mirror of
https://github.com/vladmandic/automatic
synced 2026-09-19 09:14:35 +02:00
refactor initial installer
This commit is contained in:
Vladimir Mandic
+17
-4
@@ -4,13 +4,18 @@
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- StableDiffusion 3
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## Update for 2024-06-04
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## Update for 2024-06-08
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*Note*: New features require `diffusers==0.29.0.dev`
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### New Models
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- [Tenecent HunyuanDiT](https://github.com/Tencent/HunyuanDiT) bilingual english/chinese diffusion transformer model
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note: this is a very large model at ~17GB, but can be used with less VRAM using model offloading
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simply select from networks -> models -> reference, model will be auto-downloaded on first use
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### New Functionality
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- [MuLan](https://github.com/mulanai/MuLan) Multi-langunage prompts
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write your prompts forin ~110 auto-detected languages!
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compatible with *SD15* and *SDXL*
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@@ -44,13 +49,21 @@
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- add torch **full deterministic mode**
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enable in settings -> compute -> use deterministic mode
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typical differences are not large and its disabled by default as it does have some performance impact
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- lower overhead on generate calls
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- cumulative fixes since the last release
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- add python version check for torch-directml
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### Improvements
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- improved **installer** for initial installs
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initial install will do single-pass install of all required packages with correct versions
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subsequent runs will check package versions as necessary
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- add env variable `SD_PIP_DEBUG` to write `pip.log` for all pip operations
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also improved installer logging
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- add python version check for `torch-directml`
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- improve metadata/infotext parser
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add `cli/image-exif.py` that can be used to view/extract metadata from images
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- lower overhead on generate calls
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- auto-synchronize modernui and core branches
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- fix apply/unapply hidiffusion for sd15
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- cumulative fixes since the last release
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## Update for 2024-06-02
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+242
-205
@@ -26,6 +26,7 @@ version = None
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current_branch = None
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log = logging.getLogger("sd")
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debug = log.debug if os.environ.get('SD_INSTALL_DEBUG', None) is not None else lambda *args, **kwargs: None
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pip_log = '--log pip.log ' if os.environ.get('SD_PIP_DEBUG', None) is not None else ''
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log_file = os.path.join(os.path.dirname(__file__), 'sdnext.log')
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log_rolled = False
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first_call = True
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@@ -84,7 +85,10 @@ def setup_logging():
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def get(self):
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return self.buffer
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install('rich', 'rich')
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install('rich', 'rich', quiet=True)
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install('setuptools==69.5.1', 'setuptools', quiet=True)
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install('psutil', 'psutil', quiet=True)
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install('requests', 'requests', quiet=True)
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from functools import partial, partialmethod
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from logging.handlers import RotatingFileHandler
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from rich.theme import Theme
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@@ -233,11 +237,11 @@ def uninstall(package, quiet = False):
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@lru_cache()
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def pip(arg: str, ignore: bool = False, quiet: bool = False):
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arg = arg.replace('>=', '==')
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if not quiet:
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log.info(f'Installing package: {arg.replace("install", "").replace("--upgrade", "").replace("--no-deps", "").replace("--force", "").replace(" ", " ").strip()}')
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if not quiet and '-r ' not in arg:
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log.info(f'Install: package="{arg.replace("install", "").replace("--upgrade", "").replace("--no-deps", "").replace("--force", "").replace(" ", " ").strip()}"')
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env_args = os.environ.get("PIP_EXTRA_ARGS", "")
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log.debug(f"Running pip: {arg} {env_args}")
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result = subprocess.run(f'"{sys.executable}" -m pip {arg} {env_args}', shell=True, check=False, env=os.environ, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
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log.debug(f'Running: pip="{pip_log}{arg} {env_args}"')
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result = subprocess.run(f'"{sys.executable}" -m pip {pip_log}{arg} {env_args}', shell=True, check=False, env=os.environ, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
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txt = result.stdout.decode(encoding="utf8", errors="ignore")
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if len(result.stderr) > 0:
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txt += ('\n' if len(txt) > 0 else '') + result.stderr.decode(encoding="utf8", errors="ignore")
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@@ -253,14 +257,14 @@ def pip(arg: str, ignore: bool = False, quiet: bool = False):
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# install package using pip if not already installed
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@lru_cache()
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def install(package, friendly: str = None, ignore: bool = False, reinstall: bool = False, no_deps: bool = False):
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def install(package, friendly: str = None, ignore: bool = False, reinstall: bool = False, no_deps: bool = False, quiet: bool = False):
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res = ''
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if args.reinstall or args.upgrade:
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global quick_allowed # pylint: disable=global-statement
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quick_allowed = False
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if args.reinstall or reinstall or not installed(package, friendly, quiet=False):
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deps = '' if not no_deps else '--no-deps'
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res = pip(f"install --upgrade {deps} {package}", ignore=ignore)
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if args.reinstall or reinstall or not installed(package, friendly, quiet=quiet):
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deps = '' if not no_deps else '--no-deps '
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res = pip(f"install --upgrade {deps}{package}", ignore=ignore)
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try:
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import imp # pylint: disable=deprecated-module
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imp.reload(pkg_resources)
