#?-*-?coding:?utf-8?-*-
“““
Train?an?Auxiliary?Classifier?Generative?Adversarial?Network?（ACGAN）?on?the
MNIST?dataset.?See?https://arxiv.org/abs/1610.09585?for?more?details.

You?should?start?to?see?reasonable?images?after?~5?epochs?and?good?images
by?~15?epochs.?You?should?use?a?GPU?as?the?convolution-heavy?operations?are
very?slow?on?the?CPU.?Prefer?the?TensorFlow?backend?if?you?plan?on?iterating
as?the?compilation?time?can?be?a?blocker?using?Theano.

Timings:

Hardware???????????|?Backend?|?Time?/?Epoch
-------------------------------------------
?CPU???????????????|?TF??????|?3?hrs
?Titan?X?（maxwell）?|?TF??????|?4?min
?Titan?X?（maxwell）?|?TH??????|?7?min

Consult?https://github.com/lukedeo/keras-acgan?for?more?information?and
example?output
“““
from?__future__?import?print_function

from?collections?import?defaultdict
try:
????import?cPickle?as?pickle
except?ImportError:
????import?pickle
from?PIL?import?Image

from?six.moves?import?range

from?keras.datasets?import?mnist
from?keras?import?layers
from?keras.layers?import?Input?Dense?Reshape?Flatten?embedding?Dropout
from?keras.layers?import?BatchNormalization
from?keras.layers.advanced_activations?import?LeakyReLU
from?keras.layers.convolutional?import?Conv2DTranspose?Conv2D
from?keras.models?import?Sequential?Model
from?keras.optimizers?import?Adam
from?keras.utils.generic_utils?import?Progbar
import?numpy?as?np

np.random.seed（1337）
num_classes?=?10


def?build_generator（latent_size）:
????#?we?will?map?a?pair?of?（z?L）?where?z?is?a?latent?vector?and?L?is?a
????#?label?drawn?from?P_c?to?image?space?（...?28?28?1）
????cnn?=?Sequential（）

????cnn.add（Dense（3?*?3?*?384?input_dim=latent_size?activation=‘relu‘））
????cnn.add（Reshape（（3?3?384）））

????#?upsample?to?（7?7?...）
????cnn.add（Conv2DTranspose（192?5?strides=1?padding=‘valid‘
????????????????????????????activation=‘relu‘
????????????????????????????kernel_initializer=‘glorot_normal‘））
????cnn.add（BatchNormalization（））

????#?upsample?to?（14?14?...）
????cnn.add（Conv2DTranspose（96?5?strides=2?padding=‘same‘
????????????????????????????activation=‘relu‘
????????????????????????????kernel_initializer=‘glorot_normal‘））
????cnn.add（BatchNormalization（））

????#?upsample?to?（28?28?...）
????cnn.add（Conv2DTranspose（1?5?strides=2?padding=‘same‘
????????????????????????????activation=‘tanh‘
????????????????????????????kernel_initializer=‘glorot_normal‘））

????#?this?is?the?z?space?commonly?referred?to?in?GAN?papers
????latent?=?Input（shape=（latent_size?））

????#?this?will?be?our?label
????image_class?=?Input（shape=（1）?dtype=‘int32‘）

????cls?=?Flatten（）（embedding（num_classes?latent_size
??????????????????????????????embeddings_initializer=‘glorot_normal‘）（image_class））

????#?hadamard?product?between?z-space?and?a?class?conditional?embedding
????h?=?layers.multiply（[latent?cls]）

????fake_image?=?cnn（h）

????return?Model（[latent?image_class]?fake_image）


def?build_discriminator（）:
????#?build?a?relatively?