mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
023db8ac41
This PR ports the `main` PR #2871 to the v2.3 branch. This adjusts the global diffusers model cache to work with the 0.14 diffusers layout of placing models in HF_HOME/hub rather than HF_HOME/diffusers.
113 lines
3.9 KiB
Python
113 lines
3.9 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 argparse import Namespace
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from pathlib import Path
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from typing import Union
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Globals = Namespace()
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# Where to look for the initialization file and other key components
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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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Globals.converted_ckpts_dir = 'converted_ckpts'
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# Set the default root directory. This can be overwritten by explicitly
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# passing the `--root <directory>` argument on the command line.
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# logic is:
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# 1) use INVOKEAI_ROOT environment variable (no check for this being a valid directory)
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# 2) use VIRTUAL_ENV environment variable, with a check for initfile being there
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# 3) use ~/invokeai
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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') and Path(os.environ.get('VIRTUAL_ENV'),'..',Globals.initfile).exists():
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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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# 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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# Low-memory tradeoff for guidance calculations.
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Globals.sequential_guidance = False
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# whether we are forcing full precision
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Globals.full_precision = False
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# whether we should convert ckpt files into diffusers models on the fly
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Globals.ckpt_convert = False
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# logging tokenization everywhere
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Globals.log_tokenization = 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_converted_ckpts_dir()->Path:
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return Path(global_models_dir(), Globals.converted_ckpts_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 Hugging Face-style conventions. Currently, Hugging Face has
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moved all models into the "hub" subfolder, so for any pretrained
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HF model, use:
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global_cache_dir('hub')
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The legacy location for transformers used to be global_cache_dir('transformers')
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and global_cache_dir('diffusers') for diffusers.
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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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