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@@ -388,10 +392,10 @@ def get_platform():
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# check python version
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def check_python(supported_minors=[9, 10, 11], reason=None):
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def check_python(supported_minors=[9, 10, 11, 12], reason=None):
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if args.quick:
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return
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log.info(f'Python {platform.python_version()} on {platform.system()}')
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log.info(f'Python version={platform.python_version()} platform={platform.system()} bin="{sys.executable}" venv="{sys.prefix}"')
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if not (int(sys.version_info.major) == 3 and int(sys.version_info.minor) in supported_minors):
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log.error(f"Incompatible Python version: {sys.version_info.major}.{sys.version_info.minor}.{sys.version_info.micro} required 3.{supported_minors}")
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if reason is not None:
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@@ -427,6 +431,212 @@ def check_onnx():
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install('onnxruntime', 'onnxruntime', ignore=True)
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def install_rocm_zluda(torch_command):
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is_windows = platform.system() == 'Windows'
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log.info('AMD ROCm toolkit detected')
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os.environ.setdefault('PYTORCH_HIP_ALLOC_CONF', 'garbage_collection_threshold:0.8,max_split_size_mb:512')
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if not is_windows:
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os.environ.setdefault('TENSORFLOW_PACKAGE', 'tensorflow-rocm')
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try:
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if is_windows:
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command = subprocess.run('hipinfo', shell=True, check=False, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
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amd_gpus = command.stdout.decode(encoding="utf8", errors="ignore").split('\n')
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amd_gpus = [x.split(' ')[-1].strip() for x in amd_gpus if x.startswith('gcnArchName:')]
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else:
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command = subprocess.run('rocm_agent_enumerator', shell=True, check=False, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
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amd_gpus = command.stdout.decode(encoding="utf8", errors="ignore").split('\n')
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amd_gpus = [x for x in amd_gpus if x and x != 'gfx000']
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log.debug(f'ROCm agents detected: {amd_gpus}')
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except Exception as e:
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log.debug(f'ROCm agent enumerator failed: {e}')
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amd_gpus = []
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hip_visible_devices = [] # use the first available amd gpu by default
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for idx, gpu in enumerate(amd_gpus):
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if gpu in ['gfx1100', 'gfx1101', 'gfx1102']:
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hip_visible_devices.append((idx, gpu, 'navi3x'))
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break
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if gpu in ['gfx1030', 'gfx1031', 'gfx1032', 'gfx1034']: # experimental navi 2x support
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hip_visible_devices.append((idx, gpu, 'navi2x'))
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break
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if len(hip_visible_devices) > 0:
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idx, gpu, arch = hip_visible_devices[0]
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log.debug(f'ROCm agent used by default: idx={idx} gpu={gpu} arch={arch}')
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os.environ.setdefault('HIP_VISIBLE_DEVICES', str(idx))
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if arch == 'navi3x':
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os.environ.setdefault('HSA_OVERRIDE_GFX_VERSION', '11.0.0')
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if os.environ.get('TENSORFLOW_PACKAGE') == 'tensorflow-rocm': # do not use tensorflow-rocm for navi 3x
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os.environ['TENSORFLOW_PACKAGE'] = 'tensorflow==2.13.0'
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elif arch == 'navi2x':
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os.environ.setdefault('HSA_OVERRIDE_GFX_VERSION', '10.3.0')
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else:
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log.debug(f'HSA_OVERRIDE_GFX_VERSION auto config is skipped for {gpu}')
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try:
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command = subprocess.run('hipconfig --version', shell=True, check=False, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
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arr = command.stdout.decode(encoding="utf8", errors="ignore").split('.')
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rocm_ver = f'{arr[0]}.{arr[1]}' if len(arr) >= 2 else None
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log.debug(f'ROCm version detected: {rocm_ver}')
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except Exception as e:
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log.debug(f'ROCm hipconfig failed: {e}')
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rocm_ver = None
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if args.use_zluda:
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log.warning("ZLUDA support: experimental")
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error = None
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from modules import zluda_installer
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try:
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if args.reinstall_zluda:
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zluda_installer.uninstall()
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if args.experimental:
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zluda_installer.enable_runtime_api()
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zluda_path = zluda_installer.get_path()
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zluda_installer.install(zluda_path)
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zluda_installer.make_copy(zluda_path)
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except Exception as e:
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error = e
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log.warning(f'Failed to install ZLUDA: {e}')
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if error is None:
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try:
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zluda_installer.load(zluda_path)
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torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.3.0 torchvision --index-url https://download.pytorch.org/whl/cu118')
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log.info(f'Using ZLUDA in {zluda_path}')
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except Exception as e:
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error = e
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log.warning(f'Failed to load ZLUDA: {e}')
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if error is not None:
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log.info('Using CPU-only torch')
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torch_command = os.environ.get('TORCH_COMMAND', 'torch torchvision')
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elif is_windows: # TODO TBD after ROCm for Windows is released
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log.warning("HIP SDK is detected, but no Torch release for Windows available")
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log.info("For ZLUDA support specify '--use-zluda'")
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log.info('Using CPU-only torch')
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torch_command = os.environ.get('TORCH_COMMAND', 'torch torchvision')
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# conceal ROCm installed
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os.environ.pop("ROCM_HOME", None)
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os.environ.pop("ROCM_PATH", None)
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paths = os.environ["PATH"].split(";")
