向keras中的Generator模型添加类信息

from keras.models import Model
from keras.layers import Input, Concatenate, Dense

# 定义输入层
class_input = Input(shape=(1,), dtype='int32')

# 合并输入层和Generator模型的输入层
generator_input = generator.input
combined_input = Concatenate()([class_input, generator_input])

# 修改Generator模型
x = Dense(64, activation='relu')(combined_input)
x = Dense(128, activation='relu')(x)
output = generator.output

# 创建新的Generator模型
generator_with_class = Model(inputs=[class_input, generator_input], outputs=output)

# 编译模型并训练
generator_with_class.compile(optimizer='adam', loss='binary_crossentropy')
generator_with_class.fit([class_data, generator_data], target_data, epochs=10, batch_size=32)