616 lines
25 KiB
Python
616 lines
25 KiB
Python
import os
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import sys
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import time
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import json
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import platform
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import subprocess
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import datetime
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from hashlib import sha256
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from html.parser import HTMLParser
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import torch
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try:
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import intel_extension_for_pytorch as ipex # pylint: disable=import-error, unused-import
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except:
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pass
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import accelerate
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import gradio as gr
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import psutil
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import transformers
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from modules import paths, script_callbacks, sd_hijack, sd_models, sd_samplers, shared, extensions, devices
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from modules.ui_components import FormRow
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from scripts.benchmark import run_benchmark, submit_benchmark # pylint: disable=E0401,E0611
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### system info globals
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data = {
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'date': '',
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'timestamp': '',
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'uptime': '',
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'version': '',
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'torch': '',
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'gpu': {},
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'state': {},
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'memory': {},
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'optimizations': '',
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'libs': {},
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'repos': {},
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'device': {},
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'models': [],
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'hypernetworks': [],
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'embeddings': [],
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'skipped': [],
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'loras': [],
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'lycos': [],
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'schedulers': [],
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'extensions': [],
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'platform': '',
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'crossattention': '',
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}
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### benchmark globals
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bench_text = ''
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bench_file = os.path.join(os.path.dirname(__file__), 'benchmark-data-local.json')
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bench_headers = ['timestamp', 'performance', 'version', 'system', 'libraries', 'gpu', 'optimizations', 'model', 'username', 'note', 'hash']
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bench_data = []
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console_logging = None
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### system info module
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def get_user():
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user = ''
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if user == '':
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try:
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user = os.getlogin()
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except:
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pass
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if user == '':
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try:
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import pwd
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user = pwd.getpwuid(os.getuid())[0]
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except:
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pass
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return user
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def get_gpu():
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if not torch.cuda.is_available():
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try:
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return {
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'device': f'{torch.xpu.get_device_name(torch.xpu.current_device())} ({str(torch.xpu.device_count())})',
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'ipex': str(ipex.__version__),
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}
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except:
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return {}
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else:
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try:
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if torch.version.cuda:
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return {
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'device': f'{torch.cuda.get_device_name(torch.cuda.current_device())} ({str(torch.cuda.device_count())}) ({torch.cuda.get_arch_list()[-1]}) {str(torch.cuda.get_device_capability(shared.device))}',
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'cuda': torch.version.cuda,
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'cudnn': torch.backends.cudnn.version(),
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}
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elif torch.version.hip:
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return {
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'device': f'{torch.cuda.get_device_name(torch.cuda.current_device())} ({str(torch.cuda.device_count())})',
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'hip': torch.version.hip,