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paths_no_rocm = []
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for path in paths:
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if "ROCm" not in path:
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paths_no_rocm.append(path)
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os.environ["PATH"] = ";".join(paths_no_rocm)
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else:
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if rocm_ver is None: # assume the latest if version check fails
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torch_command = os.environ.get('TORCH_COMMAND', 'torch torchvision --index-url https://download.pytorch.org/whl/rocm6.0')
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elif rocm_ver == "6.1": # need nightlies
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torch_command = os.environ.get('TORCH_COMMAND', 'torch torchvision --pre --index-url https://download.pytorch.org/whl/nightly/rocm6.1')
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elif float(rocm_ver) < 5.5: # oldest supported version is 5.5
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log.warning(f"Unsupported ROCm version detected: {rocm_ver}")
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log.warning("Minimum supported ROCm version is 5.5")
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torch_command = os.environ.get('TORCH_COMMAND', 'torch torchvision --index-url https://download.pytorch.org/whl/rocm5.5')
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else:
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torch_command = os.environ.get('TORCH_COMMAND', f'torch torchvision --index-url https://download.pytorch.org/whl/rocm{rocm_ver}')
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if rocm_ver is not None:
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ort_version = os.environ.get('ONNXRUNTIME_VERSION', None)
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ort_package = os.environ.get('ONNXRUNTIME_PACKAGE', f"--pre onnxruntime-training{'' if ort_version is None else ('==' + ort_version)} --index-url https://pypi.lsh.sh/{rocm_ver[0]}{rocm_ver[2]} --extra-index-url https://pypi.org/simple")
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install(ort_package, 'onnxruntime-training')
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return torch_command
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def install_ipex(torch_command):
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args.use_ipex = True # pylint: disable=attribute-defined-outside-init
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log.info('Intel OneAPI Toolkit detected')
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if os.environ.get("NEOReadDebugKeys", None) is None:
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os.environ.setdefault('NEOReadDebugKeys', '1')
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if os.environ.get("ClDeviceGlobalMemSizeAvailablePercent", None) is None:
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os.environ.setdefault('ClDeviceGlobalMemSizeAvailablePercent', '100')
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if "linux" in sys.platform:
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torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.1.0.post0 torchvision==0.16.0.post0 intel-extension-for-pytorch==2.1.20+xpu --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/')
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os.environ.setdefault('TENSORFLOW_PACKAGE', 'tensorflow==2.15.0 intel-extension-for-tensorflow[xpu]==2.15.0.0')
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if os.environ.get('DISABLE_VENV_LIBS', None) is None:
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install(os.environ.get('MKL_PACKAGE', 'mkl==2024.1.0'), 'mkl')
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install(os.environ.get('DPCPP_PACKAGE', 'mkl-dpcpp==2024.1.0'), 'mkl-dpcpp')
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install(os.environ.get('ONECCL_PACKAGE', 'oneccl-devel==2021.12.0'), 'oneccl-devel')
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install(os.environ.get('MPI_PACKAGE', 'impi-devel==2021.12.0'), 'impi-devel')
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else:
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if sys.version_info.minor == 11:
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pytorch_pip = 'https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.1.10%2Bxpu/torch-2.1.0a0+cxx11.abi-cp311-cp311-win_amd64.whl'
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torchvision_pip = 'https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.1.10%2Bxpu/torchvision-0.16.0a0+cxx11.abi-cp311-cp311-win_amd64.whl'
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ipex_pip = 'https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.1.10%2Bxpu/intel_extension_for_pytorch-2.1.10+xpu-cp311-cp311-win_amd64.whl'
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torch_command = os.environ.get('TORCH_COMMAND', f'{pytorch_pip} {torchvision_pip} {ipex_pip}')
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elif sys.version_info.minor == 10:
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pytorch_pip = 'https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.1.10%2Bxpu/torch-2.1.0a0+cxx11.abi-cp310-cp310-win_amd64.whl'
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torchvision_pip = 'https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.1.10%2Bxpu/torchvision-0.16.0a0+cxx11.abi-cp310-cp310-win_amd64.whl'
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ipex_pip = 'https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.1.10%2Bxpu/intel_extension_for_pytorch-2.1.10+xpu-cp310-cp310-win_amd64.whl'
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torch_command = os.environ.get('TORCH_COMMAND', f'{pytorch_pip} {torchvision_pip} {ipex_pip}')
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else:
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torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.1.0.post0 torchvision==0.16.0.post0 intel-extension-for-pytorch==2.1.20+xpu --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/')
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if os.environ.get('DISABLE_VENV_LIBS', None) is None:
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install(os.environ.get('MKL_PACKAGE', 'mkl==2024.1.0'), 'mkl')
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install(os.environ.get('DPCPP_PACKAGE', 'mkl-dpcpp==2024.1.0'), 'mkl-dpcpp')
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install(os.environ.get('ONECCL_PACKAGE', 'oneccl-devel==2021.12.0'), 'oneccl-devel')
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install(os.environ.get('MPI_PACKAGE', 'impi-devel==2021.12.0'), 'impi-devel')
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torch_command = os.environ.get('TORCH_COMMAND', f'{pytorch_pip} {torchvision_pip} {ipex_pip}')
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install(os.environ.get('OPENVINO_PACKAGE', 'openvino==2023.3.0'), 'openvino', ignore=True)
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install('nncf==2.7.0', 'nncf', ignore=True)
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install(os.environ.get('ONNXRUNTIME_PACKAGE', 'onnxruntime-openvino'), 'onnxruntime-openvino', ignore=True)
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return torch_command
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def install_openvino(torch_command):
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log.info('Using OpenVINO')
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torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.2.0 torchvision==0.17.0 --index-url https://download.pytorch.org/whl/cpu')
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install(os.environ.get('OPENVINO_PACKAGE', 'openvino==2023.3.0'), 'openvino')
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install(os.environ.get('ONNXRUNTIME_PACKAGE', 'onnxruntime-openvino'), 'onnxruntime-openvino', ignore=True)
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install('nncf==2.8.1', 'nncf')
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os.environ.setdefault('PYTORCH_TRACING_MODE', 'TORCHFX')
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if os.environ.get("NEOReadDebugKeys", None) is None:
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os.environ.setdefault('NEOReadDebugKeys', '1')
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if os.environ.get("ClDeviceGlobalMemSizeAvailablePercent", None) is None:
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os.environ.setdefault('ClDeviceGlobalMemSizeAvailablePercent', '100')
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return torch_command
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def is_rocm_available(allow_rocm):
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if not allow_rocm:
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return False
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if installed('torch-directml', quiet=True):
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log.debug('DirectML installation is detected. Skipping HIP SDK check.')
