72 lines
1.9 KiB
Python
Executable File
72 lines
1.9 KiB
Python
Executable File
import subprocess
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import sys
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from pathlib import Path
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from datetime import datetime
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from setuptools import setup, find_packages
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def shell(*args):
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out = subprocess.check_output(args)
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return out.decode("ascii").strip()
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def write_version(version_core, pre_release=True):
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if pre_release:
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time = shell("git", "log", "-1", "--format=%cd", "--date=iso")
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time = datetime.strptime(time, "%Y-%m-%d %H:%M:%S %z")
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time = time.strftime("%Y%m%d%H%M%S")
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version = f"{version_core}-dev{time}"
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else:
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version = version_core
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with open(Path("image_classifier", "version.py"), "w") as f:
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f.write('__version__ = "{}"\n'.format(version))
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return version
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with open("README.md", "r") as f:
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long_description = f.read()
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setup(
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name="image_classifier",
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python_requires=">=3.10.0",
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version=write_version("0.0.1"),
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description="A ResNet-based image classifier",
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author="ecker",
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author_email="mrq@ecker.tech",
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long_description=long_description,
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long_description_content_type="text/markdown",
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packages=find_packages(),
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install_requires=(
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# training backends
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["deepspeed>=0.7.7"] if not sys.platform.startswith("win") else [])
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+ [
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# logging niceties
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"coloredlogs>=15.0.1",
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"humanize>=4.4.0",
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"matplotlib>=3.6.0",
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"pandas>=1.5.0",
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# boiler plate niceties
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"diskcache>=5.4.0",
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"einops>=0.6.0",
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"tqdm",
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# HF bloat
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"tokenizers",
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"transformers",
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"safetensors",
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# training bloat
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"h5py",
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"prodigyopt @ git+https://github.com/konstmish/prodigy",
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# practically the reason to use python
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"numpy",
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"torch>=1.13.0",
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"torchmetrics",
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"simple_http_server",
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"pillow"
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],
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url="https://git.ecker.tech/mrq/resnet-classifier",
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)
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