{
  "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 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  "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"
}

{
  "completed_at": "2022-07-03T03:23:30.093669Z",
  "created_at": "2022-07-03T03:20:15.542654Z",
  "data_removed": false,
  "error": null,
  "id": "ebekt6p3cnfr5ncion4aurxdxq",
  "input": {
    "lr": 0.001,
    "seed": -1,
    "prompt": "steam",
    "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<00:57, 17.37it/s]\nsampling loop time step:   0%|          | 4/1000 [00:00<00:54, 18.20it/s]\nsampling loop time step:   1%|          | 6/1000 [00:00<00:53, 18.63it/s]\nsampling loop time step:   1%|          | 8/1000 [00:00<00:52, 18.77it/s]\nsampling loop time step:   1%|          | 10/1000 [00:00<00:53, 18.68it/s]\nsampling loop time step:   1%|          | 12/1000 [00:00<00:52, 18.65it/s]\nsampling loop time step:   1%|▏         | 14/1000 [00:00<00:52, 18.61it/s]\nsampling loop time step:   2%|▏         | 16/1000 [00:00<00:52, 18.64it/s]\nsampling loop time step:   2%|▏         | 18/1000 [00:00<00:52, 18.60it/s]\nsampling loop time step:   2%|▏         | 20/1000 [00:01<00:53, 18.45it/s]\nsampling loop time step:   2%|▏         | 22/1000 [00:01<00:52, 18.66it/s]\nsampling loop time step:   2%|▏         | 24/1000 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[00:54<00:00, 18.68it/s]\nsampling loop time step:  99%|█████████▉| 988/1000 [00:54<00:00, 17.43it/s]\nsampling loop time step:  99%|█████████▉| 990/1000 [00:54<00:00, 17.42it/s]\nsampling loop time step:  99%|█████████▉| 992/1000 [00:54<00:00, 17.34it/s]\nsampling loop time step:  99%|█████████▉| 994/1000 [00:54<00:00, 17.65it/s]\nsampling loop time step: 100%|█████████▉| 996/1000 [00:54<00:00, 18.04it/s]\nsampling loop time step: 100%|█████████▉| 998/1000 [00:54<00:00, 18.39it/s]\nsampling loop time step: 100%|██████████| 1000/1000 [00:54<00:00, 18.52it/s]\nsampling loop time step: 100%|██████████| 1000/1000 [00:54<00:00, 18.23it/s]\n\nUsing device: cuda\nSeed: 43187694\n0it [00:00, ?it/s]\n  0%|          | 0/250 [00:00<?, ?it/s]\n  0%|          | 1/250 [00:00<02:22,  1.75it/s]\n  1%|          | 2/250 [00:01<02:17,  1.80it/s]\n  1%|          | 3/250 [00:01<02:16,  1.81it/s]\n  2%|▏         | 4/250 [00:02<02:17,  1.79it/s]\n  2%|▏         | 5/250 [00:02<02:17,  1.79it/s]\n  2%|▏       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?it/s]\n 10%|▉         | 24/250 [00:14<02:07,  1.77it/s]\n\n\nSaved image to output/2022-07-03_03-21-24/out_00025.png\n\n\n0it [00:14, ?it/s]\n 10%|▉         | 24/250 [00:14<02:07,  1.77it/s]\n1it [00:14, 14.23s/it]\n 10%|█         | 25/250 [00:14<02:09,  1.74it/s]\n 10%|█         | 26/250 [00:14<02:07,  1.76it/s]\n 11%|█         | 27/250 [00:15<02:07,  1.75it/s]\n 11%|█         | 28/250 [00:15<02:06,  1.75it/s]\n 12%|█▏        | 29/250 [00:16<02:04,  1.77it/s]\n 12%|█▏        | 30/250 [00:16<02:04,  1.77it/s]\n 12%|█▏        | 31/250 [00:17<02:03,  1.78it/s]\n 13%|█▎        | 32/250 [00:18<02:01,  1.79it/s]\n 13%|█▎        | 33/250 [00:18<02:01,  1.78it/s]\n 14%|█▎        | 34/250 [00:19<02:03,  1.74it/s]\n 14%|█▍        | 35/250 [00:19<02:02,  1.76it/s]\n 14%|█▍        | 36/250 [00:20<02:01,  1.76it/s]\n 15%|█▍        | 37/250 [00:20<02:00,  1.77it/s]\n 15%|█▌        | 38/250 [00:21<02:00,  1.76it/s]\n 16%|█▌        | 39/250 [00:22<01:59,  1.77it/s]\n 16%|█▌        | 40/250 [00:22<01:59,  1.76it/s]\n 16%|█▋        | 41/250 [00:23<01:58,  1.76it/s]\n 17%|█▋        | 42/250 [00:23<01:57,  1.77it/s]\n 17%|█▋        | 43/250 [00:24<01:57,  1.76it/s]\n 18%|█▊        | 44/250 [00:24<01:55,  1.78it/s]\n 18%|█▊        | 45/250 [00:25<01:55,  1.78it/s]\n 18%|█▊        | 46/250 [00:25<01:54,  1.79it/s]\n 19%|█▉        | 47/250 [00:26<01:53,  1.79it/s]\n 19%|█▉        | 48/250 [00:27<01:53,  1.78it/s]\ni: 50, loss: 0.202775, losses: 0.202775\n 20%|█▉        | 49/250 [00:27<01:52,  1.78it/s]\n\n\n\n\n1it [00:28, 14.23s/it]\n 20%|█▉        | 49/250 [00:28<01:52,  1.78it/s]\nSaved image to output/2022-07-03_03-21-38/out_00050.png\n\n\n\n\n1it [00:28, 14.23s/it]\n 20%|█▉        | 49/250 [00:28<01:52,  1.78it/s]\n2it [00:28, 14.18s/it]\n 20%|██        | 50/250 [00:28<01:55,  1.73it/s]\n 20%|██        | 51/250 [00:28<01:53,  1.75it/s]\n 21%|██        | 52/250 [00:29<01:53,  1.75it/s]\n 21%|██        | 53/250 [00:29<01:50,  1.78it/s]\n 22%|██▏       | 54/250 [00:30<01:48,  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1.82it/s]\ni: 75, loss: 0.160689, losses: 0.160689\n\n\n\n\n2it [00:42, 14.18s/it]\n 30%|██▉       | 74/250 [00:42<01:36,  1.82it/s]\nSaved image to output/2022-07-03_03-21-52/out_00075.png\n\n\n\n\n2it [00:42, 14.18s/it]\n 30%|██▉       | 74/250 [00:42<01:36,  1.82it/s]\n3it [00:42, 14.03s/it]\n 30%|███       | 75/250 [00:42<01:38,  1.78it/s]\n 30%|███       | 76/250 [00:42<01:36,  1.80it/s]\n 31%|███       | 77/250 [00:43<01:36,  1.80it/s]\n 31%|███       | 78/250 [00:43<01:34,  1.82it/s]\n 32%|███▏      | 79/250 [00:44<01:34,  1.80it/s]\n 32%|███▏      | 80/250 [00:44<01:33,  1.82it/s]\n 32%|███▏      | 81/250 [00:45<01:32,  1.83it/s]\n 33%|███▎      | 82/250 [00:45<01:32,  1.82it/s]\n 33%|███▎      | 83/250 [00:46<01:32,  1.80it/s]\n 34%|███▎      | 84/250 [00:47<01:31,  1.81it/s]\n 34%|███▍      | 85/250 [00:47<01:31,  1.80it/s]\n 34%|███▍      | 86/250 [00:48<01:30,  1.82it/s]\n 35%|███▍      | 87/250 [00:48<01:30,  1.81it/s]\n 35%|███▌      | 88/250 [00:49<01:29,  1.80it/s]\n 36%|███▌      | 89/250 [00:49<01:28,  1.83it/s]\n 36%|███▌      | 90/250 [00:50<01:27,  1.82it/s]\n 36%|███▋      | 91/250 [00:50<01:28,  1.80it/s]\n 37%|███▋      | 92/250 [00:51<01:27,  1.81it/s]\n 37%|███▋      | 93/250 [00:52<01:26,  1.83it/s]\n 38%|███▊      | 94/250 [00:52<01:25,  1.82it/s]\n 38%|███▊      | 95/250 [00:53<01:26,  1.80it/s]\n 38%|███▊      | 96/250 [00:53<01:24,  1.82it/s]\n 39%|███▉      | 97/250 [00:54<01:23,  1.83it/s]\n 39%|███▉      | 98/250 [00:54<01:23,  1.82it/s]\n 40%|███▉      | 99/250 [00:55<01:22,  1.82it/s]\ni: 100, loss: 0.134296, losses: 0.134296\n\n\n\n\n3it [00:55, 14.03s/it]\n 40%|███▉      | 99/250 [00:55<01:22,  1.82it/s]\nSaved image to output/2022-07-03_03-22-06/out_00100.png\n\n\n\n\n3it [00:55, 14.03s/it]\n 40%|███▉      | 99/250 [00:55<01:22,  1.82it/s]\n4it [00:55, 13.93s/it]\n 40%|████      | 100/250 [00:55<01:23,  1.79it/s]\n 40%|████      | 101/250 [00:56<01:22,  1.80it/s]\n 41%|████      | 102/250 [00:56<01:22,  1.80it/s]\n 41%|████   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output/2022-07-03_03-23-01/out_00200.png\n7it [01:51, 13.85s/it]\n 80%|███████▉  | 199/250 [01:51<00:27,  1.83it/s]\n8it [01:51, 13.86s/it]\n 80%|████████  | 200/250 [01:51<00:27,  1.79it/s]\n 80%|████████  | 201/250 [01:51<00:27,  1.80it/s]\n 81%|████████  | 202/250 [01:52<00:26,  1.80it/s]\n 81%|████████  | 203/250 [01:52<00:26,  1.81it/s]\n 82%|████████▏ | 204/250 [01:53<00:25,  1.81it/s]\n 82%|████████▏ | 205/250 [01:54<00:25,  1.80it/s]\n 82%|████████▏ | 206/250 [01:54<00:24,  1.80it/s]\n 83%|████████▎ | 207/250 [01:55<00:23,  1.81it/s]\n 83%|████████▎ | 208/250 [01:55<00:23,  1.79it/s]\n 84%|████████▎ | 209/250 [01:56<00:22,  1.81it/s]\n 84%|████████▍ | 210/250 [01:56<00:22,  1.81it/s]\n 84%|████████▍ | 211/250 [01:57<00:21,  1.82it/s]\n 85%|████████▍ | 212/250 [01:57<00:20,  1.84it/s]\n 85%|████████▌ | 213/250 [01:58<00:20,  1.83it/s]\n 86%|████████▌ | 214/250 [01:58<00:19,  1.83it/s]\n 86%|████████▌ | 215/250 [01:59<00:19,  1.82it/s]\n 86%|████████▋ | 216/250 [02:00<00:18,  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1.82it/s]\n\n\n\ni: 250, loss: 0.0774112, losses: 0.0774112\n\n9it [02:18, 13.85s/it]\n100%|█████████▉| 249/250 [02:18<00:00,  1.82it/s]\n\n\n\n\nSaved image to output/2022-07-03_03-23-29/out_00250.png\n9it [02:18, 13.85s/it]\n100%|█████████▉| 249/250 [02:18<00:00,  1.82it/s]\n10it [02:18, 13.84s/it]\n100%|██████████| 250/250 [02:18<00:00,  1.79it/s]\n100%|██████████| 250/250 [02:18<00:00,  1.80it/s]\n\n10it [02:18, 13.90s/it]",