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}
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else:
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return {
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'device': 'unknown'
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}
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except Exception as e:
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return { 'error': e }
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def get_uptime():
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s = vars(shared.state)
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return time.strftime('%c', time.localtime(s.get('server_start', time.time())))
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class HTMLFilter(HTMLParser):
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text = ""
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def handle_data(self, data): # pylint: disable=redefined-outer-name
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self.text += data
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def get_state():
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s = vars(shared.state)
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flags = 'skipped ' if s.get('skipped', False) else ''
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flags += 'interrupted ' if s.get('interrupted', False) else ''
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flags += 'needs restart' if s.get('need_restart', False) else ''
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text = s.get('textinfo', '')
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if text is not None and len(text) > 0:
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f = HTMLFilter()
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f.feed(text)
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text = os.linesep.join([s for s in f.text.splitlines() if s])
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return {
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'started': time.strftime('%c', time.localtime(s.get('time_start', time.time()))),
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'step': f'{s.get("sampling_step", 0)} / {s.get("sampling_steps", 0)}',
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'jobs': f'{s.get("job_no", 0)} / {s.get("job_count", 0)}', # pylint: disable=consider-using-f-string
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'flags': flags,
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'job': s.get('job', ''),
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'text-info': text,
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}
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def get_memory():
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def gb(val: float):
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return round(val / 1024 / 1024 / 1024, 2)
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mem = {}
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try:
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process = psutil.Process(os.getpid())
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res = process.memory_info()
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ram_total = 100 * res.rss / process.memory_percent()
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ram = { 'free': gb(ram_total - res.rss), 'used': gb(res.rss), 'total': gb(ram_total) }
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mem.update({ 'ram': ram })
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except Exception as e:
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mem.update({ 'ram': e })
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if torch.cuda.is_available():
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try:
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s = torch.cuda.mem_get_info()
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gpu = { 'free': gb(s[0]), 'used': gb(s[1] - s[0]), 'total': gb(s[1]) }
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s = dict(torch.cuda.memory_stats(shared.device))
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allocated = { 'current': gb(s['allocated_bytes.all.current']), 'peak': gb(s['allocated_bytes.all.peak']) }
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reserved = { 'current': gb(s['reserved_bytes.all.current']), 'peak': gb(s['reserved_bytes.all.peak']) }
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active = { 'current': gb(s['active_bytes.all.current']), 'peak': gb(s['active_bytes.all.peak']) }
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inactive = { 'current': gb(s['inactive_split_bytes.all.current']), 'peak': gb(s['inactive_split_bytes.all.peak']) }
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warnings = { 'retries': s['num_alloc_retries'], 'oom': s['num_ooms'] }
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mem.update({
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'gpu': gpu,
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'gpu-active': active,
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'gpu-allocated': allocated,
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'gpu-reserved': reserved,
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'gpu-inactive': inactive,
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'events': warnings,
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'utilization': 0,
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})
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mem.update({ 'utilization': torch.cuda.utilization() }) # do this one separately as it may fail
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except:
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pass
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else:
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try:
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s = [(torch.xpu.get_device_properties(shared.device).total_memory - torch.xpu.memory_allocated()), torch.xpu.get_device_properties(shared.device).total_memory]
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gpu = { 'free': gb(s[0]), 'used': gb(s[1] - s[0]), 'total': gb(s[1]) }
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s = dict(torch.xpu.memory_stats(shared.device))
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allocated = { 'current': gb(s['allocated_bytes.all.current']), 'peak': gb(s['allocated_bytes.all.peak']) }
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reserved = { 'current': gb(s['reserved_bytes.all.current']), 'peak': gb(s['reserved_bytes.all.peak']) }
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active = { 'current': gb(s['active_bytes.all.current']), 'peak': gb(s['active_bytes.all.peak']) }
