Update cgan.py
blog.leaf
blogpost.leaf
tag.leaf
profile.leaf
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authors.leaf
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resetPassword.leaf
createPost.leaf
createUser.leaf
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JSONParser
JSONDecoder
Swift.Encoder
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@propertyWrapper
DynamicCodable
.gir
Term
Triple
Quad
TriplePattern
QuadPattern
Algebra
Expression
Query
SPARQLParser
SPARQLSerializer
getActions
getActionDetail
invoke
基于Jittor框架实现CGAN。CGAN的核心思路是将噪声与标签一起投入生成器，将真实图片与标签一起投入判别器，从而使生成器可以生成指定类别的图片。由于MLP与CNN都可以对图像信息进行提取，所以分别基于二者实现CGAN（基于CNN实现的CGAN也可以看作是DCGAN的变种）。实现的两种模型分别在MNIST与CIFAR10上进行训练和测试。
python 3.10.4
安装Jittor
# 检查python版本大于等于3.8 python --version conda install pywin32 python -m pip install jittor python -m jittor.test.test_core python -m jittor.test.test_example python -m jittor.test.test_cudnn_op
Copyright © 2022 Yiruuu.
A Jittor implementation of Conditional GAN (CGAN).
©Copyright 2023 CCF 开源发展委员会 Powered by Trustie& IntelliDE 京ICP备13000930号
A Jittor implementation of Conditional GAN (CGAN)
blog.leafblogpost.leaftag.leafprofile.leaftags.leafauthors.leafsearch.leaflogin.leafindex.leafresetPassword.leafcreatePost.leafcreateUser.leafPOSTRoutes.both)UIDevice.current.name).required)nil)JSONParserandJSONDecoderSwift.EncoderandSwift.DecoderNSAttributedStringby closure compositionNSAttributedStringby passing an attributes objectNSAttributedStringwith+@propertyWrapper?DynamicCodable?.girFilesTermTriple,Quad,TriplePattern, andQuadPatternAlgebraExpressionQuerySPARQLParserSPARQLSerializergetActionsgetActionDetailinvoke🌈 概述
基于Jittor框架实现CGAN。CGAN的核心思路是将噪声与标签一起投入生成器，将真实图片与标签一起投入判别器，从而使生成器可以生成指定类别的图片。由于MLP与CNN都可以对图像信息进行提取，所以分别基于二者实现CGAN（基于CNN实现的CGAN也可以看作是DCGAN的变种）。实现的两种模型分别在MNIST与CIFAR10上进行训练和测试。
🔧 环境配置
python 3.10.4
安装Jittor
🔗 参考
Copyright © 2022 Yiruuu.