setup.py

#!/usr/bin/env python3
""" Amazon SageMaker Debugger is an offering from AWS which helps you automate the debugging of machine learning training jobs.
This library powers Amazon SageMaker Debugger, and helps you develop better, faster and cheaper models by catching common errors quickly.
It allows you to save tensors from training jobs and makes these tensors available for analysis, all through a flexible and powerful API.
It supports TensorFlow, PyTorch, MXNet, and XGBoost on Python 3.6+.
- Zero Script Change experience on SageMaker when using supported versions of SageMaker Framework containers or AWS Deep Learning containers
- Full visibility into any tensor which is part of the training process
- Real-time training job monitoring through Rules
- Automated anomaly detection and state assertions
- Interactive exploration of saved tensors
- Distributed training support
- TensorBoard support

"""

# Standard Library
import os
import shutil
import subprocess
import sys
from datetime import date

# Third Party
import compile_protobuf
import setuptools

exec(open("smdebug/_version.py").read())
CURRENT_VERSION = __version__

DOCLINES = (__doc__ or "").split("\n")
FRAMEWORKS = ["tensorflow", "pytorch", "mxnet", "xgboost"]
TESTS_PACKAGES = ["pytest", "torchvision", "pandas"]
INSTALL_REQUIRES = [
    "protobuf>=3.20.0,<=3.20.3",
    "numpy>=1.16.0",
    "packaging",
    "boto3>=1.10.32",
    "pyinstrument==3.4.2",
    "requests",
    "pandas",
    "psutil",
]


def build_package(version):
    compile_protobuf.compile_protobuf()
    packages = setuptools.find_packages(include=["smdebug", "smdebug.*"])
    setuptools.setup(
        name="smdebug",
        version=version,
        long_description="\n".join(DOCLINES[1:]),
        long_description_content_type="text/markdown",
        author="AWS DeepLearning Team",
        description=DOCLINES[0],
        url="https://github.com/awslabs/sagemaker-debugger",
        packages=packages,
        classifiers=[
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: 3.8",
            "Programming Language :: Python :: 3 :: Only",
            "License :: OSI Approved :: Apache Software License",
            "Operating System :: OS Independent",
        ],
        install_requires=INSTALL_REQUIRES,
        setup_requires=["pytest-runner"],
        tests_require=TESTS_PACKAGES,
        python_requires=">=3.6",
        license="Apache License Version 2.0",
    )


def scan_git_secrets():
    def git(*args):
        return subprocess.call(["git"] + list(args))

    shutil.rmtree("/tmp/git-secrets", ignore_errors=True)
    git("clone", "https://github.com/awslabs/git-secrets.git", "/tmp/git-secrets")
    dir_path = os.path.dirname(os.path.realpath(__file__))
    os.chdir("/tmp/git-secrets")
    subprocess.check_call(["make"] + ["install"])
    os.chdir(dir_path)
    git("secrets", "--install")
    git("secrets", "--register-aws")
    return git("secrets", "--scan", "-r")


if scan_git_secrets() != 0:
    import sys

    sys.exit(1)


def detect_smdebug_version():
    return CURRENT_VERSION


version = detect_smdebug_version()
build_package(version=version)