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inactive = { 'current': gb(s['inactive_split_bytes.all.current']), 'peak': gb(s['inactive_split_bytes.all.peak']) }
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warnings = { 'retries': s['num_alloc_retries'], 'oom': s['num_ooms'] }
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mem.update({
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'gpu': gpu,
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'gpu-active': active,
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'gpu-allocated': allocated,
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'gpu-reserved': reserved,
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'gpu-inactive': inactive,
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'events': warnings,
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'utilization': 0,
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})
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except:
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pass
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return mem
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def get_optimizations():
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ram = []
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if shared.cmd_opts.medvram:
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ram.append('medvram')
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if shared.cmd_opts.lowvram:
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ram.append('lowvram')
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if shared.cmd_opts.lowram:
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ram.append('lowram')
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if len(ram) == 0:
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ram.append('none')
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return ram
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def get_libs():
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try:
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import xformers # pylint: disable=import-outside-toplevel, import-error
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xversion = xformers.__version__
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except:
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xversion = 'unavailable'
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return {
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'xformers': xversion,
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'accelerate': accelerate.__version__,
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'transformers': transformers.__version__,
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}
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def get_repos():
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repos = {}
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for key, val in paths.paths.items():
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try:
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cmd = f'git -C {val} log --pretty=format:"%h %ad" -1 --date=short'
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res = subprocess.run(f'{cmd} {val}', stdout = subprocess.PIPE, stderr = subprocess.PIPE, shell=True, check=True)
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stdout = res.stdout.decode(encoding = 'utf8', errors='ignore') if len(res.stdout) > 0 else ''
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words = stdout.split(' ')
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repos[key] = f'[{words[0]}] {words[1]}'
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except:
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repos[key] = '(unknown)'
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return repos
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def get_platform():
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try:
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if platform.system() == 'Windows':
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release = platform.platform(aliased = True, terse = False)
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else:
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release = platform.release()
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return {
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# 'host': platform.node(),
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'arch': platform.machine(),
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'cpu': platform.processor(),
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'system': platform.system(),
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'release': release,
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# 'platform': platform.platform(aliased = True, terse = False),
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# 'version': platform.version(),
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'python': platform.python_version(),
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}
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except Exception as e:
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return { 'error': e }
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def get_torch():
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try:
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ver = torch.__long_version__
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except:
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ver = torch.__version__
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return f"{ver} {shared.cmd_opts.precision} {' nohalf' if shared.cmd_opts.no_half else ' half'}"
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def get_version():
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version = None
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if version is None:
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try:
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res = subprocess.run('git log --pretty=format:"%h %ad" -1 --date=short', stdout = subprocess.PIPE, stderr = subprocess.PIPE, shell=True, check=True)
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ver = res.stdout.decode(encoding = 'utf8', errors='ignore') if len(res.stdout) > 0 else ''
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githash, updated = ver.split(' ')
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res = subprocess.run('git remote get-url origin', stdout = subprocess.PIPE, stderr = subprocess.PIPE, shell=True, check=True)
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origin = res.stdout.decode(encoding = 'utf8', errors='ignore') if len(res.stdout) > 0 else ''
