mirror of
https://github.com/nod-ai/SHARK-Studio.git
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67 lines
2.5 KiB
Python
67 lines
2.5 KiB
Python
# This script will toggle the comment/uncommenting aspect for dealing
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# with __file__ AttributeError arising in case of a few modules in
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# `torch/_dynamo/skipfiles.py` (within shark.venv)
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from distutils.sysconfig import get_python_lib
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import fileinput
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from pathlib import Path
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# Temporary workaround for transformers/__init__.py.
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path_to_transformers_hook = Path(
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get_python_lib() + "/_pyinstaller_hooks_contrib/hooks/stdhooks/hook-transformers.py"
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)
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if path_to_transformers_hook.is_file():
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pass
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else:
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with open(path_to_transformers_hook, "w") as f:
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f.write("module_collection_mode = 'pyz+py'")
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path_to_skipfiles = Path(get_python_lib() + "/torch/_dynamo/skipfiles.py")
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modules_to_comment = ["abc,", "os,", "posixpath,", "_collections_abc,"]
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startMonitoring = 0
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for line in fileinput.input(path_to_skipfiles, inplace=True):
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if "SKIP_DIRS = " in line:
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startMonitoring = 1
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print(line, end="")
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elif startMonitoring in [1, 2]:
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if "]" in line:
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startMonitoring += 1
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print(line, end="")
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else:
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flag = True
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for module in modules_to_comment:
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if module in line:
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if not line.startswith("#"):
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print(f"#{line}", end="")
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else:
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print(f"{line[1:]}", end="")
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flag = False
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break
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if flag:
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print(line, end="")
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else:
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print(line, end="")
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# For getting around scikit-image's packaging, laze_loader has had a patch merged but yet to be released.
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# Refer: https://github.com/scientific-python/lazy_loader
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path_to_lazy_loader = Path(get_python_lib() + "/lazy_loader/__init__.py")
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for line in fileinput.input(path_to_lazy_loader, inplace=True):
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if 'stubfile = filename if filename.endswith("i")' in line:
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print(
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' stubfile = (filename if filename.endswith("i") else f"{os.path.splitext(filename)[0]}.pyi")',
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end="",
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)
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else:
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print(line, end="")
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# For getting around timm's packaging.
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# Refer: https://github.com/pyinstaller/pyinstaller/issues/5673#issuecomment-808731505
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path_to_timm_activations = Path(get_python_lib() + "/timm/layers/activations_jit.py")
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for line in fileinput.input(path_to_timm_activations, inplace=True):
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if "@torch.jit.script" in line:
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print("@torch.jit._script_if_tracing", end="\n")
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else:
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print(line, end="")
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