forked from BayesWatch/sequential-imagenet-dataloader
-
Notifications
You must be signed in to change notification settings - Fork 0
/
setup.py
52 lines (39 loc) · 1.62 KB
/
setup.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
"""Based on example https://github.com/pypa/sampleproject"""
# Always prefer setuptools over distutils
from setuptools import setup, find_packages
# To use a consistent encoding
from codecs import open
from os import path
here = path.abspath(path.dirname(__file__))
# Get the long description from the README file
with open(path.join(here, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
setup(
name='pytorch-imagenet-dataloader',
# Versions should comply with PEP440. For a discussion on single-sourcing
# the version across setup.py and the project code, see
# https://packaging.python.org/en/latest/single_source_version.html
version='0.0.1',
description='A faster PyTorch ImageNet loader.',
long_description=long_description,
# The project's main homepage.
url='https://github.com/gngdb/pytorch-imagenet-dataloader',
# Author details
author='Gavin Gray',
author_email='[email protected]',
# Choose your license
license='MIT',
# What does your project relate to?
keywords='pytorch',
# You can just specify the packages manually here if your project is
# simple. Or you can use find_packages().
packages=find_packages(),
# Alternatively, if you want to distribute just a my_module.py, uncomment
# this:
# py_modules=["my_module"],
# List run-time dependencies here. These will be installed by pip when
# your project is installed. For an analysis of "install_requires" vs pip's
# requirements files see:
# https://packaging.python.org/en/latest/requirements.html
install_requires=['lmdb', 'tqdm'],
)