tensorflow怎么加载预训练权重'model_weights.h5'

使用TensorFlow加载预训练权重可以通过以下步骤进行：

1. 导入必要的库

import tensorflow as tf
from tensorflow.keras.models import Model
from tensorflow.keras.layers import ...

2. 构建模型

inputs = tf.keras.Input(shape=(input_shape))
x = ...
outputs = ...
model = tf.keras.Model(inputs=inputs, outputs=outputs)

3. 加载预训练权重

model.load_weights('model_weights.h5')

完整代码示例：

import tensorflow as tf
from tensorflow.keras.models import Model
from tensorflow.keras.layers import Input, Conv2D, MaxPooling2D, Flatten, Dense

# 构建模型
inputs = Input(shape=(224, 224, 3))
x = Conv2D(64, (3, 3), activation='relu', padding='same')(inputs)
x = MaxPooling2D((2, 2))(x)
x = Conv2D(128, (3, 3), activation='relu', padding='same')(x)
x = MaxPooling2D((2, 2))(x)
x = Conv2D(256, (3, 3), activation='relu', padding='same')(x)
x = MaxPooling2D((2, 2))(x)
x = Flatten()(x)
x = Dense(256, activation='relu')(x)
outputs = Dense(10, activation='softmax')(x)
model = Model(inputs=inputs, outputs=outputs)

# 加载预训练权重
model.load_weights('model_weights.h5')