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return False
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if platform.system() == 'Windows':
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from modules.zluda_installer import find_hip_sdk
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return find_hip_sdk() is not None
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else:
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return shutil.which('rocminfo') is not None or os.path.exists('/opt/rocm/bin/rocminfo') or os.path.exists('/dev/kfd')
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def install_torch_addons():
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xformers_package = os.environ.get('XFORMERS_PACKAGE', '--pre xformers') if opts.get('cross_attention_optimization', '') == 'xFormers' or args.use_xformers else 'none'
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triton_command = os.environ.get('TRITON_COMMAND', 'triton') if sys.platform == 'linux' else None
|
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if 'xformers' in xformers_package:
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try:
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install(f'--no-deps {xformers_package}', ignore=True)
|
||||
import torch # pylint: disable=unused-import
|
||||
import xformers # pylint: disable=unused-import
|
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except Exception as e:
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log.debug(f'Cannot install xformers package: {e}')
|
||||
elif not args.experimental and not args.use_xformers and opts.get('cross_attention_optimization', '') != 'xFormers':
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uninstall('xformers')
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if opts.get('cuda_compile_backend', '') == 'hidet':
|
||||
install('hidet', 'hidet')
|
||||
if opts.get('cuda_compile_backend', '') == 'deep-cache':
|
||||
install('DeepCache')
|
||||
if opts.get('cuda_compile_backend', '') == 'olive-ai':
|
||||
install('olive-ai')
|
||||
if opts.get('nncf_compress_weights', False) and not args.use_openvino:
|
||||
install('nncf==2.7.0', 'nncf')
|
||||
if triton_command is not None:
|
||||
install(triton_command, 'triton', quiet=True)
|
||||
|
||||
|
||||
def is_cuda_available(allow_cuda):
|
||||
return allow_cuda and (shutil.which('nvidia-smi') is not None or args.use_xformers or os.path.exists(os.path.join(os.environ.get('SystemRoot') or r'C:\Windows', 'System32', 'nvidia-smi.exe')))
|
||||
|
||||
|
||||
def is_ipex_available(allow_ipex):
|
||||
return allow_ipex and (args.use_ipex or shutil.which('sycl-ls') is not None or shutil.which('sycl-ls.exe') is not None or os.environ.get('ONEAPI_ROOT') is not None or os.path.exists('/opt/intel/oneapi') or os.path.exists("C:/Program Files (x86)/Intel/oneAPI") or os.path.exists("C:/oneAPI"))
|
||||
|
||||
|
||||
# check torch version
|
||||
def check_torch():
|
||||
if args.skip_torch:
|
||||
@@ -443,179 +653,19 @@ def check_torch():
|
||||
log.debug(f'Torch overrides: cuda={args.use_cuda} rocm={args.use_rocm} ipex={args.use_ipex} diml={args.use_directml} openvino={args.use_openvino}')
|
||||
log.debug(f'Torch allowed: cuda={allow_cuda} rocm={allow_rocm} ipex={allow_ipex} diml={allow_directml} openvino={allow_openvino}')
|
||||
torch_command = os.environ.get('TORCH_COMMAND', '')
|
||||
xformers_package = os.environ.get('XFORMERS_PACKAGE', '--pre xformers') if opts.get('cross_attention_optimization', '') == 'xFormers' or args.use_xformers else 'none'
|
||||
triton_command = os.environ.get('TRITON_COMMAND', 'triton') if sys.platform == 'linux' else None
|
||||
|
||||
def is_rocm_available():
|
||||
if not allow_rocm:
|
||||
return False
|
||||
if installed('torch-directml', quiet=True):
|
||||
log.debug('DirectML installation is detected. Skipping HIP SDK check.')
