
tf.keras.layers.Dropout(0.1),
tf.keras.layers.Dense(5, activation = 'softmax')
])
model.compile(loss='categorical_crossentropy', optimizer='adam')
model.summary()
model.save("test", save_format='h5')
使用自定义图层加载模型将如下所示:
model = tf.keras.models.load_model('test.h5', custom_objects={'RandomColorDistortion': RandomColorDistortion})
where RandomColorDistortion
是您的自定义图层的名称。