可以帮用python写一下DCGAN的生成器和判别器部分的代码吗
时间: 2023-02-23 10:34:41 浏览: 44
当然可以!下面是DCGAN生成器和判别器的代码:
生成器代码:
```
import tensorflow as tf
def make_generator_model():
model = tf.keras.Sequential()
model.add(tf.keras.layers.Dense(7*7*256, use_bias=False, input_shape=(100,)))
model.add(tf.keras.layers.BatchNormalization())
model.add(tf.keras.layers.LeakyReLU())
model.add(tf.keras.layers.Reshape((7, 7, 256)))
assert model.output_shape == (None, 7, 7, 256)
model.add(tf.keras.layers.Conv2DTranspose(128, (5, 5), strides=(1, 1), padding='same', use_bias=False))
assert model.output_shape == (None, 7, 7, 128)
model.add(tf.keras.layers.BatchNormalization())
model.add(tf.keras.layers.LeakyReLU())
model.add(tf.keras.layers.Conv2DTranspose(64, (5, 5), strides=(2, 2), padding='same', use_bias=False))
assert model.output_shape == (None, 14, 14, 64)
model.add(tf.keras.layers.BatchNormalization())
model.add(tf.keras.layers.LeakyReLU())
model.add(tf.keras.layers.Conv2DTranspose(1, (5, 5), strides=(2, 2), padding='same', use_bias=False, activation='tanh'))
assert model.output_shape == (None, 28, 28, 1)
return model
```
判别器代码:
```
import tensorflow as tf
def make_discriminator_model():
model = tf.keras.Sequential()
model.add(tf.keras.layers.Conv2D(64, (5, 5), strides=(2, 2), padding='same',
input_shape=[28, 28, 1]))
model.add(tf.keras.layers.LeakyReLU())
model.add(tf.keras.layers.Dropout(0.3))
model.add(tf.keras.layers.Conv2D(128, (5, 5), strides=(2, 2), padding='same'))
model.add(tf.keras.layers.LeakyReLU())
model.add(tf.keras.layers.Dropout(0.3))
model.add(tf.keras.layers.Flatten())
model.add(tf.keras.layers.Dense(1))
return model
```
希望对你有所帮助!