  "metrics": {
    "predict_time": 194.362297,
    "total_time": 194.551015
  },
  "output": [
    "https://replicate.delivery/mgxm/3c79bc29-179a-4343-ba0c-372ab86c12b1/out_00025.png",
    "https://replicate.delivery/mgxm/25e8d069-927e-45e2-9f92-d1ef665eae29/out_00050.png",
    "https://replicate.delivery/mgxm/bee04f49-757e-4fc5-8c22-63f2b14826e8/out_00075.png",
    "https://replicate.delivery/mgxm/6b4c962c-a0be-4d2c-bbb9-f9de0c4b43e6/out_00100.png",
    "https://replicate.delivery/mgxm/4e0f7f31-3503-432e-8b41-c919724ba190/out_00125.png",
    "https://replicate.delivery/mgxm/e4d52c56-edf4-4016-a0b3-f6ea08053148/out_00150.png",
    "https://replicate.delivery/mgxm/38bac1a3-d878-4b4a-b3bd-784ce848aec2/out_00175.png",
    "https://replicate.delivery/mgxm/781b7184-1b69-4f50-a585-33aea93bfcb0/out_00200.png",
    "https://replicate.delivery/mgxm/66f3e20d-1f4c-421f-aa65-37129363e62b/out_00225.png",
    "https://replicate.delivery/mgxm/60ac6b80-c987-44fc-a7c1-79eadb8e40f0/out_00250.png"
  ],
  "started_at": "2022-07-03T03:20:15.731372Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/ebekt6p3cnfr5ncion4aurxdxq",
    "cancel": "https://api.replicate.com/v1/predictions/ebekt6p3cnfr5ncion4aurxdxq/cancel"
  },
  "version": "4ed232e4ebe82b3d70ee5e0526257aeeb07187f6727ee617795a7f94d2133e2d"
}

{
  "completed_at": "2022-07-03T09:19:47.110655Z",
  "created_at": "2022-07-03T09:13:45.488339Z",
  "data_removed": false,
  "error": null,
  "id": "h2krdma3yjat3jjtmnfksd3omi",
  "input": {
    "lr": 0.001,
    "seed": -1,
    "prompt": "Hyrule field ",
    "lr_decay": 0.995,
    "iterations": 250,
    "num_scales": 6,
    "num_cutouts": "16",
    "offset_type": "none",
    "display_freq": "2",
    "offset_lr_fac": 1,
    "guidance_scale": "0.87",
    "num_samples_per_batch": "5"
  },
  "logs": "Initializing deep image prior net...\n\nsampling loop time step:   0%|          | 0/1000 [00:00<?, ?it/s]\nsampling loop time step:   0%|          | 1/1000 [00:00<02:14,  7.44it/s]\nsampling loop time step:   0%|          | 2/1000 [00:00<01:54,  8.72it/s]\nsampling loop time step:   0%|          | 3/1000 [00:00<01:59,  8.31it/s]\nsampling loop time step:   0%|          | 4/1000 [00:00<01:57,  8.51it/s]\nsampling loop time step:   0%|          | 5/1000 [00:00<01:57,  8.48it/s]\nsampling loop time step:   1%|          | 6/1000 [00:00<01:53,  8.78it/s]\nsampling loop time step:   1%|          | 7/1000 [00:00<01:55,  8.58it/s]\nsampling loop time step:   1%|          | 8/1000 [00:00<01:55,  8.58it/s]\nsampling loop time step:   1%|          | 9/1000 [00:01<02:01,  8.16it/s]\nsampling loop time step:   1%|          | 10/1000 [00:01<02:02,  8.06it/s]\nsampling loop time step:   1%|          | 11/1000 [00:01<01:59,  8.30it/s]\nsampling loop time step:   1%|          | 12/1000 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1000/1000 [01:51<00:00,  8.99it/s]\nsampling loop time step: 100%|██████████| 1000/1000 [01:51<00:00,  8.99it/s]\n\nUsing device: cuda\nSeed: 2142220\n0it [00:00, ?it/s]\n  0%|          | 0/250 [00:00<?, ?it/s]\n  0%|          | 1/250 [00:01<04:09,  1.00s/it]\n\n\ni: 2, loss: 0.532876, losses: 0.532876\n\n\n  0%|          | 1/250 [00:01<04:09,  1.00s/it]\n0it [00:02, ?it/s]\n\n\nSaved image to output/2022-07-03_09-15-38/out_00002.png\n\n\n  0%|          | 1/250 [00:01<04:09,  1.00s/it]\n0it [00:02, ?it/s]\n1it [00:02,  2.10s/it]\n  1%|          | 2/250 [00:01<04:07,  1.00it/s]\n  1%|          | 3/250 [00:03<04:10,  1.01s/it]\n\n\n\ni: 4, loss: 0.48591, losses: 0.48591\n\n  1%|          | 3/250 [00:04<04:10,  1.01s/it]\n1it [00:04,  2.10s/it]\n\n\nSaved image to output/2022-07-03_09-15-41/out_00004.png\n\n\n  1%|          | 3/250 [00:04<04:10,  1.01s/it]\n1it [00:04,  2.10s/it]\n2it [00:04,  2.07s/it]\n  2%|▏         | 4/250 [00:04<04:09,  1.01s/it]\n  2%|▏         | 5/250 [00:05<04:04,  1.00it/s]\n\n\ni: 6, loss: 0.481745, losses: 0.481745\n\n\n  2%|▏         | 5/250 [00:05<04:04,  1.00it/s]\n2it [00:06,  2.07s/it]\n\n\nSaved image to output/2022-07-03_09-15-42/out_00006.png\n\n\n  2%|▏         | 5/250 [00:06<04:04,  1.00it/s]\n2it [00:06,  2.07s/it]\n3it [00:06,  2.02s/it]\n  2%|▏         | 6/250 [00:06<04:03,  1.00it/s]\n  3%|▎         | 7/250 [00:07<04:01,  1.00it/s]\n\n\ni: 8, loss: 0.464828, losses: 0.464828\n\n\n  3%|▎         | 7/250 [00:07<04:01,  1.00it/s]\n3it [00:08,  2.02s/it]\n\n\n\n\nSaved image to output/2022-07-03_09-15-44/out_00008.png\n  3%|▎         | 7/250 [00:07<04:01,  1.00it/s]\n3it [00:08,  2.02s/it]\n4it [00:08,  2.01s/it]\n  3%|▎         | 8/250 [00:07<04:00,  1.01it/s]\n  4%|▎         | 9/250 [00:08<03:57,  1.01it/s]\n\n\ni: 10, loss: 0.42559, losses: 0.42559\n\n\n  4%|▎         | 9/250 [00:09<03:57,  1.01it/s]\n4it [00:10,  2.01s/it]\n\nSaved image to output/2022-07-03_09-15-46/out_00010.png\n\n\n\n  4%|▎         | 9/250 [00:09<03:57,  1.01it/s]\n4it [00:10,  2.01s/it]\n5it [00:10,  1.99s/it]\n  4%|▍         | 10/250 [00:09<03:56,  1.01it/s]\n  4%|▍         | 11/250 [00:10<03:53,  1.02it/s]\n\n\n\n\ni: 12, loss: 0.413679, losses: 0.413679\n  4%|▍         | 11/250 [00:11<03:53,  1.02it/s]\n5it [00:11,  1.99s/it]\n\n\n\nSaved image to output/2022-07-03_09-15-48/out_00012.png\n\n  4%|▍         | 11/250 [00:11<03:53,  1.02it/s]\n5it [00:11,  1.99s/it]\n6it [00:11,  1.96s/it]\n  5%|▍         | 12/250 [00:11<03:51,  1.03it/s]\n  5%|▌         | 13/250 [00:12<03:53,  1.01it/s]\n\n\n\ni: 14, loss: 0.390853, losses: 0.390853\n\n  5%|▌         | 13/250 [00:13<03:53,  1.01it/s]\n6it [00:13,  1.96s/it]\n\n\nSaved image to output/2022-07-03_09-15-50/out_00014.png\n\n\n  5%|▌         | 13/250 [00:13<03:53,  1.01it/s]\n6it [00:13,  1.96s/it]\n7it [00:13,  1.98s/it]\n  6%|▌         | 14/250 [00:13<03:53,  1.01it/s]\n  6%|▌         | 15/250 [00:14<03:49,  1.02it/s]\ni: 16, loss: 0.341264, losses: 0.341264\n\n\n\n\n  6%|▌         | 15/250 [00:15<03:49,  1.02it/s]\n7it [00:15,  1.98s/it]\n\n\nSaved image to output/2022-07-03_09-15-52/out_00016.png\n\n\n  6%|▌         | 15/250 [00:15<03:49,  1.02it/s]\n7it [00:15,  1.98s/it]\n8it [00:15,  1.97s/it]\n  6%|▋         | 