381 lines
17 KiB
Python
381 lines
17 KiB
Python
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# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License..
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# ==============================================================================
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"""TensorFlow is an open source machine learning framework for everyone.
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[](https://badge.fury.io/py/tensorflow)
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[](https://badge.fury.io/py/tensorflow)
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TensorFlow is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms, and from desktops to clusters of servers to mobile and edge devices.
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Originally developed by researchers and engineers from the Google Brain team ([https://research.google/teams/brain/](https://research.google/teams/brain/)) within Google's AI organization, TensorFlow comes with strong support for machine learning and deep learning with a flexible numerical computation core that can be used across many other scientific domains. TensorFlow is licensed under [Apache 2.0](https://github.com/tensorflow/tensorflow/blob/master/LICENSE).
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This optimized version of TensorFlow for Windows OS has been produced by Intel. In order to take full advantage of Intel architecture and to extract maximum performance, the TensorFlow framework has been optimized using oneAPI Deep Neural Network Library (oneDNN) primitives, a popular performance library for deep learning applications. For more information on the optimizations as well as performance data, see this blog post [Faster AI Inference with Intel Optimization for TensorFlow](https://medium.com/intel-analytics-software/accelerate-ai-model-performance-on-the-alder-lake-platform-a5c24ae3f522). To activate oneDNN, execute the following in the Windows command prompt: set TF_ENABLE_ONEDNN_OPTS=1 before running your AI/ML workload.
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"""
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import fnmatch
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import os
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import re
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import sys
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import platform
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from setuptools import Command
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from setuptools import find_packages
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from setuptools import setup
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from setuptools.command.install import install as InstallCommandBase
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from setuptools.dist import Distribution
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# This version string is semver compatible, but incompatible with pip.
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# For pip, we will remove all '-' characters from this string, and use the
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# result for pip.
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# Also update tensorflow/tensorflow.bzl and
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# tensorflow/core/public/version.h
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_VERSION = '2.12.0'
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# We use the same setup.py for all tensorflow_* packages and for the nightly
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# equivalents (tf_nightly_*). The package is controlled from the argument line
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# when building the pip package.
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project_name = 'tensorflow'
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if '--project_name' in sys.argv:
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project_name_idx = sys.argv.index('--project_name')
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project_name = sys.argv[project_name_idx + 1]
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sys.argv.remove('--project_name')
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sys.argv.pop(project_name_idx)
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collaborator_build = False
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if '--collaborator_build' in sys.argv:
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sys.argv.remove('--collaborator_build')
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collaborator_build = True
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# Returns standard if a tensorflow-* package is being built, and nightly if a
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# tf_nightly-* package is being built.
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def standard_or_nightly(standard, nightly):
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return nightly if 'tf_nightly' in project_name else standard
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# All versions of TF need these packages. We indicate the widest possible range
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# of package releases possible to be as up-to-date as possible as well as to
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# accomodate as many pre-installed packages as possible.
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# For packages that don't have yet a stable release, we pin using `~= 0.x` which
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# means we accept any `0.y` version (y >= x) but not the first major release. We
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# will need additional testing for that.
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# NOTE: This assumes that all packages follow SemVer. If a package follows a
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# different versioning scheme (e.g., PVP), we use different bound specifier and
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# comment the versioning scheme.
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REQUIRED_PACKAGES = [
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'absl-py >= 1.0.0',
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'astunparse >= 1.6.0',
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'flatbuffers >= 2.0',
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# TODO(b/213222745) gast versions above 0.4.0 break TF's tests
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'gast >= 0.2.1, <= 0.4.0',
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'google_pasta >= 0.1.1',
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'h5py >= 2.9.0',
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# TODO(b/239052279): replace with external dependency on JAX repo once JAX
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# no longer relies on TF.
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'jax >= 0.3.15',
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'libclang >= 13.0.0',
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# TODO(b/263178356): numpy 1.24 breaks TF's tests
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'numpy >= 1.22, <1.24',
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'opt_einsum >= 2.3.2',
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'packaging',
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# TODO(b/182876485): Protobuf 3.20 results in linker errors on Windows
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# Protobuf 4.0 is binary incompatible with what C++ TF uses.
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# We need ~1 quarter to update properly.
