Python-各种对抗神经网络GAN大合集
标签:
•
文件类型: .zip
•
文件大小: 12.91MB
•
下载次数: 1
•
各种对抗神经网络(GAN)大合集
代码片段和文件信息
属性 大小 日期 时间 名称
----------- --------- ---------- ----- ----
目录 0 2017-09-08 03:23 GAN-master
目录 0 2017-09-08 03:23 GAN-masterDatas
目录 0 2017-09-08 03:23 GAN-masterDatasmnist
文件 1648877 2017-09-08 03:23 GAN-masterDatasmnist 10k-images-idx3-ubyte.gz
文件 4542 2017-09-08 03:23 GAN-masterDatasmnist 10k-labels-idx1-ubyte.gz
文件 9912422 2017-09-08 03:23 GAN-masterDatasmnist rain-images-idx3-ubyte.gz
文件 28881 2017-09-08 03:23 GAN-masterDatasmnist rain-labels-idx1-ubyte.gz
文件 12072 2017-09-08 03:23 GAN-masterREADME.md
目录 0 2017-09-08 03:23 GAN-masterREADME
目录 0 2017-09-08 03:23 GAN-masterREADMEimages
文件 7178 2017-09-08 03:23 GAN-masterREADMEimagescgan.png
文件 6753 2017-09-08 03:23 GAN-masterREADMEimagesgan.png
文件 4228 2017-09-08 03:23 GAN-masterREADMEimagesinfogan1.png
文件 4777 2017-09-08 03:23 GAN-masterREADMEimagesinfogan2.png
目录 0 2017-09-08 03:23 GAN-masterREADME
esults
文件 47347 2017-09-08 03:23 GAN-masterREADME
esultscgan_mlp.png
文件 151303 2017-09-08 03:23 GAN-masterREADME
esultsface3D_dcgan.png
目录 0 2017-09-08 03:23 GAN-masterSamples
目录 0 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier
文件 32085 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier 00_0.png
文件 14637 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier 01_1.png
文件 13206 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier 02_2.png
文件 12778 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier 03_3.png
文件 12493 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier 04_4.png
文件 12609 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier 05_5.png
文件 12861 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier 06_6.png
文件 11793 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier348_8.png
目录 0 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_conv
文件 31917 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_conv 00_0.png
文件 13567 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_conv 01_1.png
文件 11557 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_conv 02_2.png
............此处省略127个文件信息
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)
属性 大小 日期 时间 名称
----------- --------- ---------- ----- ----
目录 0 2017-09-08 03:23 GAN-master
目录 0 2017-09-08 03:23 GAN-masterDatas
目录 0 2017-09-08 03:23 GAN-masterDatasmnist
文件 1648877 2017-09-08 03:23 GAN-masterDatasmnist 10k-images-idx3-ubyte.gz
文件 4542 2017-09-08 03:23 GAN-masterDatasmnist 10k-labels-idx1-ubyte.gz
文件 9912422 2017-09-08 03:23 GAN-masterDatasmnist rain-images-idx3-ubyte.gz
文件 28881 2017-09-08 03:23 GAN-masterDatasmnist rain-labels-idx1-ubyte.gz
文件 12072 2017-09-08 03:23 GAN-masterREADME.md
目录 0 2017-09-08 03:23 GAN-masterREADME
目录 0 2017-09-08 03:23 GAN-masterREADMEimages
文件 7178 2017-09-08 03:23 GAN-masterREADMEimagescgan.png
文件 6753 2017-09-08 03:23 GAN-masterREADMEimagesgan.png
文件 4228 2017-09-08 03:23 GAN-masterREADMEimagesinfogan1.png
文件 4777 2017-09-08 03:23 GAN-masterREADMEimagesinfogan2.png
目录 0 2017-09-08 03:23 GAN-masterREADME
esults
文件 47347 2017-09-08 03:23 GAN-masterREADME
esultscgan_mlp.png
文件 151303 2017-09-08 03:23 GAN-masterREADME
esultsface3D_dcgan.png
目录 0 2017-09-08 03:23 GAN-masterSamples
目录 0 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier
文件 32085 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier 00_0.png
文件 14637 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier 01_1.png
文件 13206 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier 02_2.png
文件 12778 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier 03_3.png
文件 12493 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier 04_4.png
文件 12609 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier 05_5.png
文件 12861 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier 06_6.png
文件 11793 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_classifier348_8.png
目录 0 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_conv
文件 31917 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_conv 00_0.png
文件 13567 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_conv 01_1.png
文件 11557 2017-09-08 03:23 GAN-masterSamplesmnist_cgan_conv 02_2.png
............此处省略127个文件信息
版权声明:本文内容由互联网用户自发贡献,该文观点仅代表作者本人。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如发现本站有涉嫌抄袭侵权/违法违规的内容, 请发送邮件举报,一经查实,本站将立刻删除。
评论列表(条)