16/250 [00:15<03:50,  1.01it/s]\n  7%|▋         | 17/250 [00:16<03:52,  1.00it/s]\n\n\ni: 18, loss: 0.34783, losses: 0.34783\n\n\n  7%|▋         | 17/250 [00:17<03:52,  1.00it/s]\n8it [00:17,  1.97s/it]\n\nSaved image to output/2022-07-03_09-15-54/out_00018.png\n\n\n\n  7%|▋         | 17/250 [00:17<03:52,  1.00it/s]\n8it [00:17,  1.97s/it]\n9it [00:17,  1.99s/it]\n  7%|▋         | 18/250 [00:17<03:50,  1.00it/s]\n  8%|▊         | 19/250 [00:18<03:48,  1.01it/s]\n\n\ni: 20, loss: 0.352515, losses: 0.352515\n\n\n  8%|▊         | 19/250 [00:19<03:48,  1.01it/s]\n9it [00:19,  1.99s/it]\n\n\nSaved image to output/2022-07-03_09-15-56/out_00020.png\n\n\n  8%|▊         | 19/250 [00:19<03:48,  1.01it/s]\n9it [00:19,  1.99s/it]\n10it [00:19,  1.99s/it]\n  8%|▊    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image to output/2022-07-03_09-16-02/out_00026.png\n\n\n\n 10%|█         | 25/250 [00:25<03:43,  1.01it/s]\n12it [00:25,  1.98s/it]\n13it [00:25,  1.98s/it]\n 10%|█         | 26/250 [00:25<03:41,  1.01it/s]\n 11%|█         | 27/250 [00:26<03:40,  1.01it/s]\n\ni: 28, loss: 0.299946, losses: 0.299946\n\n\n\n 11%|█         | 27/250 [00:27<03:40,  1.01it/s]\n13it [00:27,  1.98s/it]\n\n\nSaved image to output/2022-07-03_09-16-04/out_00028.png\n\n\n 11%|█         | 27/250 [00:27<03:40,  1.01it/s]\n13it [00:27,  1.98s/it]\n14it [00:27,  1.99s/it]\n 11%|█         | 28/250 [00:27<03:41,  1.00it/s]\n 12%|█▏        | 29/250 [00:28<03:37,  1.02it/s]\n\n\ni: 30, loss: 0.266263, losses: 0.266263\n\n\n 12%|█▏        | 29/250 [00:29<03:37,  1.02it/s]\n14it [00:29,  1.99s/it]\nSaved image to output/2022-07-03_09-16-06/out_00030.png\n\n\n\n\n 12%|█▏        | 29/250 [00:29<03:37,  1.02it/s]\n14it [00:29,  1.99s/it]\n15it [00:29,  1.97s/it]\n 12%|█▏        | 30/250 [00:29<03:36,  1.02it/s]\n 12%|█▏        | 31/250 [00:30<03:34,  1.02it/s]\n\ni: 32, loss: 0.270326, losses: 0.270326\n\n\n\n 12%|█▏        | 31/250 [00:31<03:34,  1.02it/s]\n15it [00:31,  1.97s/it]\nSaved image to output/2022-07-03_09-16-08/out_00032.png\n\n\n\n\n 12%|█▏        | 31/250 [00:31<03:34,  1.02it/s]\n15it [00:31,  1.97s/it]\n16it [00:31,  1.97s/it]\n 13%|█▎        | 32/250 [00:31<03:33,  1.02it/s]\n 13%|█▎        | 33/250 [00:32<03:33,  1.01it/s]\ni: 34, loss: 0.254662, losses: 0.254662\n\n\n\n\n 13%|█▎        | 33/250 [00:33<03:33,  1.01it/s]\n16it [00:33,  1.97s/it]\n\nSaved image to output/2022-07-03_09-16-10/out_00034.png\n\n\n\n 13%|█▎        | 33/250 [00:33<03:33,  1.01it/s]\n16it [00:33,  1.97s/it]\n17it [00:33,  1.97s/it]\n 14%|█▎        | 34/250 [00:33<03:33,  1.01it/s]\n 14%|█▍        | 35/250 [00:34<03:33,  1.01it/s]\n\ni: 36, loss: 0.24958, losses: 0.24958\n\n\n\n 14%|█▍        | 35/250 [00:35<03:33,  1.01it/s]\n17it [00:35,  1.97s/it]\nSaved image to output/2022-07-03_09-16-12/out_00036.png\n\n\n\n\n 14%|█▍        | 35/250 [00:35<03:33,  1.01it/s]\n17it [00:35,  1.97s/it]\n18it [00:35,  1.99s/it]\n 14%|█▍        | 36/250 [00:35<03:34,  1.00s/it]\n 15%|█▍        | 37/250 [00:36<03:32,  1.00it/s]\n\ni: 38, loss: 0.197687, losses: 0.197687\n\n\n\n 15%|█▍        | 37/250 [00:37<03:32,  1.00it/s]\n18it [00:37,  1.99s/it]\n\n\nSaved image to output/2022-07-03_09-16-14/out_00038.png\n\n\n 15%|█▍        | 37/250 [00:37<03:32,  1.00it/s]\n18it [00:37,  1.99s/it]\n19it [00:37,  1.98s/it]\n 15%|█▌        | 38/250 [00:37<03:30,  1.01it/s]\n 16%|█▌        | 39/250 [00:38<03:28,  1.01it/s]\ni: 40, loss: 0.174232, losses: 0.174232\n\n\n\n\n 16%|█▌        | 39/250 [00:39<03:28,  1.01it/s]\n19it [00:39,  1.98s/it]\nSaved image to output/2022-07-03_09-16-16/out_00040.png\n\n\n\n\n 16%|█▌        | 39/250 [00:39<03:28,  1.01it/s]\n19it [00:39,  1.98s/it]\n20it [00:39,  1.98s/it]\n 16%|█▌        | 40/250 [00:39<03:28,  1.01it/s]\n 16%|█▋        | 41/250 [00:40<03:28,  1.00it/s]\n\ni: 42, loss: 0.173457, losses: 0.173457\n\n\n\n 16%|█▋        | 41/250 [00:41<03:28,  1.00it/s]\n20it [00:41,  1.98s/it]\n\n\nSaved image to output/2022-07-03_09-16-18/out_00042.png\n\n\n 16%|█▋        | 41/250 [00:41<03:28,  1.00it/s]\n20it [00:41,  1.98s/it]\n21it [00:41,  2.00s/it]\n 17%|█▋        | 42/250 [00:41<03:29,  1.00s/it]\n 17%|█▋        | 43/250 [00:42<03:25,  1.01it/s]\ni: 44, loss: 0.153406, losses: 0.153406\n\n\n\n\n 17%|█▋        | 43/250 [00:43<03:25,  1.01it/s]\n21it [00:43,  2.00s/it]\nSaved image to output/2022-07-03_09-16-20/out_00044.png\n\n\n\n\n 17%|█▋        | 43/250 [00:43<03:25,  1.01it/s]\n21it [00:43,  2.00s/it]\n22it [00:43,  1.99s/it]\n 18%|█▊        | 44/250 [00:43<03:26,  1.00s/it]\n 18%|█▊        | 45/250 [00:44<03:23,  1.01it/s]\ni: 46, loss: 0.179768, losses: 0.179768\n\n\n\n\n 18%|█▊        | 45/250 [00:45<03:23,  1.01it/s]\n22it [00:45,  1.99s/it]\n\n\nSaved image to output/2022-07-03_09-16-22/out_00046.png\n\n\n 18%|█▊        | 45/250 [00:45<03:23,  1.01it/s]\n22it [00:45,  1.99s/it]\n23it [00:45,  2.00s/it]\n 18%|█▊        | 46/250 [00:45<03:25,  1.01s/it]\n 19%|█▉        | 47/250 [00:46<03:22,  1.00it/s]\ni: 48, loss: 0.157131, losses: 0.157131\n\n\n\n\n 19%|█▉        | 47/250 [00:47<03:22,  1.00it/s]\n23it [00:47,  2.00s/it]\n\n\nSaved image to output/2022-07-03_09-16-24/out_00048.png\n\n\n 19%|█▉        | 47/250 [00:47<03:22,  1.00it/s]\n23it [00:47,  2.00s/it]\n24it [00:47,  2.00s/it]\n 19%|█▉        | 48/250 [00:47<03:23,  1.01s/it]\n 20%|█▉        | 49/250 [00:48<03:20,  1.00it/s]\ni: 50, loss: 0.128689, losses: 0.128689\n\n\n\n\n 20%|█▉        | 49/250 [00:49<03:20,  1.00it/s]\n24it [00:49,  2.00s/it]\n\nSaved image to output/2022-07-03_09-16-26/out_00050.png\n\n\n\n 20%|█▉        | 49/250 [00:49<03:20,  1.00it/s]\n24it [00:49,  2.00s/it]\n25it [00:49,  2.00s/it]\n 20%|██        | 50/250 [00:49<03:20,  1.00s/it]\n 20%|██        | 51/250 [00:50<03:19,  1.00s/it]\n\n\ni: 52, loss: 0.162693, losses: 0.162693\n\n\n 20%|██      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2.00s/it]\n 22%|██▏       | 56/250 [00:55<03:14,  1.00s/it]\n 23%|██▎       | 57/250 [00:56<03:13,  1.00s/it]\ni: 58, loss: 0.127411, losses: 0.127411\n\n\n\n\n 23%|██▎       | 57/250 [00:57<03:13,  1.00s/it]\n28it [00:57,  2.00s/it]\nSaved image to output/2022-07-03_09-16-34/out_00058.png\n\n\n\n\n 23%|██▎       | 57/250 [00:57<03:13,  1.00s/it]\n28it [00:57,  2.00s/it]\n29it [00:57,  2.01s/it]\n 23%|██▎       | 58/250 [00:57<03:14,  1.01s/it]\n 24%|██▎       | 59/250 [00:58<03:11,  1.00s/it]\n\n\n\n\n 24%|██▎       | 59/250 [00:59<03:11,  1.00s/it]\ni: 60, loss: 0.1444, losses: 0.1444\n29it [00:59,  2.01s/it]\n\n\nSaved image to output/2022-07-03_09-16-36/out_00060.png\n\n\n 24%|██▎       | 59/250 [00:59<03:11,  1.00s/it]\n29it [00:59,  2.01s/it]\n30it [00:59,  2.00s/it]\n 24%|██▍       | 60/250 [00:59<03:11,  1.01s/it]\ni: 62, loss: 0.127972, losses: 0.127972\n 24%|██▍       | 61/250 [01:00<03:08,  1.00it/s]\n\n\n\n\n 24%|██▍       | 61/250 [01:01<03:08,  1.00it/s]\n30it [01:01,  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242/250 [04:01<00:07,  1.02it/s]\n 97%|█████████▋| 243/250 [04:02<00:06,  1.02it/s]\n\ni: 244, loss: 0.0820291, losses: 