Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use NadaGh/working with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use NadaGh/working with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("NadaGh/working", dtype=torch.bfloat16, device_map="cuda") prompt = "tst chair" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 4,519 Bytes
dde5d93 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 | import argparse
import json
import os
from datetime import date
from pathlib import Path
from slack_sdk import WebClient
from tabulate import tabulate
MAX_LEN_MESSAGE = 2900 # slack endpoint has a limit of 3001 characters
parser = argparse.ArgumentParser()
parser.add_argument("--slack_channel_name", default="diffusers-ci-nightly")
def main(slack_channel_name=None):
failed = []
passed = []
group_info = []
total_num_failed = 0
empty_file = False or len(list(Path().glob("*.log"))) == 0
total_empty_files = []
for log in Path().glob("*.log"):
section_num_failed = 0
i = 0
with open(log) as f:
for line in f:
line = json.loads(line)
i += 1
if line.get("nodeid", "") != "":
test = line["nodeid"]
if line.get("duration", None) is not None:
duration = f'{line["duration"]:.4f}'
if line.get("outcome", "") == "failed":
section_num_failed += 1
failed.append([test, duration, log.name.split("_")[0]])
total_num_failed += 1
else:
passed.append([test, duration, log.name.split("_")[0]])
empty_file = i == 0
group_info.append([str(log), section_num_failed, failed])
total_empty_files.append(empty_file)
os.remove(log)
failed = []
text = (
"🌞 There were no failures!"
if not any(total_empty_files)
else "Something went wrong there is at least one empty file - please check GH action results."
)
no_error_payload = {
"type": "section",
"text": {
"type": "plain_text",
"text": text,
"emoji": True,
},
}
message = ""
payload = [
{
"type": "header",
"text": {
"type": "plain_text",
"text": "🤗 Results of the Diffusers scheduled nightly tests.",
},
},
]
if total_num_failed > 0:
for i, (name, num_failed, failed_tests) in enumerate(group_info):
if num_failed > 0:
if num_failed == 1:
message += f"*{name}: {num_failed} failed test*\n"
else:
message += f"*{name}: {num_failed} failed tests*\n"
failed_table = []
for test in failed_tests:
failed_table.append(test[0].split("::"))
failed_table = tabulate(
failed_table,
headers=["Test Location", "Test Case", "Test Name"],
showindex="always",
tablefmt="grid",
maxcolwidths=[12, 12, 12],
)
message += "\n```\n" + failed_table + "\n```"
if total_empty_files[i]:
message += f"\n*{name}: Warning! Empty file - please check the GitHub action job *\n"
print(f"### {message}")
else:
payload.append(no_error_payload)
if len(message) > MAX_LEN_MESSAGE:
print(f"Truncating long message from {len(message)} to {MAX_LEN_MESSAGE}")
message = message[:MAX_LEN_MESSAGE] + "..."
if len(message) != 0:
md_report = {
"type": "section",
"text": {"type": "mrkdwn", "text": message},
}
payload.append(md_report)
action_button = {
"type": "section",
"text": {"type": "mrkdwn", "text": "*For more details:*"},
"accessory": {
"type": "button",
"text": {"type": "plain_text", "text": "Check Action results", "emoji": True},
"url": f"https://github.com/huggingface/diffusers/actions/runs/{os.environ['GITHUB_RUN_ID']}",
},
}
payload.append(action_button)
date_report = {
"type": "context",
"elements": [
{
"type": "plain_text",
"text": f"Nightly test results for {date.today()}",
},
],
}
payload.append(date_report)
print(payload)
client = WebClient(token=os.environ.get("SLACK_API_TOKEN"))
client.chat_postMessage(channel=f"#{slack_channel_name}", text=message, blocks=payload)
if __name__ == "__main__":
args = parser.parse_args()
main(args.slack_channel_name)
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