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sd-extension-system-info
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update sysinfo 

Signed-off-by: Vladimir Mandic <mandic00@live.com>
pull/55/head
Vladimir Mandic 2025-01-02 14:06:53 -05:00
parent dfa01ce99a
commit aafc660ba3
3 changed files with 97 additions and 74 deletions
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28
benchmark.py
View File

@ -6,14 +6,14 @@ from modules.processing import StableDiffusionProcessingTxt2Img, Processed, proc
log = logging.getLogger('sd') log = logging.getLogger('sd')
args = { default_args = {
'sd_model': None, # 'sd_model': None,
'prompt': 'postapocalyptic steampunk city, exploration, cinematic, realistic, hyper detailed, photorealistic maximum detail, volumetric light, (((focus))), wide-angle, (((brightly lit))), (((vegetation))), lightning, vines, destruction, devastation, wartorn, ruins', 'prompt': 'postapocalyptic steampunk city, exploration, cinematic, realistic, hyper detailed, photorealistic maximum detail, volumetric light, (((focus))), wide-angle, (((brightly lit))), (((vegetation))), lightning, vines, destruction, devastation, wartorn, ruins',
'sampler_name': 'Euler a', 'sampler_name': 'Euler a',
'batch_size': 1, 'batch_size': 1,
'n_iter': 1, 'n_iter': 1,
'steps': 10, 'steps': 10,
'cfg_scale': 15.0, 'cfg_scale': 7.0,
'width': 512, 'width': 512,
'height': 512, 'height': 512,
'do_not_save_samples': True, 'do_not_save_samples': True,
@ -21,14 +21,26 @@ args = {
'negative_prompt': '(((blurry))), ((foggy)), (((dark))), ((monochrome)), sun, (((depth of field)))', 'negative_prompt': '(((blurry))), ((foggy)), (((dark))), ((monochrome)), sun, (((depth of field)))',
'do_not_reload_embeddings': True 'do_not_reload_embeddings': True
} }
args = {}
def run_benchmark(batch: int, extra: bool): def run_benchmark(batch: int, steps: str, width: int, height: int):
global args # pylint: disable=global-statement
shared.state.begin('Benchmark') shared.state.begin('Benchmark')
if args['sd_model'] is None: args = default_args.copy()
args['sd_model'] = shared.sd_model # if args['sd_model'] is None:
# args['sd_model'] = shared.sd_model
args['batch_size'] = batch args['batch_size'] = batch
args['steps'] = 20 if not extra else 50 if steps == 'turbo':
args['steps'] = 10
elif steps == 'long':
args['steps'] = 50
else:
args['steps'] = 20
if width and width > 0:
args['width'] = int(width)
if height and height > 0:
args['height'] = int(height)
mp = 0 mp = 0
p = StableDiffusionProcessingTxt2Img(**args) p = StableDiffusionProcessingTxt2Img(**args)
t0 = time.time() t0 = time.time()
@ -47,6 +59,8 @@ def run_benchmark(batch: int, extra: bool):
mp += image.width * image.height mp += image.width * image.height
except Exception as e: except Exception as e:
log.error(f'SD-System-Info benchmark error: {batch} {e}') log.error(f'SD-System-Info benchmark error: {batch} {e}')
from modules import errors
errors.display(e, 'Benchmark')
return 'error' return 'error'
t1 = time.time() t1 = time.time()
shared.state.end() shared.state.end()

20
pages/benchmark.html
View File

@ -89,16 +89,16 @@
const grid = new Grid({ const grid = new Grid({
columns: [ columns: [
{ name: '', id: 'id', width: '50px', formatter: (cell) => html(`<span style="color: #67d2d2">${cell}</span>`) }, { name: '', id: 'id', width: '50px', formatter: (cell) => html(`<span style="color: #67d2d2">${cell}</span>`) },
{ name: 'Date', width: '130px', formatter: (cell) => `${new Date(cell).toLocaleString()}` }, { name: 'date', width: '130px', formatter: (cell) => `${new Date(cell).toLocaleString()}` },