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res = subprocess.run('git branch --show-current', stdout = subprocess.PIPE, stderr = subprocess.PIPE, shell=True, check=True)
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branch = res.stdout.decode(encoding = 'utf8', errors='ignore') if len(res.stdout) > 0 else ''
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version = {
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'updated': updated,
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'hash': githash,
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'url': origin.replace('\n', '') + '/tree/' + branch.replace('\n', '')
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}
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except:
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pass
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return version
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def get_embeddings():
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return sorted([f'{v} ({sd_hijack.model_hijack.embedding_db.word_embeddings[v].vectors})' for i, v in enumerate(sd_hijack.model_hijack.embedding_db.word_embeddings)])
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def get_skipped():
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return sorted([k for k in sd_hijack.model_hijack.embedding_db.skipped_embeddings.keys()])
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def get_crossattention():
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try:
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ca = sd_hijack.model_hijack.optimization_method
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if ca is None:
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return 'none'
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else: return ca
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except:
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return 'unknown'
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def get_models():
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return sorted([x.title for x in sd_models.checkpoints_list.values()])
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def get_samplers():
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return sorted([sampler[0] for sampler in sd_samplers.all_samplers])
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def get_extensions():
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return sorted([f"{e.name} ({'enabled' if e.enabled else 'disabled'}{' builtin' if e.is_builtin else ''})" for e in extensions.extensions])
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def get_loras():
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loras = []
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try:
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sys.path.append(extensions.extensions_builtin_dir)
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from Lora import lora # pylint: disable=E0401
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loras = sorted([l for l in lora.available_loras.keys()])
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except:
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pass
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return loras
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def get_lycos():
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return []
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def get_device():
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dev = {
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'active': str(devices.device),
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'dtype': str(devices.dtype),
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'vae': str(devices.dtype_vae),
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'unet': str(devices.dtype_unet),
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}
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return dev
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def get_full_data():
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global data # pylint: disable=global-statement
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data = {
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'date': datetime.datetime.now().strftime('%c'),
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'timestamp': datetime.datetime.now().strftime('%X'),
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'uptime': get_uptime(),
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'version': get_version(),
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'torch': get_torch(),
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'gpu': get_gpu(),
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'state': get_state(),
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'memory': get_memory(),
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'optimizations': get_optimizations(),
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'libs': get_libs(),
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'repos': get_repos(),
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'device': get_device(),
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'models': get_models(),
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'hypernetworks': [name for name in shared.hypernetworks],
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'embeddings': get_embeddings(),
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'skipped': get_skipped(),
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'loras': get_loras(),
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'lycos': get_lycos(),
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'schedulers': get_samplers(),
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'extensions': get_extensions(),
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'platform': get_platform(),
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'crossattention': get_crossattention(),
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}
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return data
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def get_quick_data():
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data['timestamp'] = datetime.datetime.now().strftime('%X')
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data['state'] = get_state()
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data['memory'] = get_memory()
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def list2text(lst: list):
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return '\n'.join(lst)
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def dict2str(d: dict):
