dribnet/pixray-tiler-future ✓📝 → ❓
About
Example Output
Output
[object Object][object Object][object Object][object Object]
Performance Metrics
81.36s
Prediction Time
85.06s
Total Time
All Input Parameters
{
"mirror": false,
"prompts": "colorful granite texture",
"pixelart": false,
"settings": "iterations: 50\n"
}
Input Parameters
- mirror
- shifted pattern?
- prompts
- text prompt
- pixelart
- pixelart style?
- settings
- yaml settings
Output Schema
Example Execution Logs
---> BasePixrayPredictor Predict Using seed: 13156875299438480323 Working with z of shape (1, 256, 16, 16) = 65536 dimensions. loaded pretrained LPIPS loss from taming/modules/autoencoder/lpips/vgg.pth VQLPIPSWithDiscriminator running with hinge loss. Restored from models/vqgan_imagenet_f16_16384.ckpt Using device: cuda:0 Optimising using: Adam Using text prompts: ['colorful granite texture'] using custom losses: smoothness:0.5 0it [00:00, ?it/s] iter: 0, loss: 2.91, losses: 0.0295, 0.914, 0.0763, 0.868, 0.047, 0.83, 0.0494, 0.0932 (-0=>2.908) 0it [00:00, ?it/s] 0it [00:09, ?it/s] 0it [00:00, ?it/s] iter: 10, loss: 2.52, losses: 0.00824, 0.809, 0.075, 0.74, 0.0533, 0.717, 0.0575, 0.0577 (-0=>2.518) 0it [00:00, ?it/s] 0it [00:09, ?it/s] 0it [00:00, ?it/s] iter: 20, loss: 2.48, losses: 0.00845, 0.798, 0.0751, 0.727, 0.0548, 0.702, 0.0578, 0.0589 (-0=>2.482) 0it [00:00, ?it/s] 0it [00:09, ?it/s] 0it [00:00, ?it/s] iter: 30, loss: 2.45, losses: 0.00705, 0.792, 0.0739, 0.722, 0.0529, 0.685, 0.0572, 0.0595 (-0=>2.45) 0it [00:00, ?it/s] Dropping learning rate 0it [00:10, ?it/s] 0it [00:00, ?it/s] iter: 40, loss: 2.44, losses: 0.00601, 0.79, 0.0756, 0.721, 0.0533, 0.683, 0.0584, 0.057 (-0=>2.444) 0it [00:00, ?it/s] 0it [00:10, ?it/s] 0it [00:00, ?it/s] iter: 50, finished (-6=>2.425) 0it [00:00, ?it/s] 0it [00:00, ?it/s]
Version Details
- Version ID
056a948009a9e98f7dcabdb29e2477238433b7e8c0c78420c1bb7b53ce960edb- Version Created
- December 7, 2021