0.0820291\n\n\n\n 97%|█████████▋| 243/250 [04:03<00:06,  1.02it/s]\n121it [04:03,  1.97s/it]\n\nSaved image to output/2022-07-03_09-19-40/out_00244.png\n\n\n\n 97%|█████████▋| 243/250 [04:03<00:06,  1.02it/s]\n121it [04:03,  1.97s/it]\n122it [04:03,  1.98s/it]\n 98%|█████████▊| 244/250 [04:03<00:05,  1.01it/s]\n 98%|█████████▊| 245/250 [04:04<00:04,  1.02it/s]\ni: 246, loss: 0.0640518, losses: 0.0640518\n\n\n\n\n 98%|█████████▊| 245/250 [04:05<00:04,  1.02it/s]\n122it [04:05,  1.98s/it]\nSaved image to output/2022-07-03_09-19-42/out_00246.png\n\n\n\n\n 98%|█████████▊| 245/250 [04:05<00:04,  1.02it/s]\n122it [04:05,  1.98s/it]\n123it [04:05,  1.98s/it]\n 98%|█████████▊| 246/250 [04:05<00:03,  1.01it/s]\n 99%|█████████▉| 247/250 [04:06<00:02,  1.02it/s]\ni: 248, loss: 0.0788548, losses: 0.0788548\n\n\n\n\n 99%|█████████▉| 247/250 [04:07<00:02,  1.02it/s]\n123it [04:07,  1.98s/it]\nSaved image to output/2022-07-03_09-19-44/out_00248.png\n\n\n\n\n 99%|█████████▉| 247/250 [04:07<00:02,  1.02it/s]\n123it [04:07,  1.98s/it]\n124it [04:07,  1.98s/it]\n 99%|█████████▉| 248/250 [04:07<00:01,  1.00it/s]\n100%|█████████▉| 249/250 [04:08<00:00,  1.01it/s]\ni: 250, loss: 0.0746291, losses: 0.0746291\n\n\n\n\n100%|█████████▉| 249/250 [04:09<00:00,  1.01it/s]\n124it [04:09,  1.98s/it]\n\n\n\n\nSaved image to output/2022-07-03_09-19-46/out_00250.png\n100%|█████████▉| 249/250 [04:09<00:00,  1.01it/s]\n124it [04:09,  1.98s/it]\n125it [04:09,  2.00s/it]\n100%|██████████| 250/250 [04:09<00:00,  1.01s/it]\n100%|██████████| 250/250 [04:09<00:00,  1.00it/s]\n\n125it [04:09,  2.00s/it]",
  "metrics": {
    "predict_time": 361.445803,
    "total_time": 361.622316
  },
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    "https://replicate.delivery/mgxm/2c8d49b3-27dc-4834-ac72-2ae27e4467e5/out_00246.png",
    "https://replicate.delivery/mgxm/9761d9fc-4769-4e77-9ff2-b77b2bc211e1/out_00248.png",
    "https://replicate.delivery/mgxm/d28db3ce-eab2-4732-ab0e-49f652875b3f/out_00250.png"
  ],
  "started_at": "2022-07-03T09:13:45.664852Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/h2krdma3yjat3jjtmnfksd3omi",
    "cancel": "https://api.replicate.com/v1/predictions/h2krdma3yjat3jjtmnfksd3omi/cancel"
  },
  "version": "4ed232e4ebe82b3d70ee5e0526257aeeb07187f6727ee617795a7f94d2133e2d"
}

{
  "completed_at": "2022-07-04T05:57:12.129767Z",
  "created_at": "2022-07-04T05:56:21.621981Z",
  "data_removed": false,
  "error": null,
  "id": "cqgrrpo6cjh3vdn7y4ils2xviq",
  "input": {
    "lr": "0.0002",
    "seed": -1,
    "prompt": "An oil painting of mountains, in the style of pixar",
    "lr_decay": 0.995,
    "iterations": "50",
    "num_scales": "6",
    "num_cutouts": "16",
    "offset_type": "none",
    "display_freq": 25,
    "offset_lr_fac": 1,
    "guidance_scale": "2",
    "num_samples_per_batch": "8"
  },
  "logs": "Using cached prior embedding for prompt: An oil painting of mountains, in the style of pixar\nUsing device: cuda\n\nSeed: 27922989\n0it [00:00, ?it/s]\n  0%|          | 0/50 [00:00<?, ?it/s]\n  2%|▏         | 1/50 [00:01<00:51,  1.05s/it]\n  4%|▍         | 2/50 [00:01<00:47,  1.01it/s]\n  6%|▌         | 3/50 [00:02<00:46,  1.02it/s]\n  8%|▊         | 4/50 [00:03<00:45,  1.02it/s]\n 10%|█         | 5/50 [00:04<00:43,  1.03it/s]\n 12%|█▏        | 6/50 [00:05<00:43,  1.02it/s]\n 14%|█▍        | 7/50 [00:06<00:41,  1.03it/s]\n 16%|█▌        | 8/50 [00:07<00:40,  1.03it/s]\n 18%|█▊        | 9/50 [00:08<00:39,  1.03it/s]\n 20%|██        | 10/50 [00:09<00:38,  1.03it/s]\n 22%|██▏       | 11/50 [00:10<00:37,  1.03it/s]\n 24%|██▍       | 12/50 [00:11<00:37,  1.03it/s]\n 26%|██▌       | 13/50 [00:12<00:36,  1.03it/s]\n 28%|██▊       | 14/50 [00:13<00:35,  1.02it/s]\n 30%|███       | 15/50 [00:14<00:34,  1.01it/s]\n 32%|███▏      | 16/50 [00:15<00:33,  1.01it/s]\n 34%|███▍      | 17/50 [00:16<00:32,  1.01it/s]\n 36%|███▌      | 18/50 [00:17<00:31,  1.00it/s]\n 38%|███▊      | 19/50 [00:18<00:31,  1.01s/it]\n 40%|████      | 20/50 [00:19<00:30,  1.01s/it]\n 42%|████▏     | 21/50 [00:20<00:29,  1.02s/it]\n 44%|████▍     | 22/50 [00:21<00:28,  1.02s/it]\n 46%|████▌     | 23/50 [00:22<00:27,  1.02s/it]\n 48%|████▊     | 24/50 [00:23<00:26,  1.02s/it]\n\ni: 25, loss: 0.199801, losses: 0.199801\n\n\n\n 48%|████▊     | 24/50 [00:24<00:26,  1.02s/it]\n0it [00:24, ?it/s]\n\n\n\n\nSaved image to output/2022-07-04_05-56-46/out_00025.png\n 48%|████▊     | 24/50 [00:24<00:26,  1.02s/it]\n0it [00:24, ?it/s]\n1it [00:24, 24.99s/it]\n 50%|█████     | 25/50 [00:24<00:25,  1.03s/it]\n 52%|█████▏    | 26/50 [00:25<00:24,  1.03s/it]\n 54%|█████▍    | 27/50 [00:26<00:23,  1.03s/it]\n 56%|█████▌    | 28/50 [00:27<00:22,  1.02s/it]\n 58%|█████▊    | 29/50 [00:28<00:21,  1.02s/it]\n 60%|██████    | 30/50 [00:29<00:20,  1.01s/it]\n 62%|██████▏   | 31/50 [00:30<00:19,  1.02s/it]\n 64%|██████▍   | 32/50 [00:32<00:18,  1.02s/it]\n 66%|██████▌   | 33/50 [00:33<00:17,  1.01s/it]\n 68%|██████▊   | 34/50 [00:34<00:16,  1.01s/it]\n 70%|███████   | 35/50 [00:35<00:15,  1.01s/it]\n 72%|███████▏  | 36/50 [00:36<00:14,  1.00s/it]\n 74%|███████▍  | 37/50 [00:37<00:12,  1.00it/s]\n 76%|███████▌  | 38/50 [00:38<00:12,  1.00s/it]\n 78%|███████▊  | 39/50 [00:38<00:10,  1.01it/s]\n 80%|████████  | 40/50 [00:39<00:09,  1.00it/s]\n 82%|████████▏ | 41/50 [00:40<00:08,  1.01it/s]\n 84%|████████▍ | 42/50 [00:41<00:07,  1.01it/s]\n 86%|████████▌ | 43/50 [00:42<00:06,  1.01it/s]\n 88%|████████▊ | 44/50 [00:43<00:05,  1.02it/s]\n 90%|█████████ | 45/50 [00:44<00:04,  1.03it/s]\n 92%|█████████▏| 46/50 [00:45<00:03,  1.03it/s]\n 94%|█████████▍| 47/50 [00:46<00:02,  1.03it/s]\n 96%|█████████▌| 48/50 [00:47<00:01,  1.04it/s]\n 98%|█████████▊| 49/50 [00:48<00:00,  1.04it/s]\n\n\ni: 50, loss: 0.107678, losses: 0.107678\n\n\n 98%|█████████▊| 49/50 [00:49<00:00,  1.04it/s]\n1it [00:49, 24.99s/it]\n\n\nSaved image to output/2022-07-04_05-57-11/out_00050.png\n\n\n 98%|█████████▊| 49/50 [00:49<00:00,  1.04it/s]\n1it [00:49, 24.99s/it]\n2it [00:49, 24.90s/it]\n100%|██████████| 50/50 [00:49<00:00,  1.03it/s]\n100%|██████████| 50/50 [00:49<00:00,  1.01it/s]\n\n2it [00:49, 24.91s/it]",
  "metrics": {
    "predict_time": 50.334741,
    "total_time": 50.507786
  },
  "output": [
    "https://replicate.delivery/mgxm/cf32b428-e10f-4a63-8204-79e893b46be8/out_00025.png",
    "https://replicate.delivery/mgxm/c4830ac7-5a9e-456b-9253-814db8bd3a70/out_00050.png"
  ],
  "started_at": "2022-07-04T05:56:21.795026Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/cqgrrpo6cjh3vdn7y4ils2xviq",
    "cancel": "https://api.replicate.com/v1/predictions/cqgrrpo6cjh3vdn7y4ils2xviq/cancel"
  },
  "version": "4ed232e4ebe82b3d70ee5e0526257aeeb07187f6727ee617795a7f94d2133e2d"
}

{
  "completed_at": "2022-07-04T06:07:52.155042Z",
  "created_at": "2022-07-04T06:05:27.197016Z",
  "data_removed": false,
  "error": null,
  "id": "gu27yaikordpbjp3vtwnszrlue",
  "input": {
    "lr": "0.0005",
    "seed": "0",
    "prompt": "An oil painting of person, in the style of pixar",
    "lr_decay": 0.995,
    "iterations": "100",
