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update directml

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This commit is contained in:
Vladimir Mandic
2023-05-13 11:21:11 -04:00
parent a2485cf7ef
commit d96ab6a1ae
11 changed files with 127 additions and 72 deletions
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cli/generate.py
+1 -1
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@@ -121,7 +121,7 @@ def sampler(params, options): # find sampler
async def generate(prompt = None, options = None, quiet = False): # pylint: disable=redefined-outer-name
global sd
global sd # pylint: disable=global-statement
if options:
sd = Map(options)
if prompt is not None:
cli/modules/preview-models.py
+72 -32
View File
@@ -11,7 +11,7 @@ from sdapi import get, post, close
from grid import grid
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
from generate import sd, generate
from generate import generate # pylint: disable=import-error
default = 'sd-v15-runwayml.ckpt [cc6cb27103]'
@@ -72,13 +72,12 @@ options = Map({
})
async def models(params):
global sd
async def preview_models(params):
data = await get('/sdapi/v1/sd-models')
all = [m['title'] for m in data]
allmodels = [m['title'] for m in data]
models = []
excluded = []
for m in all: # loop through all registered models
for m in allmodels: # loop through all registered models
ok = True
for e in exclude: # check if model is excluded
if e in m:
@@ -100,17 +99,16 @@ async def models(params):
models = filtered
log.info({ 'models preview' })
log.info({ 'models': len(models), 'excluded': len(excluded) })
cmdflags = await get('/sdapi/v1/cmd-flags')
opt = await get('/sdapi/v1/options')
if params.output != '':
dir = params.output
folder = params.output
else:
dir = os.path.abspath(os.path.join(cmdflags['hypernetwork_dir'], '..', 'Stable-diffusion'))
log.info({ 'output directory': dir })
folder = os.path.abspath(os.path.join(opt['hypernetwork_dir'], '..', 'Stable-diffusion'))
log.info({ 'output directory': folder })
log.info({ 'total jobs': len(models) * options.generate.batch_size, 'per-model': options.generate.batch_size })
log.info(json.dumps(options, indent=2))
for model in models:
fn = os.path.join(dir, os.path.basename(model) + options.format)
fn = os.path.join(folder, os.path.basename(model) + options.format)
if os.path.exists(fn) and len(params.input) == 0: # if model preview exists and not manually included
log.info({ 'model preview exists': model })
continue
@@ -122,8 +120,8 @@ async def models(params):
images = []
labels = []
t0 = time.time()
for label, prompt in prompts:
options.generate.prompt = prompt
for label, p in prompts:
options.generate.prompt = p
log.info({ 'model generating': model, 'label': label, 'prompt': options.generate.prompt })
data = await generate(options = options, quiet=True)
if 'image' in data:
@@ -139,7 +137,7 @@ async def models(params):
t = t1 - t0
its = 1.0 * options.generate.steps * len(images) / t
log.info({ 'model preview created': model, 'image': fn, 'images': len(images), 'grid': [image.width, image.height], 'time': round(t, 2), 'its': round(its, 2) })
opt = await get('/sdapi/v1/options')
if opt['sd_model_checkpoint'] != default and not params.fixed:
log.info({ 'model set default': default })
@@ -148,17 +146,17 @@ async def models(params):
async def lora(params):
cmdflags = await get('/sdapi/v1/cmd-flags')
dir = cmdflags['lora_dir']
if not os.path.exists(dir):
log.error({ 'lora directory not found': dir })
opt = await get('/sdapi/v1/options')
folder = opt['lora_dir']
if not os.path.exists(folder):
log.error({ 'lora directory not found': folder })
return
models1 = [f for f in Path(dir).glob('*.safetensors')]
models2 = [f for f in Path(dir).glob('*.ckpt')]
models1 = [f for f in Path(folder).glob('*.safetensors')]
models2 = [f for f in Path(folder).glob('*.ckpt')]
models = [f.stem for f in models1 + models2]
log.info({ 'loras': len(models) })
for model in models:
