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WGAN 使用 MNIST 进行实验

9from labml import experiment
10
11from labml.configs import calculate

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从 DCGAN 实验导入配置

13from labml_nn.gan.dcgan import Configs

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进口 Wasserstein GAN 亏损

16from labml_nn.gan.wasserstein import GeneratorLoss, DiscriminatorLoss

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为 Wasserstein GAN 损耗设置配置选项

19calculate(Configs.generator_loss, 'wasserstein', lambda c: GeneratorLoss())
20calculate(Configs.discriminator_loss, 'wasserstein', lambda c: DiscriminatorLoss())

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23def main():

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创建配置对象

25    conf = Configs()

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创建实验

27    experiment.create(name='mnist_wassertein_dcgan', comment='test')

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覆盖配置

29    experiment.configs(conf,
30                       {
31                           'discriminator': 'cnn',
32                           'generator': 'cnn',
33                           'label_smoothing': 0.01,
34                           'generator_loss': 'wasserstein',
35                           'discriminator_loss': 'wasserstein',
36                       })

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开始实验并运行训练循环

39    with experiment.start():
40        conf.run()
41
42
43if __name__ == '__main__':
44    main()