    "num_scales": "6",
    "num_cutouts": "24",
    "offset_type": "none",
    "display_freq": "5",
    "offset_lr_fac": 1,
    "guidance_scale": "2",
    "num_samples_per_batch": "8"
  },
  "logs": "Using cached prior embedding for prompt: An oil painting of person, in the style of pixar\nUsing device: cuda\n\nSeed: 0\n0it [00:00, ?it/s]\n  0%|          | 0/100 [00:00<?, ?it/s]\n  1%|          | 1/100 [00:01<02:37,  1.59s/it]\n  2%|▏         | 2/100 [00:03<02:26,  1.50s/it]\n  3%|▎         | 3/100 [00:04<02:21,  1.46s/it]\n  4%|▍         | 4/100 [00:06<02:30,  1.57s/it]\n\n\n\n\n  4%|▍         | 4/100 [00:07<02:30,  1.57s/it]\ni: 5, loss: 0.509012, losses: 0.509012\n0it [00:07, ?it/s]\n\nSaved image to output/2022-07-04_06-05-35/out_00005.png\n\n\n\n  4%|▍         | 4/100 [00:07<02:30,  1.57s/it]\n0it [00:07, ?it/s]\n1it [00:07,  7.78s/it]\n  5%|▌         | 5/100 [00:07<02:26,  1.54s/it]\n  6%|▌         | 6/100 [00:09<02:21,  1.50s/it]\n  7%|▋         | 7/100 [00:10<02:17,  1.48s/it]\n  8%|▊         | 8/100 [00:11<02:15,  1.48s/it]\n  9%|▉         | 9/100 [00:13<02:13,  1.47s/it]\n\ni: 10, loss: 0.357501, losses: 0.357501\n\n\n\n  9%|▉         | 9/100 [00:14<02:13,  1.47s/it]\n1it [00:15,  7.78s/it]\nSaved image to output/2022-07-04_06-05-42/out_00010.png\n\n\n\n\n  9%|▉         | 9/100 [00:14<02:13,  1.47s/it]\n1it [00:15,  7.78s/it]\n2it [00:15,  7.49s/it]\n 10%|█         | 10/100 [00:14<02:13,  1.48s/it]\n 11%|█         | 11/100 [00:16<02:11,  1.48s/it]\n 12%|█▏        | 12/100 [00:17<02:09,  1.47s/it]\n 13%|█▎        | 13/100 [00:19<02:08,  1.48s/it]\n 14%|█▍        | 14/100 [00:20<02:06,  1.47s/it]\n\ni: 15, loss: 0.295286, losses: 0.295286\n\n\n\n 14%|█▍        | 14/100 [00:22<02:06,  1.47s/it]\n2it [00:22,  7.49s/it]\nSaved image to output/2022-07-04_06-05-49/out_00015.png\n\n\n\n\n 14%|█▍        | 14/100 [00:22<02:06,  1.47s/it]\n2it [00:22,  7.49s/it]\n3it [00:22,  7.46s/it]\n 15%|█▌        | 15/100 [00:22<02:06,  1.49s/it]\n 16%|█▌        | 16/100 [00:23<02:04,  1.49s/it]\n 17%|█▋        | 17/100 [00:25<02:03,  1.48s/it]\n 18%|█▊        | 18/100 [00:26<02:01,  1.48s/it]\n 19%|█▉        | 19/100 [00:28<02:01,  1.50s/it]\n\n\n\n\ni: 20, loss: 0.187371, losses: 0.187371\n 19%|█▉        | 19/100 [00:29<02:01,  1.50s/it]\n3it [00:29,  7.46s/it]\n\nSaved image to output/2022-07-04_06-05-57/out_00020.png\n\n\n\n 19%|█▉        | 19/100 [00:29<02:01,  1.50s/it]\n3it [00:29,  7.46s/it]\n4it [00:29,  7.44s/it]\n 20%|██        | 20/100 [00:29<01:58,  1.48s/it]\n 21%|██        | 21/100 [00:31<01:56,  1.48s/it]\n 22%|██▏       | 22/100 [00:32<01:54,  1.47s/it]\n 23%|██▎       | 23/100 [00:34<01:52,  1.46s/it]\ni: 25, loss: 0.131395, losses: 0.131395\n 24%|██▍       | 24/100 [00:35<01:50,  1.45s/it]\n\n\n\n\n 24%|██▍       | 24/100 [00:37<01:50,  1.45s/it]\n4it [00:37,  7.44s/it]\nSaved image to output/2022-07-04_06-06-04/out_00025.png\n\n\n\n\n 24%|██▍       | 24/100 [00:37<01:50,  1.45s/it]\n4it [00:37,  7.44s/it]\n5it [00:37,  7.38s/it]\n 25%|██▌       | 25/100 [00:37<01:49,  1.46s/it]\n 26%|██▌       | 26/100 [00:38<01:47,  1.45s/it]\n 27%|██▋       | 27/100 [00:39<01:45,  1.45s/it]\n 28%|██▊       | 28/100 [00:41<01:43,  1.44s/it]\n 29%|██▉       | 29/100 [00:42<01:42,  1.44s/it]\n\ni: 30, loss: 0.116634, losses: 0.116634\n\n\n\n 29%|██▉       | 29/100 [00:44<01:42,  1.44s/it]\n5it [00:44,  7.38s/it]\n\n\n\nSaved image to output/2022-07-04_06-06-11/out_00030.png\n\n 29%|██▉       | 29/100 [00:44<01:42,  1.44s/it]\n5it [00:44,  7.38s/it]\n6it [00:44,  7.31s/it]\n 30%|███       | 30/100 [00:44<01:40,  1.44s/it]\n 31%|███       | 31/100 [00:45<01:38,  1.43s/it]\n 32%|███▏      | 32/100 [00:47<01:36,  1.42s/it]\n 33%|███▎      | 33/100 [00:48<01:35,  1.43s/it]\ni: 35, loss: 0.106386, losses: 0.106386\n 34%|███▍      | 34/100 [00:49<01:33,  1.42s/it]\n\n\n\n\n 34%|███▍      | 34/100 [00:51<01:33,  1.42s/it]\n6it [00:51,  7.31s/it]\n\n\n\n\n 34%|███▍      | 34/100 [00:51<01:33,  1.42s/it]\nSaved image to output/2022-07-04_06-06-18/out_00035.png\n6it [00:51,  7.31s/it]\n7it [00:51,  7.24s/it]\n 35%|███▌      | 35/100 [00:51<01:32,  1.42s/it]\n 36%|███▌      | 36/100 [00:52<01:31,  1.43s/it]\n 37%|███▋      | 37/100 [00:54<01:29,  1.42s/it]\n 38%|███▊      | 38/100 [00:55<01:27,  1.41s/it]\n 39%|███▉      | 39/100 [00:57<01:27,  1.43s/it]\n\n\ni: 40, loss: 0.0943774, losses: 0.0943774\n\n\n 39%|███▉      | 39/100 [00:58<01:27,  1.43s/it]\n7it [00:58,  7.24s/it]\nSaved image to output/2022-07-04_06-06-25/out_00040.png\n\n\n\n\n 39%|███▉      | 39/100 [00:58<01:27,  1.43s/it]\n7it [00:58,  7.24s/it]\n8it [00:58,  7.22s/it]\n 40%|████      | 40/100 [00:58<01:26,  1.44s/it]\n 41%|████      | 41/100 [00:59<01:24,  1.43s/it]\n 42%|████▏     | 42/100 [01:01<01:22,  1.43s/it]\n 43%|████▎     | 43/100 [01:02<01:21,  1.42s/it]\n 44%|████▍     | 44/100 [01:04<01:19,  1.42s/it]\ni: 45, loss: 0.0881185, losses: 0.0881185\n\n\n\n\n 44%|████▍     | 44/100 [01:05<01:19,  1.42s/it]\n8it [01:05,  7.22s/it]\nSaved image to output/2022-07-04_06-06-33/out_00045.png\n\n\n\n\n 44%|████▍     | 44/100 [01:05<01:19,  1.42s/it]\n8it [01:05,  7.22s/it]\n9it [01:05,  7.20s/it]\n 45%|████▌     | 45/100 [01:05<01:19,  1.44s/it]\n 46%|████▌     | 46/100 [01:07<01:17,  1.44s/it]\n 47%|████▋     | 47/100 [01:08<01:15,  1.42s/it]\n 48%|████▊     | 48/100 [01:09<01:13,  1.42s/it]\ni: 50, loss: 0.0892947, losses: 0.0892947\n 49%|████▉     | 49/100 [01:11<01:12,  1.42s/it]\n\n\n\n\n 49%|████▉     | 49/100 [01:12<01:12,  1.42s/it]\n9it [01:12,  7.20s/it]\nSaved image to output/2022-07-04_06-06-40/out_00050.png\n\n\n\n\n 49%|████▉     | 49/100 [01:12<01:12,  1.42s/it]\n9it [01:12,  7.20s/it]\n10it [01:12,  7.16s/it]\n 50%|█████     | 50/100 [01:12<01:11,  1.42s/it]\n 51%|█████     | 51/100 [01:14<01:09,  1.42s/it]\n 52%|█████▏    | 52/100 [01:15<01:08,  1.43s/it]\n 53%|█████▎    | 53/100 [01:16<01:06,  1.41s/it]\n 54%|█████▍    | 54/100 [01:18<01:04,  1.40s/it]\ni: 55, loss: 0.0873839, losses: 0.0873839\n\n\n\n\n 54%|█████▍    | 54/100 [01:19<01:04,  1.40s/it]\n10it [01:19,  7.16s/it]\nSaved image to output/2022-07-04_06-06-47/out_00055.png\n\n\n\n\n 54%|█████▍    | 54/100 [01:19<01:04,  1.40s/it]\n10it [01:19,  7.16s/it]\n11it [01:19,  7.14s/it]\n 55%|█████▌    | 55/100 [01:19<01:04,  1.43s/it]\n 56%|█████▌    | 56/100 [01:21<01:03,  1.43s/it]\n 57%|█████▋    | 57/100 [01:22<01:01,  1.43s/it]\n 58%|█████▊    | 58/100 [01:24<01:00,  1.44s/it]\n 59%|█████▉    | 59/100 [01:25<00:59,  1.44s/it]\n\n\ni: 60, loss: 0.0746877, losses: 0.0746877\n\n\n 59%|█████▉    | 59/100 [01:27<00:59,  1.44s/it]\n11it [01:27,  7.14s/it]\n\nSaved image to output/2022-07-04_06-06-54/out_00060.png\n\n\n\n 59%|█████▉    | 59/100 [01:27<00:59,  1.44s/it]\n11it [01:27,  7.14s/it]\n12it [01:27,  7.17s/it]\n 60%|██████    | 60/100 [01:27<00:57,  1.44s/it]\n 61%|██████    | 61/100 [01:28<00:56,  1.44s/it]\n 62%|██████▏   | 62/100 [01:29<00:54,  1.43s/it]\n 63%|██████▎   | 63/100 [01:31<00:52,  1.43s/it]\n 64%|██████▍   | 64/100 [01:32<00:51,  1.43s/it]\n\n\n\n\n 64%|██████▍   | 