|
||||
return False
|
||||
if platform.system() == 'Windows':
|
||||
from modules.zluda_installer import find_hip_sdk
|
||||
return find_hip_sdk() is not None
|
||||
else:
|
||||
return shutil.which('rocminfo') is not None or os.path.exists('/opt/rocm/bin/rocminfo') or os.path.exists('/dev/kfd')
|
||||
|
||||
if torch_command != '':
|
||||
pass
|
||||
elif allow_cuda and (shutil.which('nvidia-smi') is not None or args.use_xformers or os.path.exists(os.path.join(os.environ.get('SystemRoot') or r'C:\Windows', 'System32', 'nvidia-smi.exe'))):
|
||||
elif is_cuda_available(allow_cuda):
|
||||
log.info('nVidia CUDA toolkit detected: nvidia-smi present')
|
||||
torch_command = os.environ.get('TORCH_COMMAND', 'torch torchvision --index-url https://download.pytorch.org/whl/cu121')
|
||||
install('onnxruntime-gpu', 'onnxruntime-gpu', ignore=True)
|
||||
elif is_rocm_available():
|
||||
is_windows = platform.system() == 'Windows'
|
||||
log.info('AMD ROCm toolkit detected')
|
||||
os.environ.setdefault('PYTORCH_HIP_ALLOC_CONF', 'garbage_collection_threshold:0.8,max_split_size_mb:512')
|
||||
if not is_windows:
|
||||
os.environ.setdefault('TENSORFLOW_PACKAGE', 'tensorflow-rocm')
|
||||
try:
|
||||
if is_windows:
|
||||
command = subprocess.run('hipinfo', shell=True, check=False, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
|
||||
amd_gpus = command.stdout.decode(encoding="utf8", errors="ignore").split('\n')
|
||||
amd_gpus = [x.split(' ')[-1].strip() for x in amd_gpus if x.startswith('gcnArchName:')]
|
||||
else:
|
||||
command = subprocess.run('rocm_agent_enumerator', shell=True, check=False, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
|
||||
amd_gpus = command.stdout.decode(encoding="utf8", errors="ignore").split('\n')
|
||||
amd_gpus = [x for x in amd_gpus if x and x != 'gfx000']
|
||||
log.debug(f'ROCm agents detected: {amd_gpus}')
|
||||
except Exception as e:
|
||||
log.debug(f'ROCm agent enumerator failed: {e}')
|
||||
amd_gpus = []
|
||||
|
||||
hip_visible_devices = [] # use the first available amd gpu by default
|
||||
for idx, gpu in enumerate(amd_gpus):
|
||||
if gpu in ['gfx1100', 'gfx1101', 'gfx1102']:
|
||||
hip_visible_devices.append((idx, gpu, 'navi3x'))
|
||||
break
|
||||
if gpu in ['gfx1030', 'gfx1031', 'gfx1032', 'gfx1034']: # experimental navi 2x support
|
||||
hip_visible_devices.append((idx, gpu, 'navi2x'))
|
||||
break
|
||||
if len(hip_visible_devices) > 0:
|
||||
idx, gpu, arch = hip_visible_devices[0]
|
||||
log.debug(f'ROCm agent used by default: idx={idx} gpu={gpu} arch={arch}')
|
||||
os.environ.setdefault('HIP_VISIBLE_DEVICES', str(idx))
|
||||
if arch == 'navi3x':
|
||||
os.environ.setdefault('HSA_OVERRIDE_GFX_VERSION', '11.0.0')
|
||||
if os.environ.get('TENSORFLOW_PACKAGE') == 'tensorflow-rocm': # do not use tensorflow-rocm for navi 3x
|
||||
os.environ['TENSORFLOW_PACKAGE'] = 'tensorflow==2.13.0'
|
||||
elif arch == 'navi2x':
|
||||
os.environ.setdefault('HSA_OVERRIDE_GFX_VERSION', '10.3.0')
|
||||
else:
|
||||
log.debug(f'HSA_OVERRIDE_GFX_VERSION auto config is skipped for {gpu}')
|
||||
try:
|
||||
command = subprocess.run('hipconfig --version', shell=True, check=False, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
|
||||
arr = command.stdout.decode(encoding="utf8", errors="ignore").split('.')
|
||||
rocm_ver = f'{arr[0]}.{arr[1]}' if len(arr) >= 2 else None
|
||||
log.debug(f'ROCm version detected: {rocm_ver}')
|
||||
except Exception as e:
|
||||
log.debug(f'ROCm hipconfig failed: {e}')
|
||||
rocm_ver = None
|
||||
if args.use_zluda:
|
||||
log.warning("ZLUDA support: experimental")
|
||||
error = None
|
||||
from modules import zluda_installer
|
||||
try:
|
||||
if args.reinstall_zluda:
|
||||
zluda_installer.uninstall()
|
||||
if args.experimental:
|
||||
zluda_installer.enable_runtime_api()
|
||||
zluda_path = zluda_installer.get_path()
|
||||
zluda_installer.install(zluda_path)
|
||||
zluda_installer.make_copy(zluda_path)
|
||||
except Exception as e:
|
||||
error = e
|
||||
log.warning(f'Failed to install ZLUDA: {e}')
|
||||
if error is None:
|
||||
try:
|
||||
zluda_installer.load(zluda_path)
|
||||
torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.3.0 torchvision --index-url https://download.pytorch.org/whl/cu118')
|
||||
log.info(f'Using ZLUDA in {zluda_path}')
|
||||
except Exception as e:
|
||||
error = e
|
||||
log.warning(f'Failed to load ZLUDA: {e}')
|
||||
if error is not None:
|
||||
log.info('Using CPU-only torch')
|
||||
torch_command = os.environ.get('TORCH_COMMAND', 'torch torchvision')
|
||||
elif is_windows: # TODO TBD after ROCm for Windows is released
|
||||
log.warning("HIP SDK is detected, but no Torch release for Windows available")
|
||||
log.info("For ZLUDA support specify '--use-zluda'")
