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nightmareai /disco-diffusion:cc730cf6
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=nightmareai/disco-diffusion
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run nightmareai/disco-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"nightmareai/disco-diffusion:cc730cf65f83d7ffed2aa6d47bc9a538b628617be5a4c2db27e7aee6a6391920",
{
input: {
RN50: false,
seed: 2874114942,
RN101: false,
steps: 200,
width: 400,
RN50x4: true,
ViTB16: true,
ViTB32: true,
ViTL14: true,
height: 400,
prompt: "I feel so alive with these phantoms of night and I know that this life isn't safe, but it's wild and it's free, intricate detailed painting, artstation deviantart, absolutely mind blowing beautiful fine art, haunting, whimsical",
RN50x16: false,
RN50x64: false,
RN50x101: false,
tv_scale: 2000,
sat_scale: 1000,
skip_augs: false,
RN50_cc12m: false,
ViTL14_336: true,
init_scale: 1000,
skip_steps: 4,
range_scale: 200,
cutn_batches: 4,
display_rate: 60,
target_scale: 20000,
RN101_yfcc15m: false,
RN50_yffcc15m: false,
diffusion_model: "512x512_diffusion_uncond_finetune_008100",
ViTB32_laion2b_e16: false,
clip_guidance_scale: 80000,
use_secondary_model: false,
RN50_quickgelu_cc12m: false,
ViTB16_laion400m_e31: false,
ViTB16_laion400m_e32: false,
ViTB32_laion400m_e31: false,
ViTB32_laion400m_e32: false,
RN50_quickgelu_yfcc15m: false,
RN101_quickgelu_yfcc15m: false,
diffusion_sampling_mode: "plms",
ViTB32quickgelu_laion400m_e31: false,
ViTB32quickgelu_laion400m_e32: false
}
}
);
console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:
pip install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:
import replicateRun nightmareai/disco-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"nightmareai/disco-diffusion:cc730cf65f83d7ffed2aa6d47bc9a538b628617be5a4c2db27e7aee6a6391920",
input={
"RN50": False,
"seed": 2874114942,
"RN101": False,
"steps": 200,
"width": 400,
"RN50x4": True,
"ViTB16": True,
"ViTB32": True,
"ViTL14": True,
"height": 400,
"prompt": "I feel so alive with these phantoms of night and I know that this life isn't safe, but it's wild and it's free, intricate detailed painting, artstation deviantart, absolutely mind blowing beautiful fine art, haunting, whimsical",
"RN50x16": False,
"RN50x64": False,
"RN50x101": False,
"tv_scale": 2000,
"sat_scale": 1000,
"skip_augs": False,
"RN50_cc12m": False,
"ViTL14_336": True,
"init_scale": 1000,
"skip_steps": 4,
"range_scale": 200,
"cutn_batches": 4,
"display_rate": 60,
"target_scale": 20000,
"RN101_yfcc15m": False,
"RN50_yffcc15m": False,
"diffusion_model": "512x512_diffusion_uncond_finetune_008100",
"ViTB32_laion2b_e16": False,
"clip_guidance_scale": 80000,
"use_secondary_model": False,
"RN50_quickgelu_cc12m": False,
"ViTB16_laion400m_e31": False,
"ViTB16_laion400m_e32": False,
"ViTB32_laion400m_e31": False,
"ViTB32_laion400m_e32": False,
"RN50_quickgelu_yfcc15m": False,
"RN101_quickgelu_yfcc15m": False,
"diffusion_sampling_mode": "plms",
"ViTB32quickgelu_laion400m_e31": False,
"ViTB32quickgelu_laion400m_e32": False
}
)
# The nightmareai/disco-diffusion model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
# https://replicate.com/nightmareai/disco-diffusion/api#output-schema
print(item)To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run nightmareai/disco-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \
-H "Authorization: Bearer $REPLICATE_API_TOKEN" \
-H "Content-Type: application/json" \
-H "Prefer: wait" \
-d $'{
"version": "cc730cf65f83d7ffed2aa6d47bc9a538b628617be5a4c2db27e7aee6a6391920",
"input": {
"RN50": false,
"seed": 2874114942,
"RN101": false,
"steps": 200,
"width": 400,
"RN50x4": true,
"ViTB16": true,
"ViTB32": true,
"ViTL14": true,
"height": 400,
"prompt": "I feel so alive with these phantoms of night and I know that this life isn\'t safe, but it\'s wild and it\'s free, intricate detailed painting, artstation deviantart, absolutely mind blowing beautiful fine art, haunting, whimsical",
"RN50x16": false,
"RN50x64": false,
"RN50x101": false,
"tv_scale": 2000,
"sat_scale": 1000,
"skip_augs": false,
"RN50_cc12m": false,
"ViTL14_336": true,
"init_scale": 1000,
"skip_steps": 4,
"range_scale": 200,
"cutn_batches": 4,
"display_rate": 60,
"target_scale": 20000,
"RN101_yfcc15m": false,
"RN50_yffcc15m": false,
"diffusion_model": "512x512_diffusion_uncond_finetune_008100",
"ViTB32_laion2b_e16": false,
"clip_guidance_scale": 80000,
"use_secondary_model": false,
"RN50_quickgelu_cc12m": false,
"ViTB16_laion400m_e31": false,
"ViTB16_laion400m_e32": false,
"ViTB32_laion400m_e31": false,
"ViTB32_laion400m_e32": false,
"RN50_quickgelu_yfcc15m": false,
"RN101_quickgelu_yfcc15m": false,
"diffusion_sampling_mode": "plms",
"ViTB32quickgelu_laion400m_e31": false,
"ViTB32quickgelu_laion400m_e32": false
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
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Output
{
"completed_at": "2022-07-21T17:48:29.543933Z",
"created_at": "2022-07-21T17:28:59.227783Z",
"data_removed": false,
"error": null,
"id": "q6olw26osbbpnme33qfhp73zo4",
"input": {
"RN50": false,
"seed": "2874114942",
"steps": "200",
"width": 400,
"RN50x4": true,
"ViTB16": true,
"ViTB32": true,
"ViTL14": true,
"height": 400,
"prompt": "I feel so alive with these phantoms of night and I know that this life isn't safe, but it's wild and it's free, intricate detailed painting, artstation deviantart, absolutely mind blowing beautiful fine art, haunting, whimsical",
"tv_scale": 2000,
"sat_scale": 1000,
"skip_augs": false,
"RN50_cc12m": false,
"ViTL14_336": true,
"init_scale": 1000,
"skip_steps": 4,
"range_scale": 200,
"cutn_batches": 4,
"display_rate": 60,
"target_scale": 20000,
"diffusion_model": "512x512_diffusion_uncond_finetune_008100",
"clip_guidance_scale": 80000,
"use_secondary_model": false,
"ViTB32_laion400m_e31": false,
"ViTB32_laion400m_e32": false,
"diffusion_sampling_mode": "plms"
},
"logs": "2022-07-21 17:34:29.702 | INFO | dd:getDevice:2590 - ✅ Using device: cuda:0\n2022-07-21 17:34:29.703 | INFO | dd:getDevice:2600 - Disabling CUDNN for A100 gpu\n2022-07-21 17:34:29.706 | INFO | dd:start_run:2288 - 💼 1 jobs found.\n2022-07-21 17:34:29.706 | INFO | dd:start_run:2300 - ⚒️ Session 27801dd6-f5ec-4d4d-86c5-fc9d5ac6a5d0 started...\n2022-07-21 17:34:29.706 | INFO | dd:start_run:2303 - 💼 Processing job 1 of 1...\n2022-07-21 17:34:29.707 | INFO | dd:start_run:2306 - 🌲 Setting TORCH_HOME environment variable to /root/.cache/disco-diffusion...\n2022-07-21 17:34:29.708 | INFO | dd:processBatch:2414 - 🌱 Using starting seed: 2874114942\n2022-07-21 17:34:29.708 | INFO | dd:free_mem:73 - Clearing CUDA cache on cuda:0...