{
  "completed_at": "2022-07-03T01:46:33.270423Z",
  "created_at": "2022-07-03T01:42:59.952944Z",
  "data_removed": false,
  "error": null,
  "id": "iz4anzmjzfgubakxieksaceysm",
  "input": {
    "lr": 0.001,
    "seed": -1,
    "prompt": "An oil painting of mountains, in the style of monet",
    "lr_decay": 0.995,
    "iterations": 250,
    "num_scales": 6,
    "num_cutouts": "8",
    "offset_type": "none",
    "display_freq": 25,
    "offset_lr_fac": 1,
    "guidance_scale": 1,
    "num_samples_per_batch": "1"
  },
  "logs": "Initializing deep image prior net...\n\nsampling loop time step:   0%|          | 0/1000 [00:00<?, ?it/s]\nsampling loop time step:   0%|          | 2/1000 [00:00<01:02, 16.07it/s]\nsampling loop time step:   0%|          | 4/1000 [00:00<00:58, 16.98it/s]\nsampling loop time step:   1%|          | 6/1000 [00:00<00:57, 17.43it/s]\nsampling loop time step:   1%|          | 8/1000 [00:00<00:55, 17.79it/s]\nsampling loop time step:   1%|          | 10/1000 [00:00<00:55, 17.88it/s]\nsampling loop time step:   1%|          | 12/1000 [00:00<00:55, 17.70it/s]\nsampling loop time step:   1%|▏         | 14/1000 [00:00<00:55, 17.65it/s]\nsampling loop time step:   2%|▏         | 16/1000 [00:00<00:55, 17.61it/s]\nsampling loop time step:   2%|▏         | 18/1000 [00:01<00:54, 17.92it/s]\nsampling loop time step:   2%|▏         | 20/1000 [00:01<00:53, 18.26it/s]\nsampling loop time step:   2%|▏         | 22/1000 [00:01<00:53, 18.37it/s]\nsampling loop time step:   2%|▏         | 24/1000 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It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n  right_pads = (((out_sz - fw_arange(num_convs, fw, device) - 1)  # (1)\n/root/.pyenv/versions/3.8.13/lib/python3.8/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. 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output/2022-07-03_01-46-18/out_00225.png\n\n\n\n\n8it [02:03, 13.86s/it]\n 90%|████████▉ | 224/250 [02:03<00:14,  1.82it/s]\n9it [02:03, 13.84s/it]\n 90%|█████████ | 225/250 [02:03<00:13,  1.79it/s]\n 90%|█████████ | 226/250 [02:04<00:13,  1.79it/s]\n 91%|█████████ | 227/250 [02:04<00:12,  1.79it/s]\n 91%|█████████ | 228/250 [02:05<00:12,  1.79it/s]\n 92%|█████████▏| 229/250 [02:06<00:11,  1.78it/s]\n 92%|█████████▏| 230/250 [02:06<00:11,  1.80it/s]\n 92%|█████████▏| 231/250 [02:07<00:10,  1.79it/s]\n 93%|█████████▎| 232/250 [02:07<00:10,  1.80it/s]\n 93%|█████████▎| 233/250 [02:08<00:09,  1.81it/s]\n 94%|█████████▎| 234/250 [02:08<00:08,  1.80it/s]\n 94%|█████████▍| 235/250 [02:09<00:08,  1.82it/s]\n 94%|█████████▍| 236/250 [02:09<00:07,  1.80it/s]\n 95%|█████████▍| 237/250 [02:10<00:07,  1.79it/s]\n 95%|█████████▌| 238/250 [02:11<00:06,  1.81it/s]\n 96%|█████████▌| 239/250 [02:11<00:06,  1.80it/s]\n 96%|█████████▌| 240/250 [02:12<00:05,  1.81it/s]\n 96%|█████████▋| 241/250 [02:12<00:04,  1.82it/s]\n 97%|█████████▋| 242/250 [02:13<00:04,  1.84it/s]\n 97%|█████████▋| 243/250 [02:13<00:03,  1.84it/s]\n 98%|█████████▊| 244/250 [02:14<00:03,  1.83it/s]\n 98%|█████████▊| 245/250 [02:14<00:02,  1.84it/s]\n 98%|█████████▊| 246/250 [02:15<00:02,  1.83it/s]\n 99%|█████████▉| 247/250 [02:15<00:01,  1.82it/s]\n 99%|█████████▉| 248/250 [02:16<00:01,  1.82it/s]\n100%|█████████▉| 249/250 [02:17<00:00,  1.82it/s]\n\n\n\n\ni: 250, loss: 0.0951135, losses: 0.0951135\n9it [02:17, 13.84s/it]\n100%|█████████▉| 249/250 [02:17<00:00,  1.82it/s]\nSaved image to output/2022-07-03_01-46-32/out_00250.png\n\n\n\n\n9it [02:17, 13.84s/it]\n100%|█████████▉| 249/250 [02:17<00:00,  1.82it/s]\n10it [02:17, 13.84s/it]\n100%|██████████| 250/250 [02:17<00:00,  1.77it/s]\n100%|██████████| 250/250 [02:17<00:00,  1.82it/s]\n\n10it [02:17, 13.77s/it]",
  "metrics": {
    "predict_time": 189.116149,
    "total_time": 213.317479
  },
  "output": [
    "https://replicate.delivery/mgxm/8ccfd17c-8ed6-478f-89ee-8642a562b09a/out_00025.png",
    "https://replicate.delivery/mgxm/860df9a9-1cec-4437-8c56-78ce77dae821/out_00050.png",
    "https://replicate.delivery/mgxm/af52dbde-8b2d-481c-bb4d-d3ac7cef93e5/out_00075.png",
    "https://replicate.delivery/mgxm/91c116d5-4013-4329-bbda-487a2cc0795f/out_00100.png",
    "https://replicate.delivery/mgxm/b4c24c6b-9a37-436a-9611-5f917c52d59f/out_00125.png",
    "https://replicate.delivery/mgxm/fa1d545a-12a8-43ff-8634-d10c998c88f6/out_00150.png",
    "https://replicate.delivery/mgxm/95577f4b-fec0-4e29-8776-15dbff32d64d/out_00175.png",
    "https://replicate.delivery/mgxm/2f40bd34-fa12-4551-84fe-208aa3a9c34a/out_00200.png",
    "https://replicate.delivery/mgxm/1fed3af3-1247-447c-a662-d58361e54bbf/out_00225.png",
    "https://replicate.delivery/mgxm/427d7301-e4d9-4893-a210-8cc91a48d188/out_00250.png"
  ],
  "started_at": "2022-07-03T01:43:24.154274Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/iz4anzmjzfgubakxieksaceysm",
    "cancel": "https://api.replicate.com/v1/predictions/iz4anzmjzfgubakxieksaceysm/cancel"
  },
  "version": "4ed232e4ebe82b3d70ee5e0526257aeeb07187f6727ee617795a7f94d2133e2d"
}