|
||||
log.info('Using CPU-only torch')
|
||||
torch_command = os.environ.get('TORCH_COMMAND', 'torch torchvision')
|
||||
|
||||
# conceal ROCm installed
|
||||
os.environ.pop("ROCM_HOME", None)
|
||||
os.environ.pop("ROCM_PATH", None)
|
||||
paths = os.environ["PATH"].split(";")
|
||||
paths_no_rocm = []
|
||||
for path in paths:
|
||||
if "ROCm" not in path:
|
||||
paths_no_rocm.append(path)
|
||||
os.environ["PATH"] = ";".join(paths_no_rocm)
|
||||
else:
|
||||
if rocm_ver is None: # assume the latest if version check fails
|
||||
torch_command = os.environ.get('TORCH_COMMAND', 'torch torchvision --index-url https://download.pytorch.org/whl/rocm6.0')
|
||||
elif rocm_ver == "6.1": # need nightlies
|
||||
torch_command = os.environ.get('TORCH_COMMAND', 'torch torchvision --pre --index-url https://download.pytorch.org/whl/nightly/rocm6.1')
|
||||
elif float(rocm_ver) < 5.5: # oldest supported version is 5.5
|
||||
log.warning(f"Unsupported ROCm version detected: {rocm_ver}")
|
||||
log.warning("Minimum supported ROCm version is 5.5")
|
||||
torch_command = os.environ.get('TORCH_COMMAND', 'torch torchvision --index-url https://download.pytorch.org/whl/rocm5.5')
|
||||
else:
|
||||
torch_command = os.environ.get('TORCH_COMMAND', f'torch torchvision --index-url https://download.pytorch.org/whl/rocm{rocm_ver}')
|
||||
if rocm_ver is not None:
|
||||
ort_version = os.environ.get('ONNXRUNTIME_VERSION', None)
|
||||
ort_package = os.environ.get('ONNXRUNTIME_PACKAGE', f"--pre onnxruntime-training{'' if ort_version is None else ('==' + ort_version)} --index-url https://pypi.lsh.sh/{rocm_ver[0]}{rocm_ver[2]} --extra-index-url https://pypi.org/simple")
|
||||
install(ort_package, 'onnxruntime-training')
|
||||
elif allow_ipex and (args.use_ipex or shutil.which('sycl-ls') is not None or shutil.which('sycl-ls.exe') is not None or os.environ.get('ONEAPI_ROOT') is not None or os.path.exists('/opt/intel/oneapi') or os.path.exists("C:/Program Files (x86)/Intel/oneAPI") or os.path.exists("C:/oneAPI")):
|
||||
args.use_ipex = True # pylint: disable=attribute-defined-outside-init
|
||||
log.info('Intel OneAPI Toolkit detected')
|
||||
if os.environ.get("NEOReadDebugKeys", None) is None:
|
||||
os.environ.setdefault('NEOReadDebugKeys', '1')
|
||||
if os.environ.get("ClDeviceGlobalMemSizeAvailablePercent", None) is None:
|
||||
os.environ.setdefault('ClDeviceGlobalMemSizeAvailablePercent', '100')
|
||||
if "linux" in sys.platform:
|
||||
torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.1.0.post0 torchvision==0.16.0.post0 intel-extension-for-pytorch==2.1.20+xpu --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/')
|
||||
os.environ.setdefault('TENSORFLOW_PACKAGE', 'tensorflow==2.15.0 intel-extension-for-tensorflow[xpu]==2.15.0.0')
|
||||
if os.environ.get('DISABLE_VENV_LIBS', None) is None:
|
||||
install(os.environ.get('MKL_PACKAGE', 'mkl==2024.1.0'), 'mkl')
|
||||
install(os.environ.get('DPCPP_PACKAGE', 'mkl-dpcpp==2024.1.0'), 'mkl-dpcpp')
|
||||
install(os.environ.get('ONECCL_PACKAGE', 'oneccl-devel==2021.12.0'), 'oneccl-devel')
|
||||
install(os.environ.get('MPI_PACKAGE', 'impi-devel==2021.12.0'), 'impi-devel')
|
||||
else:
|
||||
if sys.version_info.minor == 11:
|
||||
pytorch_pip = 'https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.1.10%2Bxpu/torch-2.1.0a0+cxx11.abi-cp311-cp311-win_amd64.whl'
|
||||
torchvision_pip = 'https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.1.10%2Bxpu/torchvision-0.16.0a0+cxx11.abi-cp311-cp311-win_amd64.whl'
|
||||
ipex_pip = 'https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.1.10%2Bxpu/intel_extension_for_pytorch-2.1.10+xpu-cp311-cp311-win_amd64.whl'
|
||||
torch_command = os.environ.get('TORCH_COMMAND', f'{pytorch_pip} {torchvision_pip} {ipex_pip}')
|
||||
elif sys.version_info.minor == 10:
|
||||
pytorch_pip = 'https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.1.10%2Bxpu/torch-2.1.0a0+cxx11.abi-cp310-cp310-win_amd64.whl'
|
||||
torchvision_pip = 'https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.1.10%2Bxpu/torchvision-0.16.0a0+cxx11.abi-cp310-cp310-win_amd64.whl'
|
||||
ipex_pip = 'https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.1.10%2Bxpu/intel_extension_for_pytorch-2.1.10+xpu-cp310-cp310-win_amd64.whl'
|
||||
torch_command = os.environ.get('TORCH_COMMAND', f'{pytorch_pip} {torchvision_pip} {ipex_pip}')
|
||||
else:
|
||||
torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.1.0.post0 torchvision==0.16.0.post0 intel-extension-for-pytorch==2.1.20+xpu --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/')
|
||||
if os.environ.get('DISABLE_VENV_LIBS', None) is None:
|
||||
install(os.environ.get('MKL_PACKAGE', 'mkl==2024.1.0'), 'mkl')
|
||||
install(os.environ.get('DPCPP_PACKAGE', 'mkl-dpcpp==2024.1.0'), 'mkl-dpcpp')