\n2022-07-21 17:34:29.709 | INFO | dd:do_run:1188 - 💻 Starting Run: eb1a4d44-6054-4861-8a2e-1d4927542eb2(0) at frame 0\n2022-07-21 17:34:29.709 | INFO | dd:clipLoad:1174 - 🤖 Loading model 'ViT-B/32'...\n2022-07-21 17:34:36.185 | INFO | dd:clipLoad:1174 - 🤖 Loading model 'ViT-B/16'...\n2022-07-21 17:34:40.345 | INFO | dd:clipLoad:1174 - 🤖 Loading model 'ViT-L/14'...\n2022-07-21 17:34:50.961 | INFO | dd:clipLoad:1174 - 🤖 Loading model 'ViT-L/14@336px'...\n2022-07-21 17:35:00.966 | INFO | dd:clipLoad:1174 - 🤖 Loading model 'RN50x4'...\n2022-07-21 17:35:06.323 | INFO | dd:do_run:1246 - 🤖 Loading LPIPS...\n/root/.pyenv/versions/3.8.13/lib/python3.8/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and will be removed in 0.15, please use 'weights' instead.\n warnings.warn(\n/root/.pyenv/versions/3.8.13/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and will be removed in 0.15. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.\n warnings.warn(msg)\n\u001b[2K\n2022-07-21 17:35:08.161 | WARNING | dd:disco:1497 - Changing output size to 384x384. Dimensions must by multiples of 64.\n2022-07-21 17:35:08.162 | INFO | dd:disco:1556 - timestep_respacing : ddim200 | diffusion_steps: 1000\n2022-07-21 17:35:08.162 | INFO | dd:prepModels:1071 - Prepping models...\n2022-07-21 17:35:14.292 | INFO | dd:disco:1586 - Running job '7c31ba4e-c6d4-4b9c-a375-7be4f1202798'...\n2022-07-21 17:35:14.293 | INFO | dd:disco:1600 - 🌱 Seed used: 2874114942\n2022-07-21 17:35:14.302 | INFO | dd:disco:1626 - Frame 0 📝 Prompt: [\"I feel so alive with these phantoms of night and I know that this life isn't safe, but it's wild and it's free, intricate detailed painting, artstation deviantart, absolutely mind blowing beautiful fine art, haunting, whimsical\"]\n\u001b[2K\n\u001b[2K\n\u001b[2K\nBatches: 0%| | 0/1 [00:00<?, ?it/s]\nOutput()\n2022-07-21 17:35:17.031 | INFO | dd:free_mem:73 - Clearing CUDA cache on cuda:0...\n\n\n 0%| | 0/196 [00:00<?, ?it/s]\u001b[A\nBatch 0, step 0, output 0:\n\n\n\u001b[A\n\n\u001b[2K\n\u001b[2K\n<PIL.Image.Image image mode=RGB size=384x384 at 0x7FBEA89FBF70>\n 0%| | 0/196 [00:07<?, ?it/s]\u001b[A\n\n 1%| | 1/196 [00:07<25:06, 7.73s/it]\u001b[A\n\n 1%| | 2/196 [00:11<17:33, 5.43s/it]\u001b[A\n\n 2%|▏ | 3/196 [00:15<15:04, 4.68s/it]\u001b[A\n\n 2%|▏ | 4/196 [00:19<13:52, 4.34s/it]\u001b[A\n\n 3%|▎ | 5/196 [00:22<13:10, 4.14s/it]\u001b[A\n\n 3%|▎ | 6/196 [00:26<12:44, 4.03s/it]\u001b[A\n\n 4%|▎ | 7/196 [00:30<12:26, 3.95s/it]\u001b[A\n\n 4%|▍ | 8/196 [00:34<12:13, 3.90s/it]\u001b[A\n\n 5%|▍ | 9/196 [00:38<12:03, 3.87s/it]\u001b[A\n\n 5%|▌ | 10/196 [00:41<11:55, 3.84s/it]\u001b[A\n\n 6%|▌ | 11/196 [00:45<11:48, 3.83s/it]\u001b[A\n\n 6%|▌ | 12/196 [00:49<11:43, 3.82s/it]\u001b[A\n\n 7%|▋ | 13/196 [00:53<11:37, 3.81s/it]\u001b[A\n\n 7%|▋ | 14/196 [00:57<11:33, 3.81s/it]\u001b[A\n\n 8%|▊ | 15/196 [01:00<11:29, 3.81s/it]\u001b[A\n\n 8%|▊ | 16/196 [01:04<11:25, 3.81s/it]\u001b[A\n\n 9%|▊ | 17/196 [01:08<11:21, 3.80s/it]\u001b[A\n\n 9%|▉ | 18/196 [01:12<11:16, 3.80s/it]\u001b[A\n\n 10%|▉ | 19/196 [01:16<11:11, 3.79s/it]\u001b[A\n\n 10%|█ | 20/196 [01:19<11:09, 3.80s/it]\u001b[A\n\n 11%|█ | 21/196 [01:23<11:05, 3.80s/it]\u001b[A\n\n 11%|█ | 22/196 [01:27<11:01, 3.80s/it]\u001b[A\n\n 