mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
288e31fc60
- This replaces the original clipseg library with the transformers version from HuggingFace. - This should make it possible to register InvokeAI at PyPi and do a fully automated pip-based install. - Minor regression: it is no longer possible to specify which device the clipseg model will be loaded into, and it will reside in CPU. However, performance is more than acceptable.
91 lines
2.9 KiB
Python
91 lines
2.9 KiB
Python
'''
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ldm.invoke.globals defines a small number of global variables that would
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otherwise have to be passed through long and complex call chains.
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It defines a Namespace object named "Globals" that contains
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the attributes:
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- root - the root directory under which "models" and "outputs" can be found
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- initfile - path to the initialization file
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- try_patchmatch - option to globally disable loading of 'patchmatch' module
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- always_use_cpu - force use of CPU even if GPU is available
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'''
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import os
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import os.path as osp
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from pathlib import Path
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from argparse import Namespace
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from typing import Union
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Globals = Namespace()
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# This is usually overwritten by the command line and/or environment variables
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if os.environ.get('INVOKEAI_ROOT'):
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Globals.root = osp.abspath(os.environ.get('INVOKEAI_ROOT'))
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elif os.environ.get('VIRTUAL_ENV'):
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Globals.root = osp.abspath(osp.join(os.environ.get('VIRTUAL_ENV'), '..'))
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else:
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Globals.root = osp.abspath(osp.expanduser('~/invokeai'))
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# Where to look for the initialization file
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Globals.initfile = 'invokeai.init'
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Globals.models_file = 'models.yaml'
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Globals.models_dir = 'models'
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Globals.config_dir = 'configs'
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Globals.autoscan_dir = 'weights'
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# Try loading patchmatch
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Globals.try_patchmatch = True
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# Use CPU even if GPU is available (main use case is for debugging MPS issues)
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Globals.always_use_cpu = False
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# Whether the internet is reachable for dynamic downloads
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# The CLI will test connectivity at startup time.
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Globals.internet_available = True
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# Whether to disable xformers
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Globals.disable_xformers = False
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# whether we are forcing full precision
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Globals.full_precision = False
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def global_config_file()->Path:
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return Path(Globals.root, Globals.config_dir, Globals.models_file)
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def global_config_dir()->Path:
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return Path(Globals.root, Globals.config_dir)
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def global_models_dir()->Path:
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return Path(Globals.root, Globals.models_dir)
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def global_autoscan_dir()->Path:
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return Path(Globals.root, Globals.autoscan_dir)
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def global_set_root(root_dir:Union[str,Path]):
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Globals.root = root_dir
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def global_cache_dir(subdir:Union[str,Path]='')->Path:
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'''
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Returns Path to the model cache directory. If a subdirectory
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is provided, it will be appended to the end of the path, allowing
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for huggingface-style conventions:
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global_cache_dir('diffusers')
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global_cache_dir('hub')
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global_cache_dir('transformers') # not used?
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'''
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home: str = os.getenv('HF_HOME')
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if home is None:
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home = os.getenv('XDG_CACHE_HOME')
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if home is not None:
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# Set `home` to $XDG_CACHE_HOME/huggingface, which is the default location mentioned in HuggingFace Hub Client Library.
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# See: https://huggingface.co/docs/huggingface_hub/main/en/package_reference/environment_variables#xdgcachehome
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home += os.sep + 'huggingface'
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if home is not None:
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return Path(home,subdir)
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else:
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return Path(Globals.root,'models',subdir)
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