{ name: 'Performance', formatter: (cell) => html(`<b>${cell.replace(/\//g, 'it/s<br>')} it/s</b>`), sort: { compare: (a, b) => perfSort(a, b) } }, { name: 'it/s', formatter: (cell) => html(`<b>${cell.replace(/\//g, 'it/s<br>')} it/s</b>`), sort: { compare: (a, b) => perfSort(a, b) } },
{ name: 'Version', width: '260px', formatter: (cell) => html(`${text2url(cell)}`) }, { name: 'version', width: '260px', formatter: (cell) => html(`${text2url(cell)}`) },
{ name: 'System', width: '400px', formatter: (cell) => html(attrs(cell)) }, { name: 'system', width: '400px', formatter: (cell) => html(attrs(cell)) },
{ name: 'Libraries', width: '300px', formatter: (cell) => html(attrs(cell)) }, { name: 'libraries', width: '300px', formatter: (cell) => html(attrs(cell)) },
{ name: 'GPU', width: '260px', formatter: (cell) => html(`${attrs(cell.replace('device:', ''))}`) }, { name: 'gpu', width: '260px', formatter: (cell) => html(`${attrs(cell.replace('device:', ''))}`) },
{ name: 'Optimizations', formatter: (cell) => html(cell.replace(/ /g, '<br>').toLowerCase()) }, { name: 'optimizations', formatter: (cell) => html(cell.replace(/ /g, '<br>').toLowerCase()) },
{ name: 'Model', width: '260px', formatter: (cell) => html(`<span style="color: bisque">${cell.split(/\/|\\/).pop().replace(/\[/g, '<br>[')}</span>`) }, { name: 'settings', width: '260px', formatter: (cell) => html(`<span style="color: bisque">${cell.split(/\/|\\/).pop().replace(/\[/g, '<br>[')}</span>`) },
{ name: 'Username' }, { name: 'username' },
{ name: 'Note', formatter: (cell) => html(`<span style="font-size: 0.9rem">${attrs(cell?.replace('device:', '') || '')}</span>`) }, { name: 'note', formatter: (cell) => html(`<span style="font-size: 0.9rem">${attrs(cell?.replace('device:', '') || '')}</span>`) },
], ],
pagination: { pagination: {
limit: 200, limit: 200,

123
scripts/system-info.py
View File

@ -10,7 +10,7 @@ from html.parser import HTMLParser
import torch import torch
import gradio as gr import gradio as gr
from modules import paths, script_callbacks, sd_models, sd_samplers, shared, extensions, devices from modules import paths, script_callbacks, sd_models, sd_samplers, shared, extensions, devices
from benchmark import run_benchmark, submit_benchmark # pylint: disable=E0401,E0611,C0411 import benchmark # pylint: disable=wrong-import-order
### system info globals ### system info globals
@ -25,7 +25,7 @@ data = {
'gpu': {}, 'gpu': {},
'state': {}, 'state': {},
'memory': {}, 'memory': {},
'optimizations': [], 'flags': [],
'libs': {}, 'libs': {},
'repos': {}, 'repos': {},
'device': {}, 'device': {},
@ -34,7 +34,7 @@ data = {
'platform': '', 'platform': '',
'crossattention': '', 'crossattention': '',
'backend': getattr(devices, 'backend', ''), 'backend': getattr(devices, 'backend', ''),
'pipeline': shared.opts.data.get('sd_backend', ''), 'pipeline': ('native' if shared.native else 'original') if hasattr(shared, 'native') else 'a1111',
'model': {}, 'model': {},
} }
networks = { networks = {
@ -50,7 +50,7 @@ networks = {
bench_text = '' bench_text = ''
bench_file = os.path.join(os.path.dirname(__file__), 'benchmark-data-local.json') bench_file = os.path.join(os.path.dirname(__file__), 'benchmark-data-local.json')
bench_headers = ['timestamp', 'performance', 'version', 'system', 'libraries', 'gpu', 'pipeline', 'model', 'username', 'note', 'hash'] bench_headers = ['timestamp', 'it/s', 'version', 'system', 'libraries', 'gpu', 'flags', 'settings', 'username', 'note', 'hash']
bench_data = [] bench_data = []
### system info module ### system info module
@ -202,7 +202,7 @@ def get_memory():
return mem return mem
def get_optimizations(): def get_flags():
ram = [] ram = []
if getattr(shared.cmd_opts, 'medvram', False): if getattr(shared.cmd_opts, 'medvram', False):
ram.append('medvram') ram.append('medvram')
@ -311,32 +311,13 @@ def get_crossattention():