12%|█▏ | 23/196 [01:31<10:56, 3.80s/it]\u001b[A\n\n 12%|█▏ | 24/196 [01:35<10:52, 3.80s/it]\u001b[A\n\n 13%|█▎ | 25/196 [01:38<10:49, 3.80s/it]\u001b[A\n\n 13%|█▎ | 26/196 [01:42<10:45, 3.80s/it]\u001b[A\n\n 14%|█▍ | 27/196 [01:46<10:41, 3.80s/it]\u001b[A\n\n 14%|█▍ | 28/196 [01:50<10:37, 3.79s/it]\u001b[A\n\n 15%|█▍ | 29/196 [01:54<10:34, 3.80s/it]\u001b[A\n\n 15%|█▌ | 30/196 [01:57<10:30, 3.80s/it]\u001b[A\n\n 16%|█▌ | 31/196 [02:01<10:27, 3.80s/it]\u001b[A\n\n 16%|█▋ | 32/196 [02:05<10:23, 3.80s/it]\u001b[A\n\n 17%|█▋ | 33/196 [02:09<10:20, 3.81s/it]\u001b[A\n\n 17%|█▋ | 34/196 [02:13<10:17, 3.81s/it]\u001b[A\n\n 18%|█▊ | 35/196 [02:16<10:13, 3.81s/it]\u001b[A\n\n 18%|█▊ | 36/196 [02:20<10:10, 3.81s/it]\u001b[A\n\n 19%|█▉ | 37/196 [02:24<10:06, 3.81s/it]\u001b[A\n\n 19%|█▉ | 38/196 [02:28<10:02, 3.81s/it]\u001b[A\n\n 20%|█▉ | 39/196 [02:32<09:58, 3.81s/it]\u001b[A\n\n 20%|██ | 40/196 [02:36<09:55, 3.81s/it]\u001b[A\n\n 21%|██ | 41/196 [02:39<09:51, 3.81s/it]\u001b[A\n\n 21%|██▏ | 42/196 [02:43<09:48, 3.82s/it]\u001b[A\n\n 22%|██▏ | 43/196 [02:47<09:44, 3.82s/it]\u001b[A\n\n 22%|██▏ | 44/196 [02:51<09:40, 3.82s/it]\u001b[A\n\n 23%|██▎ | 45/196 [02:55<09:36, 3.82s/it]\u001b[A\n\n 23%|██▎ | 46/196 [02:58<09:33, 3.82s/it]\u001b[A\n\n 24%|██▍ | 47/196 [03:02<09:29, 3.82s/it]\u001b[A\n\n 24%|██▍ | 48/196 [03:06<09:24, 3.81s/it]\u001b[A\n\n 25%|██▌ | 49/196 [03:10<09:21, 3.82s/it]\u001b[A\n\n 26%|██▌ | 50/196 [03:14<09:18, 3.83s/it]\u001b[A\n\n 26%|██▌ | 51/196 [03:18<09:13, 3.82s/it]\u001b[A\n\n 27%|██▋ | 52/196 [03:21<09:10, 3.82s/it]\u001b[A\n\n 27%|██▋ | 53/196 [03:25<09:07, 3.83s/it]\u001b[A\n\n 28%|██▊ | 54/196 [03:29<09:04, 3.83s/it]\u001b[A\n\n 28%|██▊ | 55/196 [03:33<08:59, 3.83s/it]\u001b[A\n\n 29%|██▊ | 56/196 [03:37<08:55, 3.83s/it]\u001b[A\n\n 29%|██▉ | 57/196 [03:41<08:51, 3.82s/it]\u001b[A\n\n 30%|██▉ | 58/196 [03:44<08:46, 3.82s/it]\u001b[A\n\n 30%|███ | 59/196 [03:48<08:42, 3.82s/it]\u001b[A\n\n 31%|███ | 60/196 [03:52<08:40, 3.82s/it]\u001b[A\n\n\nBatch 0, step 60, output 0:\n\u001b[A\n\n\u001b[2K\n\u001b[2K\n<PIL.Image.Image image mode=RGB size=384x384 at 0x7FBEA89FBEE0>\n 31%|███ | 60/196 [03:56<08:40, 3.82s/it]\u001b[A\n\n 31%|███ | 61/196 [03:56<08:37, 3.83s/it]\u001b[A\n\n 32%|███▏ | 62/196 [04:00<08:33, 3.83s/it]\u001b[A\n\n 32%|███▏ | 63/196 [04:03<08:29, 3.83s/it]\u001b[A\n\n 33%|███▎ | 64/196 [04:07<08:26, 3.83s/it]\u001b[A\n\n 33%|███▎ | 65/196 [04:11<08:23, 3.84s/it]\u001b[A\n\n 34%|███▎ | 66/196 [04:15<08:19, 3.84s/it]\u001b[A\n\n 34%|███▍ | 67/196 [04:19<08:15, 3.84s/it]\u001b[A\n\n 35%|███▍ | 68/196 [04:23<08:12, 3.85s/it]\u001b[A\n\n 35%|███▌ | 69/196 [04:27<08:08, 3.85s/it]\u001b[A2022-07-21 17:39:47.733 | DEBUG | dd:cond_fn:2061 - NaN'd\n\n\n 36%|███▌ | 70/196 [04:30<07:56, 3.78s/it]\u001b[A2022-07-21 17:39:51.365 | DEBUG | dd:cond_fn:2061 - NaN'd\n\n\n 36%|███▌ | 71/196 [04:34<07:47, 3.74s/it]\u001b[A\n\n 37%|███▋ | 72/196 [04:38<07:47, 3.77s/it]\u001b[A\n\n 37%|███▋ | 73/196 [04:42<07:47, 3.80s/it]\u001b[A\n\n 38%|███▊ | 74/196 [04:45<07:45, 3.82s/it]\u001b[A\n\n 38%|███▊ | 75/196 [04:49<07:43, 3.83s/it]\u001b[A\n\n 39%|███▉ | 76/196 [04:53<07:39, 3.83s/it]\u001b[A\n\n 39%|███▉ | 77/196 [04:57<07:46, 3.92s/it]\u001b[A\n\n 40%|███▉ | 78/196 [05:01<07:51, 3.99s/it]\u001b[A\n\n 40%|████ | 79/196 [05:06<07:51, 4.03s/it]\u001b[A\n\n 41%|████ | 80/196 [05:10<07:51, 4.06s/it]\u001b[A\n\n 41%|████▏ | 81/196 [05:14<07:50, 4.09s/it]\u001b[A\n\n 42%|████▏ | 82/196 [05:18<07:47, 4.10s/it]\u001b[A\n\n 42%|████▏ | 83/196 [05:22<07:44, 4.11s/it]\u001b[A\n\n 43%|████▎ | 84/196 [05:26<07:41, 4.12s/it]\u001b[A\n\n 43%|████▎ | 85/196 [05:30<07:37, 4.12s/it]\u001b[A\n\n 44%|████▍ | 86/196 [05:34<07:33, 4.13s/it]\u001b[A\n\n 44%|████▍ | 87/196 [05:39<07:29, 4.13s/it]\u001b[A\n\n 45%|████▍ | 88/196 [05:43<07:25, 4.13s/it]\u001b[A\n\n 45%|████▌ | 89/196 [05:47<07:20, 4.12s/it]\u001b[A\n\n 46%|████▌ | 90/196 [05:51<07:16, 4.12s/it]\u001b[A\n\n 46%|████▋ | 91/196 [05:55<07:12, 4.12s/it]\u001b[A\n\n 47%|████▋ | 92/196 [05:59<07:07, 4.11s/it]\u001b[A\n\n 47%|████▋ | 93/196 [06:03<07:03, 4.12s/it]\u001b[A\n\n 48%|████▊ | 94/196 [06:07<06:59, 4.11s/it]\u001b[A\n\n 48%|████▊ | 95/196 [06:12<06:55, 4.11s/it]\u001b[A\n\n 49%|████▉ | 96/196 [06:16<06:50, 4.11s/it]\u001b[A\n\n 49%|████▉ | 97/196 [06:20<06:46, 4.10s/it]\u001b[A\n\n 50%|█████ | 98/196 [06:24<06:42, 4.11s/it]\u001b[A\n\n 51%|█████ | 99/196 [06:28<06:38, 4.11s/it]\u001b[A\n\n 51%|█████ | 100/196 [06:32<06:34, 4.11s/it]\u001b[A\n\n 52%|█████▏ | 101/196 [06:36<06:30, 4.11s/it]\u001b[A\n\n 52%|█████▏ | 102/196 [06:40<06:26, 4.11s/it]\u001b[A\n\n 53%|█████▎ | 103/196 [06:44<06:22, 4.11s/it]\u001b[A\n\n 53%|█████▎ | 104/196 [06:49<06:18, 4.12s/it]\u001b[A\n\n 54%|█████▎ | 105/196 [06:53<06:14, 4.11s/it]\u001b[A\n\n 54%|█████▍ | 106/196 [06:57<06:09, 4.11s/it]\u001b[A\n\n 55%|█████▍ | 107/196 [07:01<06:05, 4.11s/it]\u001b[A\n\n 55%|█████▌ | 108/196 [07:05<06:00, 4.10s/it]\u001b[A\n\n 56%|█████▌ | 109/196 [07:09<05:56, 4.10s/it]\u001b[A\n\n 56%|█████▌ | 110/196 [07:13<05:52, 4.10s/it]\u001b[A\n\n 57%|█████▋ | 111/196 [07:17<05:48, 4.10s/it]\u001b[A\n\n 57%|█████▋ | 112/196 [07:21<05:45, 4.11s/it]\u001b[A\n\n 58%|█████▊ | 113/196 [07:25<05:41, 4.11s/it]\u001b[A\n\n 58%|█████▊ | 114/196 [07:30<05:36, 4.11s/it]\u001b[A\n\n 59%|█████▊ | 115/196 [07:34<05:32, 4.11s/it]\u001b[A\n\n 59%|█████▉ | 116/196 [07:38<05:28, 4.11s/it]\u001b[A\n\n 60%|█████▉ | 117/196 [07:42<05:24, 4.11s/it]\u001b[A\n\n 60%|██████ | 118/196 [07:46<05:20, 4.10s/it]\u001b[A\n\n 61%|██████ | 119/196 [07:50<05:16, 4.11s/it]\u001b[A\n\n 61%|██████ | 120/196 [07:54<05:12, 4.12s/it]\u001b[A\n\nBatch 0, step 120, output 0:\n\n\u001b[A\n\n\u001b[2K\n\u001b[2K\n<PIL.Image.Image image mode=RGB size=384x384 at 0x7FBEA89FBDF0>\n 61%|██████ | 120/196 [07:58<05:12, 4.12s/it]\u001b[A\n\n 62%|██████▏ | 121/196 [07:58<05:10, 4.14s/it]\u001b[A\n\n 62%|██████▏ | 122/196 [08:03<05:05, 4.13s/it]\u001b[A\n\n 63%|██████▎ | 123/196 [08:07<05:01, 4.13s/it]\u001b[A\n\n 63%|██████▎ | 124/196 [08:11<04:57, 4.13s/it]\u001b[A\n\n 64%|██████▍ | 125/196 [08:15<04:53, 4.13s/it]\u001b[A\n\n 64%|██████▍ | 126/196 [08:19<04:49, 4.13s/it]\u001b[A\n\n 65%|██████▍ | 127/196 [08:23<04:45, 4.13s/it]\u001b[A2022-07-21 17:43:44.640 | DEBUG | dd:cond_fn:2061 - NaN'd\n\n\n 65%|██████▌ | 128/196 [08:27<04:36, 4.07s/it]\u001b[A\n\n 66%|██████▌ | 129/196 [08:31<04:34, 4.09s/it]\u001b[A2022-07-21 17:43:52.669 | DEBUG | dd:cond_fn:2061 - NaN'd\n\n\n 66%|██████▋ | 130/196 [08:35<04:26, 4.03s/it]\u001b[A\n\n 67%|██████▋ | 131/196 [08:39<04:23, 4.06s/it]\u001b[A\n\n 67%|██████▋ | 132/196 [08:43<04:21, 4.08s/it]\u001b[A\n\n 68%|██████▊ | 133/196 [08:48<04:17, 4.10s/it]\u001b[A\n\n 68%|██████▊ | 134/196 [08:52<04:14, 4.10s/it]\u001b[A\n\n 69%|██████▉ | 135/196 [08:56<04:10, 4.11s/it]\u001b[A\n\n 69%|██████▉ | 136/196 [09:00<04:07, 4.12s/it]\u001b[A\n\n 70%|██████▉ | 137/196 [09:04<04:03, 4.12s/it]\u001b[A\n\n 70%|███████ | 138/196 [09:08<03:59, 4.13s/it]\u001b[A\n\n 71%|███████ | 139/196 [09:12<03:55, 4.13s/it]\u001b[A\n\n 71%|███████▏ | 140/196 [09:16<03:50, 4.12s/it]\u001b[A\n\n 72%|███████▏ | 141/196 [09:21<03:46, 4.12s/it]\u001b[A\n\n 72%|███████▏ | 142/196 [09:25<03:41, 4.11s/it]\u001b[A\n\n 73%|███████▎ | 143/196 [09:29<03:37, 4.10s/it]\u001b[A\n\n 73%|███████▎ | 144/196 [09:33<03:33, 4.10s/it]\u001b[A\n\n 74%|███████▍ | 145/196 [09:37<03:28, 4.09s/it]\u001b[A\n\n 74%|███████▍ | 146/196 [09:41<03:24, 4.09s/it]\u001b[A\n\n 75%|███████▌ | 147/196 [09:45<03:20, 4.10s/it]\u001b[A\n\n 76%|███████▌ | 148/196 [09:49<03:16, 4.10s/it]\u001b[A\n\n 76%|███████▌ | 149/196 [09:53<03:12, 4.10s/it]\u001b[A\n\n 77%|███████▋ | 150/196 [09:57<03:08, 4.10s/it]\u001b[A\n\n 77%|███████▋ | 151/196 [10:01<03:04, 4.10s/it]\u001b[A\n\n 78%|███████▊ | 152/196 [10:06<03:00, 4.10s/it]\u001b[A2022-07-21 17:45:26.967 | DEBUG | dd:cond_fn:2061 - NaN'd\n\n\n 78%|███████▊ | 153/196 [10:09<02:53, 4.03s/it]\u001b[A\n\n 79%|███████▊ | 154/196 [10:14<02:50, 4.06s/it]\u001b[A\n\n 79%|███████▉ | 155/196 [10:18<02:47, 4.08s/it]\u001b[A\n\n 80%|███████▉ | 156/196 [10:22<02:43, 4.09s/it]\u001b[A2022-07-21 17:45:43.251 | DEBUG | dd:cond_fn:2061 - NaN'd\n\n\n 80%|████████ | 157/196 [10:26<02:37, 4.04s/it]\u001b[A\n\n 81%|████████ | 158/196 [10:30<02:34, 4.06s/it]\u001b[A\n\n 81%|████████ | 159/196 [10:34<02:31, 4.08s/it]\u001b[A\n\n 82%|████████▏ | 160/196 [10:38<02:28, 4.11s/it]\u001b[A\n\n 82%|████████▏ | 161/196 [10:42<02:24, 4.13s/it]\u001b[A\n\n 83%|████████▎ | 162/196 [10:46<02:20, 4.14s/it]\u001b[A\n\n 83%|████████▎ | 163/196 [10:51<02:16, 4.14s/it]\u001b[A\n\n 84%|████████▎ | 164/196 [10:55<02:12, 4.14s/it]\u001b[A\n\n 84%|████████▍ | 165/196 [10:59<02:08, 4.15s/it]\u001b[A\n\n 85%|████████▍ | 166/196 [11:03<02:04, 4.15s/it]\u001b[A\n\n 85%|████████▌ | 167/196 [11:07<02:00, 4.15s/it]\u001b[A\n\n 86%|████████▌ | 168/196 [11:11<01:56, 4.15s/it]\u001b[A\n\n 86%|████████▌ | 169/196 [11:16<01:51, 4.14s/it]\u001b[A\n\n 87%|████████▋ | 170/196 [11:20<01:47, 4.14s/it]\u001b[A\n\n 87%|████████▋ | 171/196 [11:24<01:43, 4.14s/it]\u001b[A\n\n 88%|████████▊ | 172/196 [11:28<01:39, 4.14s/it]\u001b[A\n\n 88%|████████▊ | 173/196 [11:32<01:35, 4.13s/it]\u001b[A\n\n 89%|████████▉ | 174/196 [11:36<01:30, 4.13s/it]\u001b[A2022-07-21 17:46:57.609 | DEBUG | dd:cond_fn:2061 - NaN'd\n\n\n 89%|████████▉ | 175/196 [11:40<01:25, 4.06s/it]\u001b[A\n\n 90%|████████▉ | 176/196 [11:44<01:21, 4.08s/it]\u001b[A\n\n 90%|█████████ | 177/196 [11:48<01:17, 4.10s/it]\u001b[A\n\n 91%|█████████ | 178/196 [11:52<01:13, 4.11s/it]\u001b[A\n\n 91%|█████████▏| 179/196 [11:57<01:09, 4.12s/it]\u001b[A\n\nBatch 0, step 180, output 0:\n 92%|█████████▏| 180/196 [12:01<01:05, 4.12s/it]\u001b[A\n\n\n\u001b[A\n\n\u001b[2K\n\u001b[2K\n<PIL.Image.Image image mode=RGB size=384x384 at 0x7FBEA89FBEE0>\n 92%|█████████▏| 180/196 [12:05<01:05, 4.12s/it]\u001b[A\n\n 92%|█████████▏| 181/196 [12:05<01:01, 