tactile_vae
ViT-based tactile variational autoencoder.
Architecture
- Encoder:
PatchEmbed + Transformer blocks + fixed sin-cos positional embedding - Latent:
mu/logvar+ reparameterization - Decoder: latent-conditioned transformer patch decoder + unpatchify
Usage
import torch
from tactile_vae.model import TactileVAE, VAELoss
model = TactileVAE()
out = model(torch.randn(2, 3, 128, 128))
loss_fn = VAELoss(beta=1.0)
losses = loss_fn(out["x_hat"], torch.randn(2, 3, 128, 128), out["mu"], out["logvar"])