def get_model(): def get_model():
from modules.sd_models import model_data
import modules.sd_vae
obj = { obj = {
'configured': { 'base': shared.opts.data.get('sd_model_checkpoint', 'none'),
'base': shared.opts.data.get('sd_model_checkpoint', ''), 'refiner': shared.opts.data.get('sd_model_refiner', 'none'),
'refiner': shared.opts.data.get('sd_model_refiner', ''), 'vae': shared.opts.data.get('sd_vae', 'none'),
'vae': shared.opts.data.get('sd_vae', ''), 'te': shared.opts.data.get('sd_text_encoder', 'none'),
}, 'unet': shared.opts.data.get('sd_unet', 'none'),
'loaded': {
'base': '',
'refiner': '',
'vae': '',
}
} }
try:
obj['loaded']['base'] = model_data.sd_model.sd_checkpoint_info.filename if model_data.sd_model is not None and hasattr(model_data.sd_model, 'sd_checkpoint_info') else ''
except Exception :
pass
try:
obj['loaded']['refiner'] = model_data.sd_refiner.sd_checkpoint_info.filename if model_data.sd_refiner is not None and hasattr(model_data.sd_refiner, 'sd_checkpoint_info') else ''
except Exception :
pass
try:
obj['loaded']['vae'] = modules.sd_vae.loaded_vae_file
except Exception:
pass
return obj return obj
@ -384,7 +365,7 @@ def get_full_data():
'gpu': get_gpu(), 'gpu': get_gpu(),
'state': get_state(), 'state': get_state(),
'memory': get_memory(), 'memory': get_memory(),
'optimizations': get_optimizations(), 'flags': get_flags(),
'libs': get_libs(), 'libs': get_libs(),
'repos': get_repos(), 'repos': get_repos(),
'device': get_device(), 'device': get_device(),
@ -394,7 +375,7 @@ def get_full_data():
'platform': get_platform(), 'platform': get_platform(),
'crossattention': get_crossattention(), 'crossattention': get_crossattention(),
'backend': getattr(devices, 'backend', ''), 'backend': getattr(devices, 'backend', ''),
'pipeline': shared.opts.data.get('sd_backend', ''), 'pipeline': ('native' if shared.native else 'original') if hasattr(shared, 'native') else 'a1111',
} }
global networks # pylint: disable=global-statement global networks # pylint: disable=global-statement
networks = { networks = {
@ -432,7 +413,7 @@ def refresh_info_quick(_old_data = None):
def refresh_info_full(): def refresh_info_full():
get_full_data() get_full_data()
return data['uptime'], dict2text(data['version']), dict2text(data['state']), dict2text(data['memory']), dict2text(data['platform']), data['torch'], dict2text(data['gpu']), list2text(data['optimizations']), data['crossattention'], data['backend'], data['pipeline'], dict2text(data['libs']), dict2text(data['repos']), dict2text(data['device']), dict2text(data['model']), networks['models'], networks['loras'], data['timestamp'], data return data['uptime'], dict2text(data['version']), dict2text(data['state']), dict2text(data['memory']), dict2text(data['platform']), data['torch'], dict2text(data['gpu']), list2text(data['flags']), data['crossattention'], data['backend'], data['pipeline'], dict2text(data['libs']), dict2text(data['repos']), dict2text(data['device']), dict2text(data['model']), networks['models'], networks['loras'], data['timestamp'], data
### ui definition ### ui definition
@ -475,7 +456,7 @@ def create_ui(blocks: gr.Blocks = None):
torchtxt = gr.Textbox(data['torch'], label = 'Torch', lines = 1) torchtxt = gr.Textbox(data['torch'], label = 'Torch', lines = 1)
gputxt = gr.Textbox(dict2text(data['gpu']), label = 'GPU', lines = len(data['gpu'])) gputxt = gr.Textbox(dict2text(data['gpu']), label = 'GPU', lines = len(data['gpu']))
with gr.Row(): with gr.Row():
opttxt = gr.Textbox(list2text(data['optimizations']), label = 'Memory optimization') opttxt = gr.Textbox(list2text(data['flags']), label = 'Memory optimization')
attentiontxt = gr.Textbox(data['crossattention'], label = 'Cross-attention') attentiontxt = gr.Textbox(data['crossattention'], label = 'Cross-attention')
