帮我写一个基于anime数据集的gan网络的代码，用tensorf框架

我可以为你提供一个基于anime数据集的gan网络的TensorFlow代码示例：# 导入TensorFlow
import tensorflow as tf# 定义GAN网络
def create_gan_network(input_shape): # 定义输入层
inputs = tf.keras.Input(shape=input_shape) # 定义生成器
x = tf.keras.layers.Dense(128)(inputs)
x = tf.keras.layers.LeakyReLU()(x)
x = tf.keras.layers.Dense(256)(x)
x = tf.keras.layers.LeakyReLU()(x)
x = tf.keras.layers.Dense(512)(x)
x = tf.keras.layers.LeakyReLU()(x)
x = tf.keras.layers.Dense(1024)(x)
x = tf.keras.layers.LeakyReLU()(x)
x = tf.keras.layers.Dense(input_shape[0])(x)
generator = tf.keras.Model(inputs, x, name="generator") # 定义判别器
x = tf.keras.layers.Dense(128)(inputs)
x = tf.keras.layers.LeakyReLU()(x)
x = tf.keras.layers.Dense(256)(x)
x = tf.keras.layers.LeakyReLU()(x)
x = tf.keras.layers.Dense(512)(x)
x = tf.keras.layers.LeakyReLU()(x)
x = tf.keras.layers.Dense(1024)(x)
x = tf.keras.layers.LeakyReLU()(x)
x = tf.keras.layers.Dense(1, activation="sigmoid")(x)
discriminator = tf.keras.Model(inputs, x, name="discriminator") # 返回生成器和判别器
return generator, discriminator