#!/usr/bin/env python import os, sys import shutil import datetime from setuptools import setup, find_packages from setuptools.command.install import install readme = open('README.md').read() readme = ''' # MCUNet: Tiny Deep Learning on IoT Devices ### [website](http://mcunet.mit.edu/) | [paper](https://arxiv.org/abs/2007.10319) | [demo](https://www.youtube.com/watch?v=YvioBgtec4U&feature=emb_logo) ## News - **(2022/06)** We refactor the MCUNet repo as a standalone repo (previous repo: https://github.com/mit-han-lab/tinyml) - **(2021/10)** Checkout our new paper **MCUNetV2**: https://arxiv.org/abs/2110.15352 ! - Our projects are covered by: [MIT News](https://news.mit.edu/2020/iot-deep-learning-1113), [WIRED](https://www.wired.com/story/ai-algorithms-slimming-fit-fridge/), [Morning Brew](https://www.morningbrew.com/emerging-tech/stories/2020/12/07/researchers-figured-fit-ai-ever-onto-internet-things-microchips), [Stacey on IoT](https://staceyoniot.com/researchers-take-a-3-pronged-approach-to-edge-ai/), [Analytics Insight](https://www.analyticsinsight.net/amalgamating-ml-and-iot-in-smart-home-devices/), [Techable](https://techable.jp/archives/142462), etc. ''' VERSION = "0.1.1" requirements = [ "torch", "torchvision" ] # import subprocess # commit_hash = subprocess.check_output("git rev-parse HEAD", shell=True).decode('UTF-8').rstrip() # VERSION += "_" + str(int(commit_hash, 16))[:8] VERSION += "_" + datetime.datetime.now().strftime("%Y%m%d%H%M") setup( # Metadata name="mcunet", version=VERSION, author="MTI HAN LAB ", author_email="hanlab.eecs+github@gmail.com", url="https://github.com/mit-han-lab/mcunet", description="MCUNet: Tiny Deep Learning on IoT Devices", long_description=readme, long_description_content_type="text/markdown", license="MIT", # Package info packages=find_packages(exclude=("*test*",)), # zip_safe=True, install_requires=requirements, # Classifiers classifiers=[ "Programming Language :: Python :: 3", ], )