with gr.Column(): with gr.Column():
libstxt = gr.Textbox(dict2text(data['libs']), label = 'Libs', lines = len(data['libs'])) libstxt = gr.Textbox(dict2text(data['libs']), label = 'Libs', lines = len(data['libs']))
@ -495,25 +476,28 @@ def create_ui(blocks: gr.Blocks = None):
with gr.Row(): with gr.Row():
benchmark_data = gr.DataFrame(bench_data, label = 'Benchmark Data', elem_id = 'system_info_benchmark_data', show_label = True, interactive = False, wrap = True, overflow_row_behaviour = 'paginate', max_rows = 10, headers = bench_headers) benchmark_data = gr.DataFrame(bench_data, label = 'Benchmark Data', elem_id = 'system_info_benchmark_data', show_label = True, interactive = False, wrap = True, overflow_row_behaviour = 'paginate', max_rows = 10, headers = bench_headers)
with gr.Row(): with gr.Row():
with gr.Column(scale=3): with gr.Column(scale=1):
username = gr.Textbox(get_user, label = 'Username', placeholder='enter username for submission', elem_id='system_info_tab_username') username = gr.Textbox(get_user, label = 'Username', placeholder='enter username for submission', elem_id='system_info_tab_username')
with gr.Column(scale=6):
note = gr.Textbox('', label = 'Note', placeholder='enter any additional notes', elem_id='system_info_tab_note') note = gr.Textbox('', label = 'Note', placeholder='enter any additional notes', elem_id='system_info_tab_note')
with gr.Column(scale=1): with gr.Row():
with gr.Accordion('Settings'):
warmup = gr.Checkbox(label = 'Perform warmup', value = True, elem_id = 'system_info_tab_warmup')
with gr.Row(): with gr.Row():
warmup = gr.Checkbox(label = 'Perform warmup', value = True, elem_id = 'system_info_tab_warmup') steps = gr.Dropdown(['turbo', 'default', 'long'], value = 'normal', label = 'Benchmark steps', elem_id = 'system_info_tab_steps')
extra = gr.Checkbox(label = 'Extra steps', value = False, elem_id = 'system_info_tab_extra') level = gr.Dropdown(['quick', 'normal', 'extensive', 'ludicrous'], value = 'normal', label = 'Benchmark level', elem_id = 'system_info_tab_level')
level = gr.Radio(['quick', 'normal', 'extensive'], value = 'normal', label = 'Benchmark level', elem_id = 'system_info_tab_level') with gr.Row():
# batches = gr.Textbox('1, 2, 4, 8', label = 'Batch sizes', elem_id = 'system_info_tab_batch_size', interactive = False) width = gr.Number(512, label = 'Image width', elem_id = 'system_info_tab_width')
with gr.Column(scale=1): height = gr.Number(512, label = 'Image height', elem_id = 'system_info_tab_height')
with gr.Column():
bench_run_btn = gr.Button('Run benchmark', elem_id = 'system_info_tab_benchmark_btn', variant='primary') bench_run_btn = gr.Button('Run benchmark', elem_id = 'system_info_tab_benchmark_btn', variant='primary')
bench_run_btn.click(bench_init, inputs = [username, note, warmup, level, extra], outputs = [benchmark_data]) bench_run_btn.click(bench_init, inputs = [username, note, warmup, level, steps, width, height], outputs = [benchmark_data])
bench_submit_btn = gr.Button('Submit results', elem_id = 'system_info_tab_submit_btn', variant='primary') bench_submit_btn = gr.Button('Submit results', elem_id = 'system_info_tab_submit_btn', variant='primary')
bench_submit_btn.click(bench_submit, inputs = [username], outputs = []) bench_submit_btn.click(bench_submit, inputs = [username], outputs = [])
_bench_link = gr.HTML('<a href="https://vladmandic.github.io/sd-extension-system-info/pages/benchmark.html" target="_blank">Link to online results</a>') _bench_link = gr.HTML('<a href="https://vladmandic.github.io/sd-extension-system-info/pages/benchmark.html" target="_blank">Link to online results</a>')
with gr.Row(): _bench_note = gr.HTML(elem_id = 'system_info_tab_bench_note', value = """