64/100 [01:34<00:51,  1.43s/it]\ni: 65, loss: 0.0764417, losses: 0.0764417\n12it [01:34,  7.17s/it]\n\n\nSaved image to output/2022-07-04_06-07-01/out_00065.png\n\n\n 64%|██████▍   | 64/100 [01:34<00:51,  1.43s/it]\n12it [01:34,  7.17s/it]\n13it [01:34,  7.16s/it]\n 65%|██████▌   | 65/100 [01:34<00:50,  1.44s/it]\n 66%|██████▌   | 66/100 [01:35<00:48,  1.44s/it]\n 67%|██████▋   | 67/100 [01:37<00:46,  1.42s/it]\n 68%|██████▊   | 68/100 [01:38<00:45,  1.42s/it]\ni: 70, loss: 0.0734245, losses: 0.0734245\n 69%|██████▉   | 69/100 [01:39<00:43,  1.42s/it]\n\n\n\n\n 69%|██████▉   | 69/100 [01:41<00:43,  1.42s/it]\nSaved image to output/2022-07-04_06-07-08/out_00070.png\n13it [01:41,  7.16s/it]\n\n\n\n\n 69%|██████▉   | 69/100 [01:41<00:43,  1.42s/it]\n13it [01:41,  7.16s/it]\n14it [01:41,  7.14s/it]\n 70%|███████   | 70/100 [01:41<00:42,  1.43s/it]\n 71%|███████   | 71/100 [01:42<00:41,  1.42s/it]\n 72%|███████▏  | 72/100 [01:44<00:39,  1.42s/it]\n 73%|███████▎  | 73/100 [01:45<00:38,  1.42s/it]\n 74%|███████▍  | 74/100 [01:46<00:37,  1.43s/it]\n\ni: 75, loss: 0.0699265, losses: 0.0699265\n\n\n\n 74%|███████▍  | 74/100 [01:48<00:37,  1.43s/it]\n14it [01:48,  7.14s/it]\n\n\nSaved image to output/2022-07-04_06-07-15/out_00075.png\n\n\n 74%|███████▍  | 74/100 [01:48<00:37,  1.43s/it]\n14it [01:48,  7.14s/it]\n15it [01:48,  7.16s/it]\n 75%|███████▌  | 75/100 [01:48<00:36,  1.45s/it]\n 76%|███████▌  | 76/100 [01:49<00:34,  1.44s/it]\n 77%|███████▋  | 77/100 [01:51<00:32,  1.43s/it]\n 78%|███████▊  | 78/100 [01:52<00:31,  1.43s/it]\n 79%|███████▉  | 79/100 [01:54<00:29,  1.42s/it]\ni: 80, loss: 0.0725935, losses: 0.0725935\n\n\n\n\n 79%|███████▉  | 79/100 [01:55<00:29,  1.42s/it]\n15it [01:55,  7.16s/it]\nSaved image to output/2022-07-04_06-07-23/out_00080.png\n\n\n\n\n 79%|███████▉  | 79/100 [01:55<00:29,  1.42s/it]\n15it [01:55,  7.16s/it]\n16it [01:55,  7.15s/it]\n 80%|████████  | 80/100 [01:55<00:28,  1.44s/it]\n 81%|████████  | 81/100 [01:57<00:27,  1.44s/it]\n 82%|████████▏ | 82/100 [01:58<00:25,  1.43s/it]\n 83%|████████▎ | 83/100 [01:59<00:24,  1.43s/it]\ni: 85, loss: 0.0636112, losses: 0.0636112\n 84%|████████▍ | 84/100 [02:01<00:22,  1.43s/it]\n\n\n\n\n 84%|████████▍ | 84/100 [02:02<00:22,  1.43s/it]\n16it [02:02,  7.15s/it]\n\n\nSaved image to output/2022-07-04_06-07-30/out_00085.png\n\n\n 84%|████████▍ | 84/100 [02:02<00:22,  1.43s/it]\n16it [02:02,  7.15s/it]\n17it [02:02,  7.16s/it]\n 85%|████████▌ | 85/100 [02:02<00:21,  1.44s/it]\n 86%|████████▌ | 86/100 [02:04<00:19,  1.43s/it]\n 87%|████████▋ | 87/100 [02:05<00:18,  1.42s/it]\n 88%|████████▊ | 88/100 [02:07<00:17,  1.42s/it]\n 89%|████████▉ | 89/100 [02:08<00:15,  1.41s/it]\n\ni: 90, loss: 0.0665739, losses: 0.0665739\n\n\n\n 89%|████████▉ | 89/100 [02:09<00:15,  1.41s/it]\nSaved image to output/2022-07-04_06-07-37/out_00090.png\n17it [02:09,  7.16s/it]\n\n\n\n\n 89%|████████▉ | 89/100 [02:09<00:15,  1.41s/it]\n17it [02:09,  7.16s/it]\n18it [02:09,  7.12s/it]\n 90%|█████████ | 90/100 [02:09<00:14,  1.42s/it]\n 91%|█████████ | 91/100 [02:11<00:12,  1.41s/it]\n 92%|█████████▏| 92/100 [02:12<00:11,  1.40s/it]\n 93%|█████████▎| 93/100 [02:14<00:09,  1.41s/it]\ni: 95, loss: 0.0629401, losses: 0.0629401\n 94%|█████████▍| 94/100 [02:15<00:08,  1.42s/it]\n\n\n\n\n 94%|█████████▍| 94/100 [02:16<00:08,  1.42s/it]\n18it [02:17,  7.12s/it]\n\nSaved image to output/2022-07-04_06-07-44/out_00095.png\n\n\n\n 94%|█████████▍| 94/100 [02:16<00:08,  1.42s/it]\n18it [02:17,  7.12s/it]\n19it [02:17,  7.13s/it]\n 95%|█████████▌| 95/100 [02:16<00:07,  1.43s/it]\n 96%|█████████▌| 96/100 [02:18<00:05,  1.44s/it]\n 97%|█████████▋| 97/100 [02:19<00:04,  1.43s/it]\n 98%|█████████▊| 98/100 [02:21<00:02,  1.43s/it]\n 99%|█████████▉| 99/100 [02:22<00:01,  1.42s/it]\n\n\ni: 100, loss: 0.0603441, losses: 0.0603441\n\n\n 99%|█████████▉| 99/100 [02:24<00:01,  1.42s/it]\n19it [02:24,  7.13s/it]\n\n\n\n\n 99%|█████████▉| 99/100 [02:24<00:01,  1.42s/it]\nSaved image to output/2022-07-04_06-07-51/out_00100.png\n19it [02:24,  7.13s/it]\n20it [02:24,  7.12s/it]\n100%|██████████| 100/100 [02:24<00:00,  1.42s/it]\n100%|██████████| 100/100 [02:24<00:00,  1.44s/it]\n\n20it [02:24,  7.21s/it]",
  "metrics": {
    "predict_time": 144.772309,
    "total_time": 144.958026
  },
  "output": [
    "https://replicate.delivery/mgxm/e63edd88-d094-4760-a472-f693f761c62d/out_00005.png",
    "https://replicate.delivery/mgxm/1a2dc19f-fd3a-4921-b2ee-a9eaafc18666/out_00010.png",
    "https://replicate.delivery/mgxm/8f517ed1-ef92-4ea2-a11b-fc77c3e45fa0/out_00015.png",
    "https://replicate.delivery/mgxm/05da3fbb-c2d3-45ad-9d77-99acaaca93f3/out_00020.png",
    "https://replicate.delivery/mgxm/b2948818-1c69-4ac9-a975-b7b4631b177e/out_00025.png",
    "https://replicate.delivery/mgxm/2d673968-9ba9-4ecd-b4cd-07463d619d0f/out_00030.png",
    "https://replicate.delivery/mgxm/3b353b67-90d3-46c1-bd2f-0888e81da27b/out_00035.png",
    "https://replicate.delivery/mgxm/6a8b5fe0-70ec-4d30-80ec-ffc151bef919/out_00040.png",
    "https://replicate.delivery/mgxm/caa8414f-5758-4075-b941-a0df7709b9de/out_00045.png",
    "https://replicate.delivery/mgxm/7cc56bed-a5be-48f4-8524-48ac8b1d6449/out_00050.png",
    "https://replicate.delivery/mgxm/edf31c0c-963f-42b8-81b6-9855eb8ea085/out_00055.png",
    "https://replicate.delivery/mgxm/7142ddd9-e0b8-41b5-b060-670c6d0b73ff/out_00060.png",
    "https://replicate.delivery/mgxm/1938b904-63ad-4c2d-a740-72b4f0674ded/out_00065.png",
    "https://replicate.delivery/mgxm/7606301f-31c7-44b3-9933-4ad8e8ad75e1/out_00070.png",
    "https://replicate.delivery/mgxm/948cbfcb-0e31-40db-945f-8e83237b0865/out_00075.png",
    "https://replicate.delivery/mgxm/1f3eb8b3-7ec8-421d-8d14-56b81b090ef8/out_00080.png",
    "https://replicate.delivery/mgxm/e63bc9d5-f2cd-4ed4-a457-8ffe82f170c1/out_00085.png",
    "https://replicate.delivery/mgxm/74d72536-057b-4f8b-92f7-5c30f9d35509/out_00090.png",
    "https://replicate.delivery/mgxm/3ca73bf6-5685-4f81-a440-197d211b7a8b/out_00095.png",
    "https://replicate.delivery/mgxm/aec05fc9-7dd3-4eb2-a2d4-3aaf0438d886/out_00100.png"
  ],
  "started_at": "2022-07-04T06:05:27.382733Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/gu27yaikordpbjp3vtwnszrlue",
    "cancel": "https://api.replicate.com/v1/predictions/gu27yaikordpbjp3vtwnszrlue/cancel"
  },
  "version": "4ed232e4ebe82b3d70ee5e0526257aeeb07187f6727ee617795a7f94d2133e2d"
}

{
  "completed_at": "2022-07-04T06:20:46.715950Z",
  "created_at": "2022-07-04T06:16:26.542306Z",
  "data_removed": false,
  "error": null,
  "id": "vo4p6ishmvgexjbupqejzn5raq",
  "input": {
    "lr": "0.0005",
    "seed": "0",
    "prompt": "high detailed reflection",
    "lr_decay": 0.995,
    "iterations": "100",
    "num_scales": "6",
    "num_cutouts": "24",
    "offset_type": "none",
    "display_freq": "5",
    "offset_lr_fac": 1,
    "guidance_scale": "2",
    "num_samples_per_batch": "8"
  },