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# See also: https://github.com/tensorflow/tensorflow/issues/53234
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# See also: https://github.com/protocolbuffers/protobuf/issues/9954
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# See also: https://github.com/tensorflow/tensorflow/issues/56077
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# This is a temporary patch for now, to patch previous TF releases.
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'protobuf>=3.20.3,<5.0.0dev,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5',
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'setuptools',
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'six >= 1.12.0',
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'termcolor >= 1.1.0',
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'typing_extensions >= 3.6.6',
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# TODO(b/266362323): wrapt==1.15.0rc0 incompatible with TF 2.12.0 RC0 (and
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# nightly, but works with TF 2.11)
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'wrapt >= 1.11.0, <1.15',
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'tensorflow-io-gcs-filesystem >= 0.23.1;platform_machine!="arm64" or ' +
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'platform_system!="Darwin"',
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# grpcio does not build correctly on big-endian machines due to lack of
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# BoringSSL support.
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# See https://github.com/tensorflow/tensorflow/issues/17882.
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'grpcio >= 1.24.3, < 2.0' if sys.byteorder == 'little' else None,
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# TensorFlow exposes the TF API for certain TF ecosystem packages like
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# keras. When TF depends on those packages, the package version needs to
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# match the current TF version. For tf_nightly, we install the nightly
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# variant of each package instead, which must be one version ahead of the
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# current release version. These also usually have "alpha" or "dev" in their
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# version name.
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# These are all updated during the TF release process.
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standard_or_nightly('tensorboard >= 2.12, < 2.13',
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'tb-nightly ~= 2.12.0.a'),
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standard_or_nightly('tensorflow_estimator >= 2.12.0, < 2.13',
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'tf-estimator-nightly ~= 2.13.0.dev'),
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standard_or_nightly('keras >= 2.12.0, < 2.13',
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'keras-nightly ~= 2.13.0.dev'),
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]
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REQUIRED_PACKAGES = [p for p in REQUIRED_PACKAGES if p is not None]
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FAKE_REQUIRED_PACKAGES = [
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# The depedencies here below are not actually used but are needed for
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# package managers like poetry to parse as they are confused by the
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# different architectures having different requirements.
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# The entries here should be a simple duplicate of those in the collaborator
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# build section.
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standard_or_nightly('tensorflow-cpu-aws', 'tf-nightly-cpu-aws') + '==' +
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_VERSION + ';platform_system=="Linux" and (platform_machine=="arm64" or '
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'platform_machine=="aarch64")',
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standard_or_nightly('tensorflow-intel', 'tf-nightly-intel') + '==' +
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_VERSION + ';platform_system=="Windows"',
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]
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if platform.system() == 'Linux' and platform.machine() == 'x86_64':
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REQUIRED_PACKAGES.append(FAKE_REQUIRED_PACKAGES)
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if collaborator_build:
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# If this is a collaborator build, then build an "installer" wheel and
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# add the collaborator packages as the only dependencies.
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REQUIRED_PACKAGES = [
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# Install the TensorFlow package built by AWS if the user is running
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# Linux on an Aarch64 machine.
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standard_or_nightly('tensorflow-cpu-aws', 'tf-nightly-cpu-aws') + '==' +
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_VERSION + ';platform_system=="Linux" and (platform_machine=="arm64" or '
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'platform_machine=="aarch64")',
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# Install the TensorFlow package built by Intel if the user is on a
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# Windows machine.
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standard_or_nightly('tensorflow-intel', 'tf-nightly-intel') + '==' +
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_VERSION + ';platform_system=="Windows"',
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]
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DOCLINES = __doc__.split('\n')
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if project_name.endswith('-gpu'):
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project_name_no_gpu = project_name[:-len('-gpu')]
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_GPU_PACKAGE_NOTE = 'Note that %s package by default supports both CPU and '\
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'GPU. %s has the same content and exists solely for backward '\
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'compatibility. Please migrate to %s for GPU support.'\
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% (project_name_no_gpu, project_name, project_name_no_gpu)
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DOCLINES.append(_GPU_PACKAGE_NOTE)
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# pylint: disable=line-too-long
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CONSOLE_SCRIPTS = [
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'toco_from_protos = tensorflow.lite.toco.python.toco_from_protos:main',
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'tflite_convert = tensorflow.lite.python.tflite_convert:main',
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'toco = tensorflow.lite.python.tflite_convert:main',
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'saved_model_cli = tensorflow.python.tools.saved_model_cli:main',
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'import_pb_to_tensorboard = tensorflow.python.tools.import_pb_to_tensorboard:main',
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# We need to keep the TensorBoard command, even though the console script
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# is now declared by the tensorboard pip package. If we remove the
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# TensorBoard command, pip will inappropriately remove it during install,
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# even though the command is not removed, just moved to a different wheel.