_bench_note = gr.HTML(elem_id = 'system_info_tab_bench_note', value = """ <span>performance is measured in iterations per second (it/s) and reported for different batch sizes (e.g. 1, 2, 4, 8, 16...)</span><br>
<span>performance is measured in iterations per second (it/s) and reported for different batch sizes (e.g. 1, 2, 4, 8, 16...)</span><br> <span>running benchmark may take a while. extensive tests may result in gpu out-of-memory conditions.</span>""")
<span>running benchmark may take a while. extensive tests may result in gpu out-of-memory conditions.</span>""")
with gr.Row(): with gr.Row():
bench_label = gr.HTML('', elem_id = 'system_info_tab_bench_label') bench_label = gr.HTML('', elem_id = 'system_info_tab_bench_label')
refresh_bench_btn = gr.Button('Refresh bench', elem_id = 'system_info_tab_refresh_bench_btn', visible = False) # quick refresh is used from js interval refresh_bench_btn = gr.Button('Refresh bench', elem_id = 'system_info_tab_refresh_bench_btn', visible = False) # quick refresh is used from js interval
@ -545,27 +529,50 @@ def bench_submit(username: str):
if username is None or username == '': if username is None or username == '':
log.error('SD-System-Info: username is required to submit results') log.error('SD-System-Info: username is required to submit results')
return return
submit_benchmark(bench_data, username) benchmark.submit_benchmark(bench_data, username)
log.info(f'SD-System-Info: benchmark data submitted: {len(bench_data)} records') log.info(f'SD-System-Info: benchmark data submitted: {len(bench_data)} records')
def bench_run(batches: list = [1], extra: bool = False): def bench_run(batches: list = [1], steps: str = 'normal', width: int = 512, height: int = 512):
results = [] results = []
for batch in batches: for batch in batches:
log.debug(f'SD-System-Info: benchmark starting: batch={batch}') log.debug(f'SD-System-Info: benchmark starting: batch={batch}')
res = run_benchmark(batch, extra) res = benchmark.run_benchmark(batch, steps, width, height)
log.info(f'SD-System-Info: benchmark batch={batch} its={res}') log.info(f'SD-System-Info: benchmark batch={batch} its={res}')
results.append(str(res)) results.append(str(res))
its = ' / '.join(results) its = ' / '.join(results)
return its return its
def bench_init(username: str, note: str, warmup: bool, level: str, extra: bool): def get_settings():
settings = {
'pipeline': shared.sd_model.__class__.__name__,
'model': shared.opts.data.get('sd_model_checkpoint', 'none').lower(),
'vae': shared.opts.data.get('sd_vae', 'none').lower(),
'width': benchmark.args.get('width', 512),
'height': benchmark.args.get('height', 512),
}
return settings
def get_optimizations():
optimizations = {
'pipeline': data['pipeline'],
'crossattention': data['crossattention'],
'flags': ','.join(data['flags']).strip(),
'compute': str(devices.backend) if hasattr(devices, 'backend') else 'unknown',
'compile': shared.opts.data.get('cuda_compile_backend', 'none'),
'dtype': str(devices.dtype) if hasattr(devices, 'dtype') else 'unknown',
}
return optimizations
def bench_init(username: str, note: str, warmup: bool, level: str, steps: str, width: int, height: int):
from hashlib import sha256 from hashlib import sha256
log.debug('SD-System-Info: benchmark starting') log.debug('SD-System-Info: benchmark starting')
get_full_data() get_full_data()
hash256 = sha256((dict2str(data['platform']) + data['torch'] + dict2str(data['libs']) + dict2str(data['gpu']) + ','.join(data['optimizations']) + data['crossattention']).encode('utf-8')).hexdigest()[:6] hash256 = sha256((dict2str(data['platform']) + data['torch'] + dict2str(data['libs']) + dict2str(data['gpu']) + ','.join(data['flags']) + data['crossattention']).encode('utf-8')).hexdigest()[:6]