  "logs": "Initializing deep image prior net...\n\nsampling loop time step:   0%|          | 0/1000 [00:00<?, ?it/s]\nsampling loop time step:   0%|          | 1/1000 [00:00<02:07,  7.85it/s]\nsampling loop time step:   0%|          | 2/1000 [00:00<02:19,  7.14it/s]\nsampling loop time step:   0%|          | 3/1000 [00:00<02:07,  7.79it/s]\nsampling loop time step:   0%|          | 4/1000 [00:00<02:02,  8.12it/s]\nsampling loop time step:   0%|          | 5/1000 [00:00<01:59,  8.33it/s]\nsampling loop time step:   1%|          | 6/1000 [00:00<01:57,  8.47it/s]\nsampling loop time step:   1%|          | 7/1000 [00:00<01:56,  8.54it/s]\nsampling loop time step:   1%|          | 8/1000 [00:00<01:55,  8.56it/s]\nsampling loop time step:   1%|          | 9/1000 [00:01<01:55,  8.58it/s]\nsampling loop time step:   1%|          | 10/1000 [00:01<01:57,  8.45it/s]\nsampling loop time step:   1%|          | 11/1000 [00:01<01:56,  8.46it/s]\nsampling loop time step:   1%|          | 12/1000 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1000/1000 [01:56<00:00,  8.60it/s]\n\nUsing device: cuda\nSeed: 0\n0it [00:00, ?it/s]\n  0%|          | 0/100 [00:00<?, ?it/s]\n  1%|          | 1/100 [00:01<02:25,  1.46s/it]\n  2%|▏         | 2/100 [00:02<02:21,  1.44s/it]\n  3%|▎         | 3/100 [00:04<02:18,  1.43s/it]\n  4%|▍         | 4/100 [00:05<02:17,  1.43s/it]\ni: 5, loss: 0.462603, losses: 0.462603\n\n\n\n\n  4%|▍         | 4/100 [00:07<02:17,  1.43s/it]\n0it [00:07, ?it/s]\nSaved image to output/2022-07-04_06-18-30/out_00005.png\n\n\n\n\n  4%|▍         | 4/100 [00:07<02:17,  1.43s/it]\n0it [00:07, ?it/s]\n1it [00:07,  7.31s/it]\n  5%|▌         | 5/100 [00:07<02:17,  1.45s/it]\n  6%|▌         | 6/100 [00:08<02:14,  1.43s/it]\n  7%|▋         | 7/100 [00:10<02:12,  1.43s/it]\n  8%|▊         | 8/100 [00:11<02:11,  1.43s/it]\n  9%|▉         | 9/100 [00:12<02:09,  1.42s/it]\n\n\n\n\ni: 10, loss: 0.377833, losses: 0.377833\n  9%|▉         | 9/100 [00:14<02:09,  1.42s/it]\n1it [00:14,  7.31s/it]\n\n\nSaved image to output/2022-07-04_06-18-37/out_00010.png\n\n\n  9%|▉         | 9/100 [00:14<02:09,  1.42s/it]\n1it [00:14,  7.31s/it]\n2it [00:14,  7.20s/it]\n 10%|█         | 10/100 [00:14<02:09,  1.44s/it]\n 11%|█         | 11/100 [00:15<02:07,  1.44s/it]\n 12%|█▏        | 12/100 [00:17<02:06,  1.43s/it]\n 13%|█▎        | 13/100 [00:18<02:05,  1.44s/it]\n 14%|█▍        | 14/100 [00:20<02:02,  1.43s/it]\n\n\ni: 15, loss: 0.323415, losses: 0.323415\n\n\n 14%|█▍        | 14/100 [00:21<02:02,  1.43s/it]\n2it [00:21,  7.20s/it]\n\n\nSaved image to output/2022-07-04_06-18-44/out_00015.png\n\n\n 14%|█▍        | 14/100 [00:21<02:02,  1.43s/it]\n2it [00:21,  7.20s/it]\n3it [00:21,  7.20s/it]\n 15%|█▌        | 15/100 [00:21<02:02,  1.44s/it]\n 16%|█▌        | 16/100 [00:22<02:01,  1.44s/it]\n 17%|█▋        | 17/100 [00:24<01:59,  1.44s/it]\n 18%|█▊        | 18/100 [00:25<01:58,  1.44s/it]\n 19%|█▉        | 19/100 [00:27<01:57,  1.45s/it]\n\n\ni: 20, loss: 0.273566, losses: 0.273566\n\n\n 19%|█▉        | 19/100 [00:28<01:57,  1.45s/it]\n3it [00:28,  7.20s/it]\n\n\nSaved image to output/2022-07-04_06-18-51/out_00020.png\n\n\n 19%|█▉        | 19/100 [00:28<01:57,  1.45s/it]\n3it [00:28,  7.20s/it]\n4it [00:28,  7.20s/it]\n 20%|██        | 20/100 [00:28<01:54,  1.44s/it]\n 21%|██        | 21/100 [00:30<01:53,  1.44s/it]\n 22%|██▏       | 22/100 [00:31<01:52,  1.44s/it]\n 23%|██▎       | 23/100 [00:33<01:50,  1.44s/it]\ni: 25, loss: 0.229316, losses: 0.229316\n 24%|██▍       | 24/100 [00:34<01:48,  1.43s/it]\n\n\n\n\n 24%|██▍       | 24/100 [00:35<01:48,  1.43s/it]\n4it [00:35,  7.20s/it]\n\n\nSaved image to output/2022-07-04_06-18-58/out_00025.png\n\n\n 24%|██▍       | 24/100 [00:35<01:48,  1.43s/it]\n4it [00:36,  7.20s/it]\n5it [00:36,  7.19s/it]\n 25%|██▌       | 25/100 [00:35<01:47,  1.44s/it]\n 26%|██▌       | 26/100 [00:37<01:45,  1.43s/it]\n 27%|██▋       | 27/100 [00:38<01:44,  1.43s/it]\n 28%|██▊       | 28/100 [00:40<01:43,  1.44s/it]\ni: 30, loss: 0.221481, losses: 0.221481\n 29%|██▉       | 29/100 [00:41<01:41,  1.43s/it]\n\n\n\n\n 29%|██▉       | 29/100 [00:43<01:41,  1.43s/it]\n5it [00:43,  7.19s/it]\n\n\nSaved image to output/2022-07-04_06-19-06/out_00030.png\n\n\n 29%|██▉       | 29/100 [00:43<01:41,  1.43s/it]\n5it [00:43,  7.19s/it]\n6it [00:43,  7.19s/it]\n 30%|███       | 30/100 [00:43<01:40,  1.44s/it]\n 31%|███       | 31/100 [00:44<01:38,  1.43s/it]\n 32%|███▏      | 32/100 [00:45<01:36,  1.42s/it]\n 33%|███▎      | 33/100 [00:47<01:36,  1.44s/it]\n 34%|███▍      | 34/100 [00:48<01:34,  1.43s/it]\ni: 35, loss: 0.176472, losses: 0.176472\n\n\n\n\n 34%|███▍      | 34/100 [00:50<01:34,  1.43s/it]\n6it [00:50,  7.19s/it]\n\n\nSaved image to output/2022-07-04_06-19-13/out_00035.png\n\n\n 34%|███▍      | 34/100 [00:50<01:34,  1.43s/it]\n6it [00:50,  7.19s/it]\n7it [00:50,  7.17s/it]\n 35%|███▌      | 35/100 [00:50<01:32,  1.43s/it]\n 36%|███▌      | 36/100 [00:51<01:32,  1.44s/it]\n 37%|███▋      | 37/100 [00:53<01:29,  1.43s/it]\n 38%|███▊      | 38/100 [00:54<01:28,  1.42s/it]\n 39%|███▉      | 39/100 [00:55<01:27,  1.44s/it]\ni: 40, loss: 0.135095, losses: 0.135095\n\n\n\n\n 39%|███▉      | 39/100 [00:57<01:27,  1.44s/it]\nSaved image to output/2022-07-04_06-19-20/out_00040.png\n7it [00:57,  7.17s/it]\n\n\n\n\n 39%|███▉      | 39/100 [00:57<01:27,  1.44s/it]\n7it [00:57,  7.17s/it]\n8it [00:57,  7.18s/it]\n 40%|████      | 40/100 [00:57<01:26,  1.44s/it]\n 41%|████      | 41/100 [00:58<01:24,  1.43s/it]\n 42%|████▏     | 42/100 [01:00<01:23,  1.43s/it]\n 43%|████▎     | 43/100 [01:01<01:21,  1.43s/it]\n 44%|████▍     | 44/100 [01:03<01:20,  1.43s/it]\n\n\ni: 45, loss: 0.121896, losses: 0.121896\n\n\n 44%|████▍     | 44/100 [01:04<01:20,  1.43s/it]\n8it [01:04,  7.18s/it]\n\n\nSaved image to output/2022-07-04_06-19-27/out_00045.png\n\n\n 44%|████▍     | 44/100 [01:04<01:20,  1.43s/it]\n8it [01:04,  7.18s/it]\n9it [01:04,  7.18s/it]\n 45%|████▌     | 45/100 [01:04<01:19,  1.45s/it]\n 46%|████▌     | 46/100 [01:06<01:18,  1.45s/it]\n 47%|████▋     | 47/100 [01:07<01:15,  1.43s/it]\n 48%|████▊     | 48/100 [01:08<01:14,  1.43s/it]\n 49%|████▉     | 49/100 [01:10<01:13,  1.43s/it]\n\n\ni: 50, loss: 0.115956, losses: 0.115956\n\n\n 49%|████▉     | 49/100 [01:11<01:13,  1.43s/it]\n9it [01:11,  7.18s/it]\n\n\nSaved image to output/2022-07-04_06-19-34/out_00050.png\n\n\n 49%|████▉     | 49/100 [01:11<01:13,  1.43s/it]\n9it [01:11,  7.18s/it]\n10it [01:11,  7.17s/it]\n 50%|█████     | 50/100 [01:11<01:11,  1.43s/it]\n 51%|█████     | 51/100 [01:13<01:10,  1.43s/it]\n 52%|█████▏    | 52/100 [01:14<01:09,  1.44s/it]\n 53%|█████▎    | 53/100 [01:16<01:06,  1.42s/it]\ni: 55, loss: 0.133111, losses: 0.133111\n 54%|█████▍    | 54/100 [01:17<01:04,  1.41s/it]\n\n\n\n\n 54%|█████▍    | 54/100 [01:18<01:04,  1.41s/it]\nSaved image to output/2022-07-04_06-19-41/out_00055.png\n10it [01:18,  7.17s/it]\n\n\n\n\n 54%|█████▍    | 54/100 [01:18<01:04,  1.41s/it]\n10it [01:18,  7.17s/it]\n11it [01:18,  7.16s/it]\n 55%|█████▌    | 55/100 [01:18<01:04,  1.43s/it]\n 56%|█████▌    | 56/100 [01:20<01:03,  1.44s/it]\n 57%|█████▋    | 57/100 [01:21<01:01,  1.44s/it]\n 58%|█████▊    | 