|
||||
install(os.environ.get('ONECCL_PACKAGE', 'oneccl-devel==2021.12.0'), 'oneccl-devel')
|
||||
install(os.environ.get('MPI_PACKAGE', 'impi-devel==2021.12.0'), 'impi-devel')
|
||||
torch_command = os.environ.get('TORCH_COMMAND', f'{pytorch_pip} {torchvision_pip} {ipex_pip}')
|
||||
install(os.environ.get('OPENVINO_PACKAGE', 'openvino==2023.3.0'), 'openvino', ignore=True)
|
||||
install('nncf==2.7.0', 'nncf', ignore=True)
|
||||
install(os.environ.get('ONNXRUNTIME_PACKAGE', 'onnxruntime-openvino'), 'onnxruntime-openvino', ignore=True)
|
||||
install('onnxruntime-gpu', 'onnxruntime-gpu', ignore=True, quiet=True)
|
||||
elif is_rocm_available(allow_rocm):
|
||||
torch_command = install_rocm_zluda(torch_command)
|
||||
elif is_ipex_available(allow_ipex):
|
||||
torch_command = install_ipex(torch_command)
|
||||
elif allow_openvino and args.use_openvino:
|
||||
log.info('Using OpenVINO')
|
||||
torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.2.0 torchvision==0.17.0 --index-url https://download.pytorch.org/whl/cpu')
|
||||
install(os.environ.get('OPENVINO_PACKAGE', 'openvino==2023.3.0'), 'openvino')
|
||||
install(os.environ.get('ONNXRUNTIME_PACKAGE', 'onnxruntime-openvino'), 'onnxruntime-openvino', ignore=True)
|
||||
install('nncf==2.8.1', 'nncf')
|
||||
os.environ.setdefault('PYTORCH_TRACING_MODE', 'TORCHFX')
|
||||
if os.environ.get("NEOReadDebugKeys", None) is None:
|
||||
os.environ.setdefault('NEOReadDebugKeys', '1')
|
||||
if os.environ.get("ClDeviceGlobalMemSizeAvailablePercent", None) is None:
|
||||
os.environ.setdefault('ClDeviceGlobalMemSizeAvailablePercent', '100')
|
||||
torch_command = install_openvino(torch_command)
|
||||
else:
|
||||
machine = platform.machine()
|
||||
if sys.platform == 'darwin':
|
||||
@@ -633,11 +683,7 @@ def check_torch():
|
||||
log.info('Using CPU-only Torch')
|
||||
torch_command = os.environ.get('TORCH_COMMAND', 'torch torchvision')
|
||||
if 'torch' in torch_command and not args.version:
|
||||
if not installed('torch', quiet=True):
|
||||
log.debug(f'Installing torch: {torch_command}')
|
||||
install(torch_command, 'torch torchvision')
|
||||
if triton_command is not None:
|
||||
install(triton_command, 'triton')
|
||||
install(torch_command, 'torch torchvision', quiet=True)
|
||||
else:
|
||||
try:
|
||||
import torch
|
||||
@@ -676,23 +722,7 @@ def check_torch():
|
||||
if args.version:
|
||||
return
|
||||
if not args.skip_all:
|
||||
try:
|
||||
if 'xformers' in xformers_package:
|
||||
install(f'--no-deps {xformers_package}', ignore=True)
|
||||
import torch
|
||||
import xformers # pylint: disable=unused-import
|
||||
elif not args.experimental and not args.use_xformers and opts.get('cross_attention_optimization', '') != 'xFormers':
|
||||
uninstall('xformers')
|
||||
except Exception as e:
|
||||
log.debug(f'Cannot install xformers package: {e}')
|
||||
if opts.get('cuda_compile_backend', '') == 'hidet':
|
||||
install('hidet', 'hidet')
|
||||
if opts.get('cuda_compile_backend', '') == 'deep-cache':
|
||||
install('DeepCache')
|
||||
if opts.get('cuda_compile_backend', '') == 'olive-ai':
|
||||
install('olive-ai')
|
||||
if opts.get('nncf_compress_weights', False) and not args.use_openvino:
|
||||
install('nncf==2.7.0', 'nncf')
|
||||
install_torch_addons()
|
||||
if args.profile:
|
||||
print_profile(pr, 'Torch')
|
||||
|
||||
@@ -724,12 +754,12 @@ def install_packages():
|
||||
pr.enable()
|
||||
log.info('Verifying packages')
|
||||
clip_package = os.environ.get('CLIP_PACKAGE', "git+https://github.com/openai/CLIP.git")
|
||||
install(clip_package, 'clip')
|
||||
install(clip_package, 'clip', quiet=True)
|
||||
tensorflow_package = os.environ.get('TENSORFLOW_PACKAGE', 'tensorflow==2.13.0')
|
||||
install(tensorflow_package, 'tensorflow-rocm' if 'rocm' in tensorflow_package else 'tensorflow', ignore=True)
|
||||
install(tensorflow_package, 'tensorflow-rocm' if 'rocm' in tensorflow_package else 'tensorflow', ignore=True, quiet=True)
|
||||
bitsandbytes_package = os.environ.get('BITSANDBYTES_PACKAGE', None)
|
||||
if bitsandbytes_package is not None:
|
||||
install(bitsandbytes_package, 'bitsandbytes', ignore=True)
|
||||
install(bitsandbytes_package, 'bitsandbytes', ignore=True, quiet=True)
|
||||
elif not args.experimental:
|
||||
uninstall('bitsandbytes')
|
||||
if args.profile:
|
||||
@@ -874,11 +904,18 @@ def install_requirements():
|
||||
pr.enable()
|
||||
if args.skip_requirements and not args.requirements:
|
||||
return
|
||||
if not installed('diffusers', quiet=True): # diffusers are not installed, so run initial installation
|
||||
global quick_allowed # pylint: disable=global-statement
|
||||
quick_allowed = False
|
||||
log.info('Installing requirements: this make take a while...')
