NAS-sharing-parameters support 3 datasets / update ops / update pypi
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								exps/NAS-Bench-102/dist-setup.py
									
									
									
									
									
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								exps/NAS-Bench-102/dist-setup.py
									
									
									
									
									
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							| @@ -0,0 +1,28 @@ | ||||
| import os | ||||
| from setuptools import setup | ||||
|  | ||||
|  | ||||
| def read(fname='README.md'): | ||||
|   with open(os.path.join(os.path.dirname(__file__), fname), encoding='utf-8') as cfile: | ||||
|     return cfile.read() | ||||
|  | ||||
|  | ||||
| setup( | ||||
|     name = "nas_bench_102", | ||||
|     version = "1.0", | ||||
|     author = "Xuanyi Dong", | ||||
|     author_email = "dongxuanyi888@gmail.com", | ||||
|     description = "API for NAS-Bench-102 (a benchmark for neural architecture search).", | ||||
|     license = "MIT", | ||||
|     keywords = "NAS Dataset API DeepLearning", | ||||
|     url = "https://github.com/D-X-Y/NAS-Projects", | ||||
|     packages=['nas_102_api'], | ||||
|     long_description=read('README.md'), | ||||
|     long_description_content_type='text/markdown', | ||||
|     classifiers=[ | ||||
|         "Programming Language :: Python", | ||||
|         "Topic :: Database", | ||||
|         "Topic :: Scientific/Engineering :: Artificial Intelligence", | ||||
|         "License :: OSI Approved :: MIT License", | ||||
|     ], | ||||
| ) | ||||
| @@ -1,8 +1,8 @@ | ||||
| ################################################## | ||||
| # NAS-Bench-102 ################################## | ||||
| ################################################## | ||||
| # Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2019 # | ||||
| ################################################## | ||||
| ############################################################### | ||||
| # NAS-Bench-102, ICLR 2020 (https://arxiv.org/abs/2001.00326) # | ||||
| ############################################################### | ||||
| # Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2019-2020         # | ||||
| ############################################################### | ||||
| import os, sys, time, torch, random, argparse | ||||
| from PIL     import ImageFile | ||||
| ImageFile.LOAD_TRUNCATED_IMAGES = True | ||||
|   | ||||
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