58/100 [01:23<01:00,  1.44s/it]\ni: 60, loss: 0.0913672, losses: 0.0913672\n 59%|█████▉    | 59/100 [01:24<00:59,  1.45s/it]\n\n\n\n\n 59%|█████▉    | 59/100 [01:26<00:59,  1.45s/it]\n11it [01:26,  7.16s/it]\n\nSaved image to output/2022-07-04_06-19-49/out_00060.png\n\n\n\n 59%|█████▉    | 59/100 [01:26<00:59,  1.45s/it]\n11it [01:26,  7.16s/it]\n12it [01:26,  7.18s/it]\n 60%|██████    | 60/100 [01:26<00:57,  1.44s/it]\n 61%|██████    | 61/100 [01:27<00:55,  1.43s/it]\n 62%|██████▏   | 62/100 [01:28<00:54,  1.43s/it]\n 63%|██████▎   | 63/100 [01:30<00:52,  1.43s/it]\n 64%|██████▍   | 64/100 [01:31<00:51,  1.43s/it]\ni: 65, loss: 0.0970285, losses: 0.0970285\n\n\n\n\n 64%|██████▍   | 64/100 [01:33<00:51,  1.43s/it]\nSaved image to output/2022-07-04_06-19-56/out_00065.png\n12it [01:33,  7.18s/it]\n\n\n\n\n 64%|██████▍   | 64/100 [01:33<00:51,  1.43s/it]\n12it [01:33,  7.18s/it]\n13it [01:33,  7.17s/it]\n 65%|██████▌   | 65/100 [01:33<00:50,  1.43s/it]\n 66%|██████▌   | 66/100 [01:34<00:48,  1.43s/it]\n 67%|██████▋   | 67/100 [01:36<00:46,  1.42s/it]\n 68%|██████▊   | 68/100 [01:37<00:45,  1.41s/it]\n 69%|██████▉   | 69/100 [01:38<00:43,  1.41s/it]\ni: 70, loss: 0.0844536, losses: 0.0844536\n\n\n\n\n 69%|██████▉   | 69/100 [01:40<00:43,  1.41s/it]\n13it [01:40,  7.17s/it]\n\nSaved image to output/2022-07-04_06-20-03/out_00070.png\n\n\n\n 69%|██████▉   | 69/100 [01:40<00:43,  1.41s/it]\n13it [01:40,  7.17s/it]\n14it [01:40,  7.13s/it]\n 70%|███████   | 70/100 [01:40<00:42,  1.42s/it]\n 71%|███████   | 71/100 [01:41<00:41,  1.42s/it]\n 72%|███████▏  | 72/100 [01:43<00:39,  1.42s/it]\n 73%|███████▎  | 73/100 [01:44<00:38,  1.41s/it]\n 74%|███████▍  | 74/100 [01:45<00:36,  1.42s/it]\ni: 75, loss: 0.0827625, losses: 0.0827625\n\n\n\n\n 74%|███████▍  | 74/100 [01:47<00:36,  1.42s/it]\n14it [01:47,  7.13s/it]\nSaved image to output/2022-07-04_06-20-10/out_00075.png\n\n\n\n\n 74%|███████▍  | 74/100 [01:47<00:36,  1.42s/it]\n14it [01:47,  7.13s/it]\n15it [01:47,  7.15s/it]\n 75%|███████▌  | 75/100 [01:47<00:36,  1.44s/it]\n 76%|███████▌  | 76/100 [01:48<00:34,  1.44s/it]\n 77%|███████▋  | 77/100 [01:50<00:32,  1.42s/it]\n 78%|███████▊  | 78/100 [01:51<00:31,  1.42s/it]\n 79%|███████▉  | 79/100 [01:53<00:29,  1.42s/it]\n\n\ni: 80, loss: 0.0900782, losses: 0.0900782\n\n\n 79%|███████▉  | 79/100 [01:54<00:29,  1.42s/it]\nSaved image to output/2022-07-04_06-20-17/out_00080.png\n15it [01:54,  7.15s/it]\n\n\n\n\n 79%|███████▉  | 79/100 [01:54<00:29,  1.42s/it]\n15it [01:54,  7.15s/it]\n16it [01:54,  7.13s/it]\n 80%|████████  | 80/100 [01:54<00:28,  1.43s/it]\n 81%|████████  | 81/100 [01:56<00:27,  1.44s/it]\n 82%|████████▏ | 82/100 [01:57<00:25,  1.43s/it]\n 83%|████████▎ | 83/100 [01:58<00:24,  1.43s/it]\n 84%|████████▍ | 84/100 [02:00<00:22,  1.43s/it]\n\n\ni: 85, loss: 0.0749083, losses: 0.0749083\n\n\n 84%|████████▍ | 84/100 [02:01<00:22,  1.43s/it]\n16it [02:01,  7.13s/it]\nSaved image to output/2022-07-04_06-20-24/out_00085.png\n\n\n\n\n 84%|████████▍ | 84/100 [02:01<00:22,  1.43s/it]\n16it [02:01,  7.13s/it]\n17it [02:01,  7.15s/it]\n 85%|████████▌ | 85/100 [02:01<00:21,  1.44s/it]\n 86%|████████▌ | 86/100 [02:03<00:19,  1.43s/it]\n 87%|████████▋ | 87/100 [02:04<00:18,  1.42s/it]\n 88%|████████▊ | 88/100 [02:06<00:17,  1.42s/it]\n 89%|████████▉ | 89/100 [02:07<00:15,  1.42s/it]\ni: 90, loss: 0.081218, losses: 0.081218\n\n\n\n\n 89%|████████▉ | 89/100 [02:08<00:15,  1.42s/it]\n17it [02:08,  7.15s/it]\n\n\nSaved image to output/2022-07-04_06-20-31/out_00090.png\n\n\n 89%|████████▉ | 89/100 [02:08<00:15,  1.42s/it]\n17it [02:08,  7.15s/it]\n18it [02:08,  7.12s/it]\n 90%|█████████ | 90/100 [02:08<00:14,  1.42s/it]\n 91%|█████████ | 91/100 [02:10<00:12,  1.42s/it]\n 92%|█████████▏| 92/100 [02:11<00:11,  1.41s/it]\n 93%|█████████▎| 93/100 [02:13<00:09,  1.42s/it]\n 94%|█████████▍| 94/100 [02:14<00:08,  1.43s/it]\n\n\ni: 95, loss: 0.0809722, losses: 0.0809722\n\n\n 94%|█████████▍| 94/100 [02:15<00:08,  1.43s/it]\n18it [02:16,  7.12s/it]\n\n\nSaved image to output/2022-07-04_06-20-39/out_00095.png\n\n\n 94%|█████████▍| 94/100 [02:15<00:08,  1.43s/it]\n18it [02:16,  7.12s/it]\n19it [02:16,  7.13s/it]\n 95%|█████████▌| 95/100 [02:15<00:07,  1.43s/it]\n 96%|█████████▌| 96/100 [02:17<00:05,  1.43s/it]\n 97%|█████████▋| 97/100 [02:18<00:04,  1.43s/it]\n 98%|█████████▊| 98/100 [02:20<00:02,  1.43s/it]\n 99%|█████████▉| 99/100 [02:21<00:01,  1.42s/it]\n\n\ni: 100, loss: 0.0698686, losses: 0.0698686\n\n\n 99%|█████████▉| 99/100 [02:23<00:01,  1.42s/it]\n19it [02:23,  7.13s/it]\n\nSaved image to output/2022-07-04_06-20-46/out_00100.png\n\n\n\n 99%|█████████▉| 99/100 [02:23<00:01,  1.42s/it]\n19it [02:23,  7.13s/it]\n20it [02:23,  7.12s/it]\n100%|██████████| 100/100 [02:23<00:00,  1.42s/it]\n100%|██████████| 100/100 [02:23<00:00,  1.43s/it]\n\n20it [02:23,  7.16s/it]",
  "metrics": {
    "predict_time": 259.994854,
    "total_time": 260.173644
  },
  "output": [
    "https://replicate.delivery/mgxm/abd85cd1-461c-4332-8384-ea124db19fca/out_00005.png",
    "https://replicate.delivery/mgxm/c9118bc7-defc-498d-a9b8-ac434652fcbb/out_00010.png",
    "https://replicate.delivery/mgxm/2c2792bf-5514-47c7-aae4-d3505f897701/out_00015.png",
    "https://replicate.delivery/mgxm/39624f08-f241-4e9c-a6ff-54798beb22ef/out_00020.png",
    "https://replicate.delivery/mgxm/6017d6df-a744-4f4a-b476-e9d9d4c661f5/out_00025.png",
    "https://replicate.delivery/mgxm/45b831ab-5b34-4ddf-8e19-b9cada4cd3b9/out_00030.png",
    "https://replicate.delivery/mgxm/24046dde-687f-480e-8275-68ea1619b9aa/out_00035.png",
    "https://replicate.delivery/mgxm/07048943-9688-4987-9644-0ff248e70ba3/out_00040.png",
    "https://replicate.delivery/mgxm/4070127f-74cb-488a-a291-4e2460abe86d/out_00045.png",
    "https://replicate.delivery/mgxm/520781b8-a47d-4e92-a664-4e9648643714/out_00050.png",
    "https://replicate.delivery/mgxm/86b08c8f-dc77-4206-98df-0a9bc1b00aac/out_00055.png",
    "https://replicate.delivery/mgxm/d3d15815-e1a2-40e7-ae7f-d8831f404da7/out_00060.png",
    "https://replicate.delivery/mgxm/701bb34f-2a43-47a0-8a4f-b86e0dc38b31/out_00065.png",
    "https://replicate.delivery/mgxm/348eb9c0-ce4b-4cef-95c4-3a0196b7e7fa/out_00070.png",
    "https://replicate.delivery/mgxm/8a508539-4317-461b-8427-0d3ace19236e/out_00075.png",
    "https://replicate.delivery/mgxm/a3ba242d-72fa-4cc7-86a0-1f04a2c9c59f/out_00080.png",
    "https://replicate.delivery/mgxm/81de42b5-7d50-4a8c-a524-5226f92735ac/out_00085.png",
    "https://replicate.delivery/mgxm/716a14d0-2200-45a5-b4ed-14555466d890/out_00090.png",
    "https://replicate.delivery/mgxm/7cd761a9-6169-44e0-92ab-df9224b62c0d/out_00095.png",
    "https://replicate.delivery/mgxm/7e096b5d-6f6f-40db-90c6-91831165ee22/out_00100.png"
  ],
  "started_at": "2022-07-04T06:16:26.721096Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/vo4p6ishmvgexjbupqejzn5raq",
    "cancel": "https://api.replicate.com/v1/predictions/vo4p6ishmvgexjbupqejzn5raq/cancel"
  },
  "version": "4ed232e4ebe82b3d70ee5e0526257aeeb07187f6727ee617795a7f94d2133e2d"
}