4.13s/it]\u001b[A\n\n 93%|█████████▎| 182/196 [12:09<00:57, 4.13s/it]\u001b[A\n\n 93%|█████████▎| 183/196 [12:13<00:53, 4.13s/it]\u001b[A\n\n 94%|█████████▍| 184/196 [12:17<00:49, 4.12s/it]\u001b[A\n\n 94%|█████████▍| 185/196 [12:21<00:45, 4.12s/it]\u001b[A\n\n 95%|█████████▍| 186/196 [12:25<00:41, 4.12s/it]\u001b[A\n\n 95%|█████████▌| 187/196 [12:30<00:37, 4.11s/it]\u001b[A\n\n 96%|█████████▌| 188/196 [12:34<00:32, 4.11s/it]\u001b[A\n\n 96%|█████████▋| 189/196 [12:38<00:28, 4.11s/it]\u001b[A\n\n 97%|█████████▋| 190/196 [12:42<00:24, 4.11s/it]\u001b[A\n\n 97%|█████████▋| 191/196 [12:46<00:20, 4.10s/it]\u001b[A2022-07-21 17:48:07.399 | DEBUG | dd:cond_fn:2061 - NaN'd\n\n\n 98%|█████████▊| 192/196 [12:50<00:16, 4.04s/it]\u001b[A\n\n 98%|█████████▊| 193/196 [12:54<00:12, 4.06s/it]\u001b[A\n\n 99%|█████████▉| 194/196 [12:58<00:08, 4.07s/it]\u001b[A\n\nBatch 0, step 195, output 0:\n 99%|█████████▉| 195/196 [13:02<00:04, 4.07s/it]\u001b[A\n\n\n\u001b[A\n\n\u001b[2K\n\u001b[2K\n<PIL.Image.Image image mode=RGB size=384x384 at 0x7FBEA89FBDF0>\n 99%|█████████▉| 195/196 [13:06<00:04, 4.07s/it]\u001b[A2022-07-21 17:48:23.857 | INFO | dd:disco:1882 - Image render completed.\n2022-07-21 17:48:23.899 | INFO | dd:disco:1902 - Image saved to '/src/images_out/eb1a4d44-6054-4861-8a2e-1d4927542eb2/eb1a4d44-6054-4861-8a2e-1d4927542eb2(0)_0.png'\n\n\n100%|██████████| 196/196 [13:06<00:00, 4.11s/it]\u001b[A\n100%|██████████| 196/196 [13:06<00:00, 4.01s/it]\n2022-07-21 17:48:23.900 | INFO | dd:free_mem:73 - Clearing CUDA cache on cuda:0...\n2022-07-21 17:48:23.900 | SUCCESS | dd:start_run:2309 - ✅ Session 27801dd6-f5ec-4d4d-86c5-fc9d5ac6a5d0 finished by user.\n2022-07-21 17:48:23.900 | DEBUG | dd:sendSMS:2628 - Not sending SMS\n2022-07-21 17:48:23.900 | INFO | dd:free_mem:73 - Clearing CUDA cache on cuda:0...",
"metrics": {
"predict_time": 839.771437,
"total_time": 1170.31615
},
"output": [
"https://replicate.delivery/mgxm/c8408ef2-c223-42df-925d-3331e370b5b7/progress.png",
"https://replicate.delivery/mgxm/6e6af868-966c-4538-a0d2-ab822bda65e3/progress.png",
"https://replicate.delivery/mgxm/9b9848ac-9bfd-4ebc-afc1-83ae32f9224d/progress.png",
"https://replicate.delivery/mgxm/31c43e34-ed3c-4189-9de5-660300f00ec9/progress.png",
"https://replicate.delivery/mgxm/9f246d09-b852-4384-be80-9bba5f9697af/progress.png",
"https://replicate.delivery/mgxm/718506fb-f089-4f10-afd0-ba0321a71226/eb1a4d44-6054-4861-8a2e-1d4927542eb20_0.png"
],
"started_at": "2022-07-21T17:34:29.772496Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/q6olw26osbbpnme33qfhp73zo4",
"cancel": "https://api.replicate.com/v1/predictions/q6olw26osbbpnme33qfhp73zo4/cancel"
},
"version": "cc730cf65f83d7ffed2aa6d47bc9a538b628617be5a4c2db27e7aee6a6391920"
}Generated in
2022-07-21 17:34:29.702 | INFO | dd:getDevice:2590 - ✅ Using device: cuda:0
2022-07-21 17:34:29.703 | INFO | dd:getDevice:2600 - Disabling CUDNN for A100 gpu
2022-07-21 17:34:29.706 | INFO | dd:start_run:2288 - 💼 1 jobs found.
2022-07-21 17:34:29.706 | INFO | dd:start_run:2300 - ⚒️ Session 27801dd6-f5ec-4d4d-86c5-fc9d5ac6a5d0 started...
2022-07-21 17:34:29.706 | INFO | dd:start_run:2303 - 💼 Processing job 1 of 1...
2022-07-21 17:34:29.707 | INFO | dd:start_run:2306 - 🌲 Setting TORCH_HOME environment variable to /root/.cache/disco-diffusion...
