mirror of
https://github.com/vladmandic/sdnext.git
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68 lines
2.7 KiB
Python
68 lines
2.7 KiB
Python
from __future__ import annotations
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import re
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import sys
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import logging
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import warnings
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import urllib3
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from modules import timer, errors
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initialized = False
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logging.getLogger("DeepSpeed").disabled = True
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# os.environ.setdefault('OMP_NUM_THREADS', 1)
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# os.environ.setdefault('MKL_NUM_THREADS', 1)
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# import tensorflow as tf # pylint: disable=C0411
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import torch # pylint: disable=C0411
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# torch.set_num_threads(1)
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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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errors.log.debug(f'Load IPEX=={ipex.__version__}')
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except Exception:
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pass
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urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
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warnings.filterwarnings(action="ignore", category=UserWarning, module="torchvision")
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import torchvision # pylint: disable=W0611,C0411
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import pytorch_lightning # pytorch_lightning should be imported after torch, but it re-enables warnings on import so import once to disable them # pylint: disable=W0611,C0411
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logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage())
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logging.getLogger("pytorch_lightning").disabled = True
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warnings.filterwarnings(action="ignore", category=DeprecationWarning)
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warnings.filterwarnings(action="ignore", category=FutureWarning)
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warnings.filterwarnings(action="ignore", category=UserWarning, module="torchvision")
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if ".dev" in torch.__version__ or "+git" in torch.__version__:
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torch.__long_version__ = torch.__version__
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torch.__version__ = re.search(r'[\d.]+[\d]', torch.__version__).group(0)
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timer.startup.record("torch")
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from fastapi import FastAPI # pylint: disable=W0611,C0411
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import gradio # pylint: disable=W0611,C0411
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timer.startup.record("gradio")
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errors.install([gradio])
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import diffusers # pylint: disable=W0611,C0411
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timer.startup.record("diffusers")
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errors.log.info(f'Load packages: torch={getattr(torch, "__long_version__", torch.__version__)} diffusers={diffusers.__version__} gradio={gradio.__version__}')
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try:
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import os
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import math
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cores = os.cpu_count()
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affinity = len(os.sched_getaffinity(0))
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threads = torch.get_num_threads()
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if threads < (affinity / 2):
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torch.set_num_threads(math.floor(affinity / 2))
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threads = torch.get_num_threads()
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errors.log.debug(f'Detected: cores={cores} affinity={affinity} set threads={threads}')
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except Exception:
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pass
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try: # fix changed import in torchvision 0.17+, which breaks basicsr
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import torchvision.transforms.functional_tensor # pylint: disable=unused-import, ungrouped-imports
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except ImportError:
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try:
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import torchvision.transforms.functional as functional
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sys.modules["torchvision.transforms.functional_tensor"] = functional
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except ImportError:
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pass # shrug...
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