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# We exclude it anyway if building tf_nightly.
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standard_or_nightly('tensorboard = tensorboard.main:run_main', None),
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'tf_upgrade_v2 = tensorflow.tools.compatibility.tf_upgrade_v2_main:main',
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'estimator_ckpt_converter = '
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'tensorflow_estimator.python.estimator.tools.checkpoint_converter:main',
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]
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CONSOLE_SCRIPTS = [s for s in CONSOLE_SCRIPTS if s is not None]
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# pylint: enable=line-too-long
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class BinaryDistribution(Distribution):
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def has_ext_modules(self):
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return True
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class InstallCommand(InstallCommandBase):
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"""Override the dir where the headers go."""
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def finalize_options(self):
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ret = InstallCommandBase.finalize_options(self) # pylint: disable=assignment-from-no-return
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self.install_headers = os.path.join(self.install_platlib, 'tensorflow',
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'include')
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self.install_lib = self.install_platlib
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return ret
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class InstallHeaders(Command):
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"""Override how headers are copied.
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The install_headers that comes with setuptools copies all files to
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the same directory. But we need the files to be in a specific directory
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hierarchy for -I <include_dir> to work correctly.
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"""
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description = 'install C/C++ header files'
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user_options = [
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('install-dir=', 'd', 'directory to install header files to'),
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('force', 'f', 'force installation (overwrite existing files)'),
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]
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boolean_options = ['force']
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def initialize_options(self):
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self.install_dir = None
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self.force = 0
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self.outfiles = []
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def finalize_options(self):
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self.set_undefined_options('install', ('install_headers', 'install_dir'),
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('force', 'force'))
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def mkdir_and_copy_file(self, header):
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install_dir = os.path.join(self.install_dir, os.path.dirname(header))
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# Get rid of some extra intervening directories so we can have fewer
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# directories for -I
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install_dir = re.sub('/google/protobuf_archive/src', '', install_dir)
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# Copy external code headers into tensorflow/include.
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# A symlink would do, but the wheel file that gets created ignores
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# symlink within the directory hierarchy.
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# NOTE(keveman): Figure out how to customize bdist_wheel package so
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# we can do the symlink.
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external_header_locations = [
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'tensorflow/include/external/eigen_archive/',
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'tensorflow/include/external/com_google_absl/',
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]
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for location in external_header_locations:
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if location in install_dir:
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extra_dir = install_dir.replace(location, '')
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if not os.path.exists(extra_dir):
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self.mkpath(extra_dir)
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self.copy_file(header, extra_dir)
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if not os.path.exists(install_dir):
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self.mkpath(install_dir)
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return self.copy_file(header, install_dir)
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def run(self):
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hdrs = self.distribution.headers
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if not hdrs:
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return
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self.mkpath(self.install_dir)
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for header in hdrs:
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(out, _) = self.mkdir_and_copy_file(header)
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self.outfiles.append(out)
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def get_inputs(self):
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return self.distribution.headers or []
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def get_outputs(self):
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return self.outfiles
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def find_files(pattern, root):
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"""Return all the files matching pattern below root dir."""
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for dirpath, _, files in os.walk(root):
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for filename in fnmatch.filter(files, pattern):
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yield os.path.join(dirpath, filename)
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so_lib_paths = [
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i for i in os.listdir('.')