existing = [x for x in bench_data if (x[-1] is not None and x[-1][:6] == hash256)] existing = [x for x in bench_data if (x[-1] is not None and x[-1][:6] == hash256)]
if len(existing) > 0: if len(existing) > 0:
log.debug('SD-System-Info: benchmark replacing existing entry') log.debug('SD-System-Info: benchmark replacing existing entry')
@ -583,26 +590,28 @@ def bench_init(username: str, note: str, warmup: bool, level: str, extra: bool):
batches = [1, 2, 4] batches = [1, 2, 4]
elif level == 'extensive': elif level == 'extensive':
batches = [1, 2, 4, 8, 16] batches = [1, 2, 4, 8, 16]
elif level == 'ludicrous':
batches = [1, 2, 4, 8, 16, 32, 64]
else: else:
batches = [] batches = []
if warmup: if warmup:
bench_run([1], False) bench_run([1], False, width, height)
try: try:
mem = data['memory']['gpu']['total'] mem = data['memory']['gpu']['total']
except Exception: except Exception:
mem = 0 mem = 0
# bench_headers = ['timestamp', 'performance', 'version', 'system', 'libraries', 'gpu', 'optimizations', 'model', 'username', 'note', 'hash'] # bench_headers = ['timestamp', 'performance', 'version', 'system', 'libraries', 'gpu', 'flags', 'settings', 'username', 'note', 'hash']
d[0] = str(datetime.datetime.now()) d[0] = str(datetime.datetime.now())
d[1] = bench_run(batches, extra) d[1] = bench_run(batches, steps, width, height)
d[2] = dict2str(data['version']) d[2] = dict2str(data['version'])
d[3] = dict2str(data['platform']) d[3] = dict2str(data['platform'])
d[4] = f"torch:{data['torch']} {dict2str(data['libs'])}" d[4] = f"torch:{data['torch']} {dict2str(data['libs'])}"
d[5] = dict2str(data['gpu']) + f' {str(round(mem))}GB' d[5] = dict2str(data['gpu']) + f' {str(round(mem))}GB'
d[6] = (data['pipeline'] + ' ' + data['crossattention'] + ' ' + ','.join(data['optimizations'])).strip() d[6] = dict2str(get_optimizations())
d[7] = shared.opts.data['sd_model_checkpoint'] d[7] = dict2str(get_settings())
d[8] = username d[8] = username
d[9] = note d[9] = note
d[10] = hash256 d[10] = hash256
@ -668,7 +677,7 @@ class StatusRes(BaseModel): # definition of http response
platform: Optional[dict] = Field(title="Platform", description="Server platform") platform: Optional[dict] = Field(title="Platform", description="Server platform")
torch: Optional[str] = Field(title="Torch", description="Torch version") torch: Optional[str] = Field(title="Torch", description="Torch version")
gpu: Optional[dict] = Field(title="GPU", description="GPU info") gpu: Optional[dict] = Field(title="GPU", description="GPU info")
optimizations: Optional[list] = Field(title="Optimizations", description="Memory optimizations") flags: Optional[list] = Field(title="Optimizations", description="Memory optimizations")
crossatention: Optional[str] = Field(title="CrossAttention", description="Cross-attention optimization") crossatention: Optional[str] = Field(title="CrossAttention", description="Cross-attention optimization")
device: Optional[dict] = Field(title="Device", description="Device info") device: Optional[dict] = Field(title="Device", description="Device info")
backend: Optional[str] = Field(title="Backend", description="Backend") backend: Optional[str] = Field(title="Backend", description="Backend")
@ -693,7 +702,7 @@ def get_status_api(req: StatusReq = Depends()):
res.platform = data['platform'] res.platform = data['platform']
res.torch = data['torch'] res.torch = data['torch']
res.gpu = data['gpu'] res.gpu = data['gpu']
res.optimizations = data['optimizations'] res.flags = data['flags']
res.crossatention = data['crossattention'] res.crossatention = data['crossattention']
res.device = data['device'] res.device = data['device']
res.backend = data['backend'] res.backend = data['backend']