setup.py

# -*- coding: utf-8 -*-
"""
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All Rights Reserved. Permission to use, copy, modify, and distribute this
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Setup of `gqcnn` Python codebase.

Author
------
Vishal Satish & Jeff Mahler
"""
import logging
import os
from setuptools import setup, find_packages
from setuptools.command.develop import develop
from setuptools.command.install import install
import subprocess
import sys

TF_MAX_VERSION = "1.15.0"

# Set up logger.
logging.basicConfig()  # Configure the root logger.
logger = logging.getLogger("setup.py")
logger.setLevel(logging.INFO)


def get_tf_dep():
    # Check whether or not the Nvidia driver and GPUs are available and add the
    # corresponding Tensorflow dependency.
    tf_dep = "tensorflow<={}".format(TF_MAX_VERSION)
    try:
        gpus = subprocess.check_output(
            ["nvidia-smi", "--query-gpu=gpu_name",
             "--format=csv"]).decode().strip().split("\n")[1:]
        if len(gpus) > 0:
            tf_dep = "tensorflow-gpu<={}".format(TF_MAX_VERSION)
        else:
            no_device_msg = ("Found Nvidia device driver but no"
                             " devices...installing Tensorflow for CPU.")
            logger.warning(no_device_msg)
    except OSError:
        no_driver_msg = ("Could not find Nvidia device driver...installing"
                         " Tensorflow for CPU.")
        logger.warning(no_driver_msg)
    return tf_dep


# TODO(vsatish): Use inheritance here.
class DevelopCmd(develop):
    user_options_custom = [
        ("docker", None, "installing in Docker"),
    ]
    user_options = getattr(develop, "user_options", []) + user_options_custom

    def initialize_options(self):
        develop.initialize_options(self)

        # Initialize options.
        self.docker = False

    def finalize_options(self):
        develop.finalize_options(self)

    def run(self):
        # Install Tensorflow dependency.
        if not self.docker:
            tf_dep = get_tf_dep()
            subprocess.Popen([sys.executable, "-m", "pip", "install",
                              tf_dep]).wait()
        else:
            # If we're using Docker, this will already have been installed
            # explicitly through the correct `{cpu/gpu}_requirements.txt`;
            # there is no way to check for CUDA/GPUs at Docker build time
            # because there is no easy way to set the Nvidia runtime.
            # TODO(vsatish): Figure out why this isn't printed.
            skip_tf_msg = ("Omitting Tensorflow dependency because of Docker"
                           " installation.")
            logger.warning(skip_tf_msg)

        # Run installation.
        develop.run(self)


class InstallCmd(install, object):
    user_options_custom = [
        ("docker", None, "installing in Docker"),
    ]
    user_options = getattr(install, "user_options", []) + user_options_custom

    def initialize_options(self):
        install.initialize_options(self)

        # Initialize options.
        self.docker = False

    def finalize_options(self):
        install.finalize_options(self)

    def run(self):
        # Install Tensorflow dependency.
        if not self.docker:
            tf_dep = get_tf_dep()
            subprocess.Popen([sys.executable, "-m", "pip", "install",
                              tf_dep]).wait()
        else:
            # If we're using Docker, this will already have been installed
            # explicitly through the correct `{cpu/gpu}_requirements.txt`;
            # there is no way to check for CUDA/GPUs at Docker build time
            # because there is no easy way to set the Nvidia runtime.
            # TODO (vsatish): Figure out why this isn't printed.
            skip_tf_msg = ("Omitting Tensorflow dependency because of Docker"
                           " installation.")
            logger.warning(skip_tf_msg)

        # Run installation.
        install.run(self)


requirements = [
    "autolab-core", "autolab-perception", "visualization", "numpy", "scipy",
    "matplotlib", "opencv-python", "scikit-learn", "scikit-image", "psutil",
    "gputil"
]

exec(
    open(
        os.path.join(os.path.dirname(os.path.realpath(__file__)),
                     "gqcnn/version.py")).read())

setup(
    name="gqcnn",
    version=__version__,  # noqa F821
    description=("Project code for running Grasp Quality Convolutional"
                 " Neural Networks"),
    author="Vishal Satish",
    author_email="vsatish@berkeley.edu",
    license="Berkeley Copyright",
    url="https://github.com/BerkeleyAutomation/gqcnn",
    keywords="robotics grasping vision deep learning",
    classifiers=[
        "Development Status :: 4 - Beta",
        "Programming Language :: Python :: 3.5",
        "Programming Language :: Python :: 3.6",
        "Programming Language :: Python :: 3.7",
        "Natural Language :: English",  # yapf: disable
        "Topic :: Scientific/Engineering"
    ],
    packages=find_packages(),
    install_requires=requirements,
    extras_require={
        "docs": ["sphinx", "sphinxcontrib-napoleon", "sphinx_rtd_theme"],
    },
    cmdclass={
        "install": InstallCmd,
        "develop": DevelopCmd
    })