|
||||
pip('install -r requirements.txt')
|
||||
installed('torch', reload=True) # reload packages cache
|
||||
log.info('Verifying requirements')
|
||||
with open('requirements.txt', 'r', encoding='utf8') as f:
|
||||
lines = [line.strip() for line in f.readlines() if line.strip() != '' and not line.startswith('#') and line is not None]
|
||||
for line in lines:
|
||||
_res = install(line)
|
||||
if not installed(line, quiet=True):
|
||||
_res = install(line)
|
||||
if args.profile:
|
||||
print_profile(pr, 'Requirements')
|
||||
|
||||
@@ -909,7 +946,7 @@ def set_environment():
|
||||
os.environ.setdefault('KINETO_LOG_LEVEL', '3')
|
||||
os.environ.setdefault('DO_NOT_TRACK', '1')
|
||||
os.environ.setdefault('HF_HUB_CACHE', opts.get('hfcache_dir', os.path.join(os.path.expanduser('~'), '.cache', 'huggingface', 'hub')))
|
||||
log.debug(f'HF cache folder: {os.environ.get("HF_HUB_CACHE")}')
|
||||
log.info(f'HF cache folder: {os.environ.get("HF_HUB_CACHE")}')
|
||||
allocator = f'garbage_collection_threshold:{opts.get("torch_gc_threshold", 80)/100:0.2f},max_split_size_mb:512'
|
||||
if opts.get("torch_malloc", "native") == 'cudaMallocAsync':
|
||||
allocator += ',backend:cudaMallocAsync'
|
||||
|
||||
@@ -215,26 +215,25 @@ def main():
|
||||
installer.log.info('Startup: skip all')
|
||||
installer.quick_allowed = True
|
||||
init_paths()
|
||||
elif installer.check_timestamp():
|
||||
installer.log.info('Startup: quick launch')
|
||||
installer.install_requirements()
|
||||
installer.install_packages()
|
||||
init_paths()
|
||||
installer.check_extensions()
|
||||
else:
|
||||
installer.log.info('Startup: standard')
|
||||
installer.install_requirements()
|
||||
installer.install_packages()
|
||||
installer.install_submodules()
|
||||
init_paths()
|
||||
installer.install_extensions()
|
||||
installer.install_requirements() # redo requirements since extensions may change them
|
||||
installer.update_wiki()
|
||||
if installer.errors == 0:
|
||||
installer.log.debug(f'Setup complete without errors: {round(time.time())}')
|
||||
if installer.check_timestamp():
|
||||
installer.log.info('Startup: quick launch')
|
||||
init_paths()
|
||||
installer.check_extensions()
|
||||
else:
|
||||
installer.log.warning(f'Setup complete with errors: {installer.errors}')
|
||||
installer.log.warning(f'See log file for more details: {installer.log_file}')
|
||||
installer.log.info('Startup: standard')
|
||||
installer.install_submodules()
|
||||
init_paths()
|
||||
installer.install_extensions()
|
||||
installer.install_requirements() # redo requirements since extensions may change them
|
||||
installer.update_wiki()
|
||||
if installer.errors == 0:
|
||||
installer.log.debug(f'Setup complete without errors: {round(time.time())}')
|
||||
else:
|
||||
installer.log.warning(f'Setup complete with errors: {installer.errors}')
|
||||
installer.log.warning(f'See log file for more details: {installer.log_file}')
|
||||
installer.extensions_preload(parser) # adds additional args from extensions
|
||||
args = installer.parse_args(parser)
|
||||
|
||||
|
||||
@@ -76,7 +76,7 @@ def unapply(pipe): # pylint: disable=arguments-differ
|
||||
try:
|
||||
if hasattr(pipe, 'set_ip_adapter_scale'):
|
||||
pipe.set_ip_adapter_scale(0)
|
||||
if hasattr(pipe, 'unet') and hasattr(pipe.unet, 'config')and pipe.unet.config.encoder_hid_dim_type == 'ip_image_proj':
|
||||
if hasattr(pipe, 'unet') and hasattr(pipe.unet, 'config') and pipe.unet.config.encoder_hid_dim_type == 'ip_image_proj':
|
||||
pipe.unet.encoder_hid_proj = None
|
||||
pipe.config.encoder_hid_dim_type = None
|
||||
pipe.unet.set_default_attn_processor()
|
||||
|
||||
@@ -72,8 +72,8 @@ def setup_model(dirname):
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
install('basicsr')
|
||||
install('gfpgan')
|
||||
install('basicsr', quiet=True)
|
||||
install('gfpgan', quiet=True)
|
||||
import gfpgan
|
||||
import facexlib
|
||||
import modules.face_restoration
|
||||
|
||||
@@ -73,8 +73,8 @@ fi
|
||||
|
||||
if [[ -f "${venv_dir}"/bin/activate ]]
|
||||
then
|
||||
echo "Activate python venv"
|
||||
source "${venv_dir}"/bin/activate
|
||||
echo "Activate python venv: $VIRTUAL_ENV"
|
||||
else
|
||||
echo "Error: Cannot activate python venv"
|
||||
exit 1
|
||||
@@ -103,6 +103,7 @@ then
|
||||
echo "Launch: ipexrun"
|
||||
exec ipexrun --multi-task-manager 'taskset' --memory-allocator 'jemalloc' launch.py "$@"
|
||||
else
|
||||
echo "Launch"
|
||||
PYTHON=`which python`
|
||||
echo "Launch: ${PYTHON}"
|
||||
exec "${PYTHON}" launch.py "$@"
|
||||
fi
|
||||
|
||||
Reference in New Issue
Block a user