本赛题提供示例代码，提供数据下载、模型定义、训练步骤等功能。可以基于示例代码填充注释为 TODO 的部分完成该赛题。
特点是：将在数字图片数据集 MNIST 上训练 Conditional GAN（Conditional generative adversarial nets）模型，通过输入一个随机向量 z 和额外的辅助信息 y (如类别标签)，生成特定数字的图像。
本项目可再2060显卡上运行，训练时间约为1小时
-window10
python >= 3.7 jittor >= 1.3.0 pillow >=6.2.1 numpy >=1.18.2
可用自己的号码生成图片提交结果查看分数
此项目基于jittor的热身赛，部分代码参考了(https://github.com/Jittor/gan-jittor)
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