fn = os.path.join(dir, model + options.format)
fn = os.path.join(folder, model + options.format)
if os.path.exists(fn) and len(params.input) == 0: # if model preview exists and not manually included
log.info({ 'lora preview exists': model })
continue
@@ -166,7 +164,7 @@ async def lora(params):
labels = []
t0 = time.time()
import re
keywords = re.sub('\d', '', model)
keywords = re.sub(r'\d', '', model)
keywords = keywords.replace('-v', ' ').replace('-', ' ').strip().split(' ')
keyword = '\"' + '\" \"'.join(keywords) + '\"'
options.generate.prompt = prompt.replace('<keyword>', keyword)
@@ -188,16 +186,57 @@ async def lora(params):
log.info({ 'lora preview created': model, 'image': fn, 'images': len(images), 'grid': [image.width, image.height], 'time': round(t, 2), 'its': round(its, 2) })
async def hypernetwork(params):
cmdflags = await get('/sdapi/v1/cmd-flags')
dir = cmdflags['hypernetwork_dir']
if not os.path.exists(dir):
log.error({ 'hypernetwork directory not found': dir })
async def lyco(params):
opt = await get('/sdapi/v1/options')
folder = opt['lyco_dir']
if not os.path.exists(folder):
log.error({ 'lyco directory not found': folder })
return
models = [f.stem for f in Path(dir).glob('*.pt')]
log.info({ 'loras': len(models) })
models1 = [f for f in Path(folder).glob('*.safetensors')]
models2 = [f for f in Path(folder).glob('*.ckpt')]
models = [f.stem for f in models1 + models2]
log.info({ 'lycos': len(models) })
for model in models:
fn = os.path.join(dir, model + options.format)
fn = os.path.join(folder, model + options.format)
if os.path.exists(fn) and len(params.input) == 0: # if model preview exists and not manually included
log.info({ 'lyco preview exists': model })
continue
images = []
labels = []
t0 = time.time()
import re
keywords = re.sub(r'\d', '', model)
keywords = keywords.replace('-v', ' ').replace('-', ' ').strip().split(' ')
keyword = '\"' + '\" \"'.join(keywords) + '\"'
options.generate.prompt = prompt.replace('<keyword>', keyword)
options.generate.prompt = options.generate.prompt.replace('<embedding>', '')
options.generate.prompt += f' <lyco:{model}:{options.lora.strength}>'
log.info({ 'lyco generating': model, 'keyword': keyword, 'prompt': options.generate.prompt })
data = await generate(options = options, quiet=True)
if 'image' in data:
for img in data['image']:
images.append(img)
labels.append(keyword)
else:
log.error({ 'lyco': model, 'keyword': keyword, 'error': data })
t1 = time.time()
image = grid(images = images, labels = labels, border = 8)
image.save(fn)
t = t1 - t0
its = 1.0 * options.generate.steps * len(images) / t
log.info({ 'lyco preview created': model, 'image': fn, 'images': len(images), 'grid': [image.width, image.height], 'time': round(t, 2), 'its': round(its, 2) })
async def hypernetwork(params):
opt = await get('/sdapi/v1/options')
folder = opt['hypernetwork_dir']
if not os.path.exists(folder):
log.error({ 'hypernetwork directory not found': folder })
return
models = [f.stem for f in Path(folder).glob('*.pt')]
log.info({ 'hypernetworks': len(models) })
for model in models:
fn = os.path.join(folder, model + options.format)
if os.path.exists(fn) and len(params.input) == 0: # if model preview exists and not manually included
log.info({ 'hypernetwork preview exists': model })
continue
@@ -225,8 +264,9 @@ async def hypernetwork(params):
async def create_previews(params):
await models(params)
await preview_models(params)
await lora(params)
await lyco(params)
await hypernetwork(params)
await close()
@@ -236,5 +276,5 @@ if __name__ == '__main__':
parser.add_argument('--output', type = str, default = '', required = False, help = 'output directory')
parser.add_argument('--fixed', default = False, action='store_true', help = "do not change model")
parser.add_argument('input', type = str, nargs = '*')
params = parser.parse_args()
asyncio.run(create_previews(params))
args = parser.parse_args()
asyncio.run(create_previews(args))