9fe431ed5be2ebe43d08d5506a8f8eb690399a80,vae/main.py,,loss_function,#Any#Any#Any#Any#,83

Before Change

    // Kingma and Welling. Auto-Encoding Variational Bayes. ICLR, 2014
    // https://arxiv.org/abs/1312.6114
    // 0.5 * sum(1 + log(sigma^2) - mu^2 - sigma^2)
    KLD_element = mu.pow(2).add_(logvar.exp()).mul_(-1).add_(1).add_(logvar)
    KLD = torch.sum(KLD_element).mul_(-0.5)
    // Normalise by same number of elements as in reconstruction
    KLD /= args.batch_size * 784

After Change

    // Kingma and Welling. Auto-Encoding Variational Bayes. ICLR, 2014
    // https://arxiv.org/abs/1312.6114
    // 0.5 * sum(1 + log(sigma^2) - mu^2 - sigma^2)
    KLD = -0.5 * torch.sum(1 + logvar - mu.pow(2) - logvar.exp())
    // Normalise by same number of elements as in reconstruction
    KLD /= args.batch_size * 784

    return BCE + KLD

Instances