ginka-generator/ginka/vae_rnn/loss.py

20 lines
628 B
Python

import torch
import torch.nn.functional as F
class VAELoss:
def __init__(self):
self.num_classes = 32
def vae_loss(self, logits, target, mu, logvar, beta=0.1):
# target: [B, 169]
end_token = torch.tensor([15], dtype=torch.long).to(logits.device)
target = torch.cat([target, end_token], dim=1)
target = F.one_hot(target, num_classes=self.num_classes).float()
recon_loss = F.cross_entropy(logits, target)
kl_loss = -0.5 * torch.mean(
1 + logvar - mu.pow(2) - logvar.exp()
)
return recon_loss + beta * kl_loss, recon_loss, kl_loss