dcgan.py 文件源码

def make_dcgan_discriminator(Xk_d):
  x = Convolution2D(nb_filter=64, nb_row=5, nb_col=5, subsample=(2,2),
        activation=None, border_mode='same', init='glorot_uniform',
        dim_ordering='th')(Xk_d)
  x = BatchNormalization(mode=2, axis=1)(x)
  x = LeakyReLU(0.2)(x)

  x = Convolution2D(nb_filter=128, nb_row=5, nb_col=5, subsample=(2,2),
        activation=None, border_mode='same', init='glorot_uniform',
        dim_ordering='th')(x)
  x = BatchNormalization(mode=2, axis=1)(x)
  x = LeakyReLU(0.2)(x)

  x = Flatten()(x)
  x = Dense(1024)(x)
  x = BatchNormalization(mode=2)(x)
  x = LeakyReLU(0.2)(x)

  d = Dense(1, activation=None)(x)

  return d