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arr = [f'{name}:{d[name]}' for i, name in enumerate(d)]
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return ' '.join(arr)
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def dict2text(d: dict):
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arr = ['{name}: {val}'.format(name = name, val = d[name] if not type(d[name]) is dict else dict2str(d[name])) for i, name in enumerate(d)] # pylint: disable=consider-using-f-string
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return list2text(arr)
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def refresh_info_quick(_old_data):
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get_quick_data()
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return dict2text(data['state']), dict2text(data['memory']), data['crossattention'], data['timestamp'], data
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def refresh_info_full():
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get_full_data()
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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'], dict2text(data['libs']), dict2text(data['repos']), dict2text(data['device']), data['models'], data['hypernetworks'], data['embeddings'], data['skipped'], data['loras'], data['lycos'], data['timestamp'], data
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### ui definition
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def on_ui_tabs():
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# get_full_data()
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with gr.Blocks(analytics_enabled = False) as system_info:
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with gr.Row(elem_id = 'system_info'):
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with gr.Column(scale = 9):
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with gr.Box():
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with gr.Row():
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with gr.Column():
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uptimetxt = gr.Textbox(data['uptime'], label = 'Server start time', lines = 1)
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versiontxt = gr.Textbox(dict2text(data['version']), label = 'Version', lines = len(data['version']))
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with gr.Column():
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statetxt = gr.Textbox(dict2text(data['state']), label = 'State', lines = len(data['state']))
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with gr.Column():
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memorytxt = gr.Textbox(dict2text(data['memory']), label = 'Memory', lines = len(data['memory']))
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with gr.Box():
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with gr.Row():
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with gr.Column():
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platformtxt = gr.Textbox(dict2text(data['platform']), label = 'Platform', lines = len(data['platform']))
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with gr.Column():
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torchtxt = gr.Textbox(data['torch'], label = 'Torch', lines = 1)
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gputxt = gr.Textbox(dict2text(data['gpu']), label = 'GPU', lines = len(data['gpu']))
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with gr.Row():
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opttxt = gr.Textbox(list2text(data['optimizations']), label = 'Memory optimization')
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attentiontxt = gr.Textbox(data['crossattention'], label = 'Cross-attention')
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with gr.Column():
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libstxt = gr.Textbox(dict2text(data['libs']), label = 'Libs', lines = len(data['libs']))
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repostxt = gr.Textbox(dict2text(data['repos']), label = 'Repos', lines = len(data['repos']))
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devtxt = gr.Textbox(dict2text(data['device']), label = 'Device Info', lines = len(data['device']))
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with gr.Box():
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with gr.Accordion('Benchmarks...', open = True, visible = True):
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bench_load()
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with gr.Row():
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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)
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with gr.Row():
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with gr.Column(scale=3):
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username = gr.Textbox(get_user, label = 'Username', placeholder='enter username for submission', elem_id='system_info_tab_username')
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note = gr.Textbox('', label = 'Note', placeholder='enter any additional notes', elem_id='system_info_tab_note')
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with gr.Column(scale=1):
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with FormRow():
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global console_logging # pylint: disable=global-statement
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console_logging = gr.Checkbox(label = 'Console logging', value = False, elem_id = 'system_info_tab_console', interactive = True)
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warmup = gr.Checkbox(label = 'Perform warmup', value = True, elem_id = 'system_info_tab_warmup')
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extra = gr.Checkbox(label = 'Extra steps', value = False, elem_id = 'system_info_tab_extra')
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level = gr.Radio(['quick', 'normal', 'extensive'], value = 'normal', label = 'Benchmark level', elem_id = 'system_info_tab_level')
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# batches = gr.Textbox('1, 2, 4, 8', label = 'Batch sizes', elem_id = 'system_info_tab_batch_size', interactive = False)
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with gr.Column(scale=1):
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bench_run_btn = gr.Button('Run benchmark', elem_id = 'system_info_tab_benchmark_btn', variant='primary').style()
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bench_run_btn.click(bench_init, inputs = [username, note, warmup, level, extra], outputs = [benchmark_data])
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bench_submit_btn = gr.Button('Submit results', elem_id = 'system_info_tab_submit_btn', variant='primary').style()
