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文件名称:adversarial-master
介绍说明－－下载内容来自于网络，使用问题请自行百度
该代码实用于生成对抗网络初学者实践，有很详细的代码介绍，干货(The code is practical to generate combat network beginners practice, there is a very detailed code introduction, dry)
相关搜索： 对抗生成网络
(系统自动生成,下载前可以参看下载内容)
下载文件列表
adversarial-master
adversarial-master\.gitignore
adversarial-master\LICENSE
adversarial-master\README.md
adversarial-master\__init__.py
adversarial-master\cifar10_convolutional.yaml
adversarial-master\cifar10_fully_connected.yaml
adversarial-master\deconv.py
adversarial-master\ll.py
adversarial-master\ll_mnist.py
adversarial-master\mnist.yaml
adversarial-master\parzen_ll.py
adversarial-master\sgd.py
adversarial-master\sgd_alt.py
adversarial-master\show_gen_weights.py
adversarial-master\show_inpaint_samples.py
adversarial-master\show_samples.py
adversarial-master\show_samples_cifar_conv_paper.py
adversarial-master\show_samples_cifar_full_paper.py
adversarial-master\show_samples_inpaint.py
adversarial-master\show_samples_mnist_paper.py
adversarial-master\show_samples_tfd.py
adversarial-master\show_samples_tfd_paper.py
adversarial-master\test_deconv.py
adversarial-master\tfd_pretrain
adversarial-master\tfd_pretrain\pretrain.yaml
adversarial-master\tfd_pretrain\train.yaml
adversarial-master\.gitignore
adversarial-master\LICENSE
adversarial-master\README.md
adversarial-master\__init__.py
adversarial-master\cifar10_convolutional.yaml
adversarial-master\cifar10_fully_connected.yaml
adversarial-master\deconv.py
adversarial-master\ll.py
adversarial-master\ll_mnist.py
adversarial-master\mnist.yaml
adversarial-master\parzen_ll.py
adversarial-master\sgd.py
adversarial-master\sgd_alt.py
adversarial-master\show_gen_weights.py
adversarial-master\show_inpaint_samples.py
adversarial-master\show_samples.py
adversarial-master\show_samples_cifar_conv_paper.py
adversarial-master\show_samples_cifar_full_paper.py
adversarial-master\show_samples_inpaint.py
adversarial-master\show_samples_mnist_paper.py
adversarial-master\show_samples_tfd.py
adversarial-master\show_samples_tfd_paper.py
adversarial-master\test_deconv.py
adversarial-master\tfd_pretrain
adversarial-master\tfd_pretrain\pretrain.yaml
adversarial-master\tfd_pretrain\train.yaml
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