2022-07-21 17:34:29.708 | INFO | dd:processBatch:2414 - 🌱 Using starting seed: 2874114942
2022-07-21 17:34:29.708 | INFO | dd:free_mem:73 - Clearing CUDA cache on cuda:0...
2022-07-21 17:34:29.709 | INFO | dd:do_run:1188 - 💻 Starting Run: eb1a4d44-6054-4861-8a2e-1d4927542eb2(0) at frame 0
2022-07-21 17:34:29.709 | INFO | dd:clipLoad:1174 - 🤖 Loading model 'ViT-B/32'...
2022-07-21 17:34:36.185 | INFO | dd:clipLoad:1174 - 🤖 Loading model 'ViT-B/16'...
2022-07-21 17:34:40.345 | INFO | dd:clipLoad:1174 - 🤖 Loading model 'ViT-L/14'...
2022-07-21 17:34:50.961 | INFO | dd:clipLoad:1174 - 🤖 Loading model 'ViT-L/14@336px'...
2022-07-21 17:35:00.966 | INFO | dd:clipLoad:1174 - 🤖 Loading model 'RN50x4'...
2022-07-21 17:35:06.323 | INFO | dd:do_run:1246 - 🤖 Loading LPIPS...
/root/.pyenv/versions/3.8.13/lib/python3.8/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and will be removed in 0.15, please use 'weights' instead.
warnings.warn(
/root/.pyenv/versions/3.8.13/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and will be removed in 0.15. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
warnings.warn(msg)
2022-07-21 17:35:08.161 | WARNING | dd:disco:1497 - Changing output size to 384x384. Dimensions must by multiples of 64.
2022-07-21 17:35:08.162 | INFO | dd:disco:1556 - timestep_respacing : ddim200 | diffusion_steps: 1000
2022-07-21 17:35:08.162 | INFO | dd:prepModels:1071 - Prepping models...
2022-07-21 17:35:14.292 | INFO | dd:disco:1586 - Running job '7c31ba4e-c6d4-4b9c-a375-7be4f1202798'...
2022-07-21 17:35:14.293 | INFO | dd:disco:1600 - 🌱 Seed used: 2874114942
2022-07-21 17:35:14.302 | INFO | dd:disco:1626 - Frame 0 📝 Prompt: ["I feel so alive with these phantoms of night and I know that this life isn't safe, but it's wild and it's free, intricate detailed painting, artstation deviantart, absolutely mind blowing beautiful fine art, haunting, whimsical"]
Batches: 0%| | 0/1 [00:00<?, ?it/s]
Output()
2022-07-21 17:35:17.031 | INFO | dd:free_mem:73 - Clearing CUDA cache on cuda:0...
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Batch 0, step 60, output 0:
<PIL.Image.Image image mode=RGB size=384x384 at 0x7FBEA89FBEE0>
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35%|███▌ | 69/196 [04:27<08:08, 3.85s/it]2022-07-21 17:39:47.733 | DEBUG | dd:cond_fn:2061 - NaN'd
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Batch 0, step 120, output 0:
<PIL.Image.Image image mode=RGB size=384x384 at 0x7FBEA89FBDF0>
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78%|███████▊ | 152/196 [10:06<03:00, 4.10s/it]2022-07-21 17:45:26.967 | DEBUG | dd:cond_fn:2061 - NaN'd
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80%|███████▉ | 156/196 [10:22<02:43, 4.09s/it]2022-07-21 17:45:43.251 | DEBUG | dd:cond_fn:2061 - NaN'd
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89%|████████▉ | 174/196 [11:36<01:30, 4.13s/it]2022-07-21 17:46:57.609 | DEBUG | dd:cond_fn:2061 - NaN'd
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Batch 0, step 180, output 0:
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<PIL.Image.Image image mode=RGB size=384x384 at 0x7FBEA89FBEE0>
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97%|█████████▋| 191/196 [12:46<00:20, 4.10s/it]2022-07-21 17:48:07.399 | DEBUG | dd:cond_fn:2061 - NaN'd
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Batch 0, step 195, output 0:
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<PIL.Image.Image image mode=RGB size=384x384 at 0x7FBEA89FBDF0>
99%|█████████▉| 195/196 [13:06<00:04, 4.07s/it]2022-07-21 17:48:23.857 | INFO | dd:disco:1882 - Image render completed.
2022-07-21 17:48:23.899 | INFO | dd:disco:1902 - Image saved to '/src/images_out/eb1a4d44-6054-4861-8a2e-1d4927542eb2/eb1a4d44-6054-4861-8a2e-1d4927542eb2(0)_0.png'
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2022-07-21 17:48:23.900 | INFO | dd:free_mem:73 - Clearing CUDA cache on cuda:0...
2022-07-21 17:48:23.900 | SUCCESS | dd:start_run:2309 - ✅ Session 27801dd6-f5ec-4d4d-86c5-fc9d5ac6a5d0 finished by user.
2022-07-21 17:48:23.900 | DEBUG | dd:sendSMS:2628 - Not sending SMS
2022-07-21 17:48:23.900 | INFO | dd:free_mem:73 - Clearing CUDA cache on cuda:0...