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bench_submit_btn.click(bench_submit, inputs = [username], outputs = [])
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_bench_link = gr.HTML('<a href="https://vladmandic.github.io/sd-extension-system-info/pages/benchmark.html" target="_blank">Link to online results</a>')
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with gr.Row():
|
|
_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>running benchmark may take a while. extensive tests may result in gpu out-of-memory conditions.</span>""")
|
|
with gr.Row():
|
|
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).style(full_width = False) # quick refresh is used from js interval
|
|
refresh_bench_btn.click(bench_refresh, inputs = [], outputs = [bench_label])
|
|
with gr.Box():
|
|
with gr.Accordion('Models...', open = False, visible = True):
|
|
with gr.Row():
|
|
with gr.Column():
|
|
models = gr.JSON(data['models'], label = 'Models', lines = len(data['models']))
|
|
hypernetworks = gr.JSON(data['hypernetworks'], label = 'Hypernetworks', lines = len(data['hypernetworks']))
|
|
with gr.Column():
|
|
embeddings = gr.JSON(data['embeddings'], label = 'Embeddings: loaded', lines = len(data['embeddings']))
|
|
skipped = gr.JSON(data['skipped'], label = 'Embeddings: skipped', lines = len(data['embeddings']))
|
|
loras = gr.JSON(data['loras'], label = 'Available LORA', lines = len(data['loras']))
|
|
lycos = gr.JSON(data['lycos'], label = 'Available LyCORIS', lines = len(data['lycos']))
|
|
with gr.Box():
|
|
with gr.Accordion('Info object', open = False, visible = True):
|
|
# reduce json data to avoid private info
|
|
data.pop('models', None)
|
|
data.pop('embeddings', None)
|
|
data.pop('skipped', None)
|
|
data.pop('hypernetworks', None)
|
|
data.pop('schedulers', None)
|
|
data.pop('loras', None)
|
|
js = gr.JSON(data)
|
|
with gr.Column(scale = 1, min_width = 120):
|
|
timestamp = gr.Text(default=data['timestamp'], label = '', elem_id = 'system_info_tab_last_update')
|
|
gr.HTML('Load<br><div id="si-sparkline-load"></div>')
|
|
gr.HTML('Memory<br><div id="si-sparkline-memo"></div>')
|
|
refresh_quick_btn = gr.Button('Refresh state', elem_id = 'system_info_tab_refresh_btn', visible = False).style() # quick refresh is used from js interval
|
|
refresh_quick_btn.click(refresh_info_quick, _js='receive_system_info', show_progress = False,
|
|
inputs = [js],
|
|
outputs = [statetxt, memorytxt, attentiontxt, timestamp, js]
|
|
)
|
|
refresh_full_btn = gr.Button('Refresh data', elem_id = 'system_info_tab_refresh_full_btn', variant='primary').style()
|
|
refresh_full_btn.click(refresh_info_full, show_progress = False,
|
|
inputs = [],
|
|
outputs = [uptimetxt, versiontxt, statetxt, memorytxt, platformtxt, torchtxt, gputxt, opttxt, attentiontxt, libstxt, repostxt, devtxt, models, hypernetworks, embeddings, skipped, loras, lycos, timestamp, js]
|
|
)
|
|
interrupt_btn = gr.Button('Send interrupt', elem_id = 'system_info_tab_interrupt_btn', variant='primary')
|
|
interrupt_btn.click(shared.state.interrupt, inputs = [], outputs = [])
|
|
return (system_info, 'System Info', 'system_info'),
|
|
|
|
|
|
### benchmarking module
|
|
|
|
def bench_log(msg: str):
|
|
global bench_text # pylint: disable=global-statement
|
|
bench_text = msg
|
|
if console_logging is not None and console_logging.value:
|
|
print('benchmark', msg)
|
|
|
|
|
|
def bench_submit(username: str):
|
|
if username is None or username == '':
|
|
bench_log('username is required to submit results')
|
|
return
|
|
submit_benchmark(bench_data, username, console_logging.value)
|
|
bench_log(f'data submitted: {len(bench_data)} records')
|
|
|
|
|
|
def bench_run(batches: list = [1], extra: bool = False):
|
|
results = []
|
|
for batch in batches:
|
|
bench_log(f'running for batch size {batch}')
|
|
res = run_benchmark(batch, extra)
|
|
bench_log(f'results batch size {batch}: {res} it/s')
|
|
results.append(str(res))
|
|
its = ' / '.join(results)
|
|
return its
|
|
|
|
|
|
def bench_init(username: str, note: str, warmup: bool, level: str, extra: bool):
|
|
bench_log('starting')
|
|
hash256 = sha256((dict2str(data['platform']) + data['torch'] + dict2str(data['libs']) + dict2str(data['gpu']) + ','.join(data['optimizations']) + 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)]
|
|
if len(existing) > 0:
|
|
bench_log('replacing existing entry')
|
|
d = existing[0]
|
|
elif bench_data[-1][0] is not None:
|
|
bench_log('new entry')
|
|
bench_data.append([None] * len(bench_headers))
|
|
d = bench_data[-1]
|
|
else:
|
|
d = bench_data[-1]
|
|
|
|
if level == 'quick':
|
|
batches = [1]
|
|
elif level == 'normal':
|
|
batches = [1, 2, 4]
|
|
elif level == 'extensive':
|
|
batches = [1, 2, 4, 8, 16]
|
|
else:
|
|
batches = []
|
|
|
|
model_hash = shared.opts.data['sd_model_checkpoint'].split('[')[-1].split(']')[0]
|
|
if model_hash != 'cc6cb27103':
|
|
bench_log('using non standard model')
|
|
|
|
if warmup:
|
|
bench_run([1], False)
|
|
|
|
try:
|
|
mem = data['memory']['gpu']['total']
|
|
except:
|
|
mem = 0
|
|
|
|
# bench_headers = ['timestamp', 'performance', 'version', 'system', 'libraries', 'gpu', 'optimizations', 'model', 'username', 'note', 'hash']
|
|
d[0] = str(datetime.datetime.now())
|
|
d[1] = bench_run(batches, extra)
|
|
d[2] = dict2str(data['version'])
|
|
d[3] = dict2str(data['platform'])
|
|
d[4] = f"torch:{data['torch']} {dict2str(data['libs'])}"
|
|
d[5] = dict2str(data['gpu']) + f' {str(round(mem))}GB'
|
|
d[6] = data['crossattention'] + ' ' + ','.join(data['optimizations'])
|
|
d[7] = shared.opts.data['sd_model_checkpoint']
|
|
d[8] = username
|
|
d[9] = note
|
|
d[10] = hash256
|
|
|
|
md = '| ' + ' | '.join(d) + ' |'
|
|
bench_log(md)
|
|
|
|
bench_save()
|
|
return bench_data
|
|
|
|
|
|
def bench_load():
|
|
global bench_data # pylint: disable=global-statement
|
|
tmp = []
|
|
if os.path.isfile(bench_file) and os.path.getsize(bench_file) > 0:
|
|
try:
|
|
with open(bench_file, 'r', encoding='utf-8') as f:
|
|
tmp = json.load(f)
|
|
bench_data = tmp
|
|
bench_log('data loaded: ' + bench_file)
|
|
except Exception as err:
|
|
bench_log('error loading: ' + bench_file + ' ' + str(err))
|
|
if len(bench_data) == 0:
|
|
bench_data.append([None] * len(bench_headers))
|
|
return bench_data
|
|
|
|
|
|
def bench_save():
|
|
if bench_data[-1][0] is None:
|
|
del bench_data[-1]
|
|
try:
|
|
with open(bench_file, 'w', encoding='utf-8') as f:
|
|
json.dump(bench_data, f, indent=2, default=str, skipkeys=True)
|
|
bench_log('data saved: ' + bench_file)
|
|
except Exception as err:
|
|
bench_log('error saving: ' + bench_file + ' ' + str(err))
|
|
|
|
|
|
def bench_refresh():
|
|
return gr.HTML.update(value = bench_text)
|
|
|
|
|
|
script_callbacks.on_ui_tabs(on_ui_tabs)
|