TJU Deep Learning & Neural Network

Related tags

Deep Learning Deep_Learning-Neural_Network_Lab
Overview

Deep_Learning & Neural_Network_Lab

实验环境

  • Python 3.9
  • Anaconda3(官网下载或清华镜像都行)
  • PyTorch 1.10.1(安装代码如下)
conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch

数据集下载

运行方式

  • 启动PyTorch环境
conda activate pytorch
  • 在该环境下运行程序(30-60 minutes per file)
python GAN.py               # 运行GAN.py
python CGAN.py              # 运行CGAN.py
python DCGAN.py             # 运行DCGAN.py
python WGAN.py              # 运行WGAN.py
python Improved_WGAN.py     # 运行Improved_WGAN.py

实验结果

Model epoch 1 5 10 50 100 150 200
GAN d_loss 0.510469 0.342887 0.248609 0.170712 0.120419 0.169989 0.192855
g_loss 0.956933 1.874407 2.537149 3.263798 3.905378 3.570554 3.132934
CGAN d_loss 0.106481 0.135711 0.194618 0.17816 0.124881 0.106104 0.097463
g_loss 0.660399 0.585134 0.415263 0.474954 0.632873 0.689216 0.718078
DCGAN d_loss 0.692203 0.631018 0.588311 0.463967 0.334903 0.242517 0.103577
g_loss 0.694127 0.829934 0.936831 1.402277 2.230488 2.936166 2.757655
WGAN d_loss -0.291029 -0.329138 -0.468464 -0.214993 -0.123098 -0.080621 -0.060724
g_loss -12.6155 -0.209976 -0.662237 -0.456756 -0.427529 -0.388925 -0.197952
Improved_WGAN d_loss -0.246925 -7.846449 -6.713724 -3.10867 -2.067324 -1.634501 -1.393292
g_loss -14.636739 0.762477 1.745449 -2.624076 -2.965248 -2.781996 -2.585317
  • 具体数据详见 data.xls 文件
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