import?tensorflow?as?tf
from?tensorflow.examples.tutorials.mnist?import?input_data
import?numpy?as?np
import?matplotlib?as?mpl
mpl.use（‘Agg‘）
import?matplotlib.pyplot?as?plt
import?matplotlib.gridspec?as?gridspec
import?os?sys

sys.path.append（‘utils‘）
from?nets?import?*
from?datas?import?*

def?sample_z（m?n）:
	return?np.random.uniform（-1.?1.?size=[m?n]）

#?for?test
def?sample_y（m?n?ind）:
	y?=?np.zeros（[mn]）
	for?i?in?range（m）:
		y[i?i%8]?=?1
	#y[:7]?=?1
	#y[-10]?=?1
	return?y

def?concat（zy）:
	return?tf.concat（[zy]1）

class?CGAN_Classifier（object）:
	def?__init__（self?generator?discriminator?classifier?data）:
		self.generator?=?generator
		self.discriminator?=?discriminator
		self.classifier?=?classifier
		self.data?=?data

		#?data
		self.z_dim?=?self.data.z_dim
		self.y_dim?=?self.data.y_dim?#?condition
		self.size?=?self.data.size
		self.channel?=?self.data.channel

		self.X?=?tf.placeholder（tf.float32?shape=[None?self.size?self.size?self.channel]）
		self.z?=?tf.placeholder（tf.float32?shape=[None?self.z_dim]）
		self.y?=?tf.placeholder（tf.float32?shape=[None?self.y_dim]）

		#?nets
		self.G_sample?=?self.generator（concat（self.z?self.y））

		self.D_real?_?=?self.discriminator（self.X）
		self.D_fake?_?=?self.discriminator（self.G_sample?reuse?=?True）
	
		self.C_real?=?self.classifier（self.X）
		self.C_fake?=?self.classifier（self.G_sample?reuse?=?True）
	
		#?loss
		self.D_loss?=?tf.reduce_mean（tf.nn.sigmoid_cross_entropy_with_logits（logits=self.D_real?labels=tf.ones_like（self.D_real）））?+?tf.reduce_mean（tf.nn.sigmoid_cross_entropy_with_logits（logits=self.D_fake?labels=tf.zeros_like（self.D_fake）））
		self.G_loss?=?tf.reduce_mean（tf.nn.sigmoid_cross_entropy_with_logits（logits=self.D_fake?labels=tf.ones_like（self.D_fake）））
		self.C_real_loss?=?tf.reduce_mean（tf.nn.softmax_cross_entropy_with_logits（logits=self.C_real?labels=self.y））?#?real?label
		self.C_fake_loss?=?tf.reduce_mean（tf.nn.softmax_cross_entropy_with_logits（logits=self.C_fake?labels=self.y））??

		#?solver
		self.D_solver?=?tf.train.AdamOptimizer（learning_rate=2e-4?beta1=0.5）.minimize（self.D_loss?var_list=self.discriminator.vars）
		self.G_solver?=?tf.train.AdamOptimizer（learning_rate=2e-4?beta1=0.5）.minimize（self.G_loss?+?self.C_fake_loss?var_list=self.generator.vars）
		self.C_real_solver?=?tf.train.AdamOptimizer（learning_rate=2e-4?beta1=0.5）.minimize（self.C_real_loss?var_list=self.classifier.vars）
		#self.C_fake_solver?=?tf.train.AdamOptimizer（learning_rate=2e-4?beta1=0.5）.minimize（self.C_fake_loss?var_list=self.generator.vars）
		
		self.saver?=?tf.train.Saver（）
		gpu_options?=?tf.GPUOptions（allow_growth=True）
		self.sess?=?tf.Session（config=tf.ConfigProto（gpu_options=gpu_options））

	def?train（self?sample_dir?ckpt_dir=‘ckpt‘?training_epoches?=?1000000?batch_size?=?32）:
		fig_count?=?0
		self.sess.run（tf.global_variables_initializer（））
		
		for?epoch?in?range（training_epoches）:
			#?update?D
			for?_?in?range（1）:
				X_b?y_b?=?self.data（batch_size）

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2017-09-08?03:23??GAN-master\
?????目錄???????????0??2017-09-08?03:23??GAN-master\Datas\
?????目錄???????????0??2017-09-08?03:23??GAN-master\Datas\mnist\
?????文件?????1648877??2017-09-08?03:23??GAN-master\Datas\mnist\t10k-images-idx3-ubyte.gz
?????文件????????4542??2017-09-08?03:23??GAN-master\Datas\mnist\t10k-labels-idx1-ubyte.gz
?????文件?????9912422??2017-09-08?03:23??GAN-master\Datas\mnist\train-images-idx3-ubyte.gz
?????文件???????28881??2017-09-08?03:23??GAN-master\Datas\mnist\train-labels-idx1-ubyte.gz
?????文件???????12072??2017-09-08?03:23??GAN-master\README.md
?????目錄???????????0??2017-09-08?03:23??GAN-master\README\
?????目錄???????????0??2017-09-08?03:23??GAN-master\README\images\
?????文件????????7178??2017-09-08?03:23??GAN-master\README\images\cgan.png
?????文件????????6753??2017-09-08?03:23??GAN-master\README\images\gan.png
?????文件????????4228??2017-09-08?03:23??GAN-master\README\images\infogan1.png
?????文件????????4777??2017-09-08?03:23??GAN-master\README\images\infogan2.png
?????目錄???????????0??2017-09-08?03:23??GAN-master\README\results\
?????文件???????47347??2017-09-08?03:23??GAN-master\README\results\cgan_mlp.png
?????文件??????151303??2017-09-08?03:23??GAN-master\README\results\face3D_dcgan.png
?????目錄???????????0??2017-09-08?03:23??GAN-master\Samples\
?????目錄???????????0??2017-09-08?03:23??GAN-master\Samples\mnist_cgan_classifier\
?????文件???????32085??2017-09-08?03:23??GAN-master\Samples\mnist_cgan_classifier\000_0.png
?????文件???????14637??2017-09-08?03:23??GAN-master\Samples\mnist_cgan_classifier\001_1.png
?????文件???????13206??2017-09-08?03:23??GAN-master\Samples\mnist_cgan_classifier\002_2.png
?????文件???????12778??2017-09-08?03:23??GAN-master\Samples\mnist_cgan_classifier\003_3.png
?????文件???????12493??2017-09-08?03:23??GAN-master\Samples\mnist_cgan_classifier\004_4.png
?????文件???????12609??2017-09-08?03:23??GAN-master\Samples\mnist_cgan_classifier\005_5.png
?????文件???????12861??2017-09-08?03:23??GAN-master\Samples\mnist_cgan_classifier\006_6.png
?????文件???????11793??2017-09-08?03:23??GAN-master\Samples\mnist_cgan_classifier\348_8.png
?????目錄???????????0??2017-09-08?03:23??GAN-master\Samples\mnist_cgan_conv\
?????文件???????31917??2017-09-08?03:23??GAN-master\Samples\mnist_cgan_conv\000_0.png
?????文件???????13567??2017-09-08?03:23??GAN-master\Samples\mnist_cgan_conv\001_1.png
?????文件???????11557??2017-09-08?03:23??GAN-master\Samples\mnist_cgan_conv\002_2.png
............此處省略127個文件信息