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if os.path.isdir(i) and fnmatch.fnmatch(i, '_solib_*')
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]
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matches = []
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for path in so_lib_paths:
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matches.extend(['../' + x for x in find_files('*', path) if '.py' not in x])
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if os.name == 'nt':
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EXTENSION_NAME = 'python/_pywrap_tensorflow_internal.pyd'
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else:
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EXTENSION_NAME = 'python/_pywrap_tensorflow_internal.so'
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headers = (
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list(find_files('*.proto', 'tensorflow/compiler')) +
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list(find_files('*.proto', 'tensorflow/core')) +
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list(find_files('*.proto', 'tensorflow/python')) +
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list(find_files('*.proto', 'tensorflow/python/framework')) +
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list(find_files('*.proto', 'tensorflow/tsl')) +
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list(find_files('*.def', 'tensorflow/compiler')) +
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list(find_files('*.h', 'tensorflow/c')) +
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list(find_files('*.h', 'tensorflow/cc')) +
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list(find_files('*.h', 'tensorflow/compiler')) +
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list(find_files('*.h.inc', 'tensorflow/compiler')) +
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list(find_files('*.h', 'tensorflow/core')) +
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list(find_files('*.h', 'tensorflow/lite/kernels/shim')) +
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list(find_files('*.h', 'tensorflow/python')) +
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list(find_files('*.h', 'tensorflow/python/client')) +
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list(find_files('*.h', 'tensorflow/python/framework')) +
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list(find_files('*.h', 'tensorflow/stream_executor')) +
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list(find_files('*.h', 'tensorflow/compiler/xla/stream_executor')) +
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list(find_files('*.h', 'tensorflow/tsl')) +
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|
|
list(find_files('*.h', 'google/com_google_protobuf/src')) +
|
||
|
|
list(find_files('*.inc', 'google/com_google_protobuf/src')) +
|
||
|
|
list(find_files('*', 'third_party/eigen3')) +
|
||
|
|
list(find_files('*', 'third_party/gpus')) +
|
||
|
|
list(find_files('*.h', 'tensorflow/include/external/com_google_absl')) +
|
||
|
|
list(find_files('*.inc', 'tensorflow/include/external/com_google_absl')) +
|
||
|
|
list(find_files('*', 'tensorflow/include/external/eigen_archive')))
|
||
|
|
|
||
|
|
setup(
|
||
|
|
name=project_name,
|
||
|
|
version=_VERSION.replace('-', ''),
|
||
|
|
description=DOCLINES[0],
|
||
|
|
long_description='\n'.join(DOCLINES[2:]),
|
||
|
|
long_description_content_type='text/markdown',
|
||
|
|
url='https://www.tensorflow.org/',
|
||
|
|
download_url='https://github.com/tensorflow/tensorflow/tags',
|
||
|
|
author='Google Inc.',
|
||
|
|
author_email='packages@tensorflow.org',
|
||
|
|
# Contained modules and scripts.
|
||
|
|
packages=find_packages() if not collaborator_build else [],
|
||
|
|
entry_points={
|
||
|
|
'console_scripts': CONSOLE_SCRIPTS,
|
||
|
|
} if not collaborator_build else {},
|
||
|
|
headers=headers if not collaborator_build else [],
|
||
|
|
install_requires=REQUIRED_PACKAGES,
|
||
|
|
# Add in any packaged data.
|
||
|
|
include_package_data=True if not collaborator_build else False,
|
||
|
|
package_data={
|
||
|
|
'tensorflow': [EXTENSION_NAME,] + matches,
|
||
|
|
} if not collaborator_build else {},
|
||
|
|
zip_safe=False,
|
||
|
|
distclass=BinaryDistribution if not collaborator_build else None,
|
||
|
|
cmdclass={
|
||
|
|
'install_headers': InstallHeaders,
|
||
|
|
'install': InstallCommand,} if not collaborator_build else {},
|
||
|
|
# Supported Python versions
|
||
|
|
python_requires='>=3.8',
|
||
|
|
# PyPI package information.
|
||
|
|
classifiers=sorted([
|
||
|
|
'Development Status :: 5 - Production/Stable',
|
||
|
|
# TODO(angerson) Add IFTTT when possible
|
||
|
|
'Environment :: GPU :: NVIDIA CUDA :: 11.8',
|
||
|
|
'Intended Audience :: Developers',
|
||
|
|
'Intended Audience :: Education',
|
||
|
|
'Intended Audience :: Science/Research',
|
||
|
|
'License :: OSI Approved :: Apache Software License',
|
||
|
|
'Programming Language :: Python :: 3',
|
||
|
|
'Programming Language :: Python :: 3.8',
|
||
|
|
'Programming Language :: Python :: 3.9',
|
||
|
|
'Programming Language :: Python :: 3.10',
|
||
|
|
'Programming Language :: Python :: 3.11',
|
||
|
|
'Programming Language :: Python :: 3 :: Only',
|
||
|
|
'Topic :: Scientific/Engineering',
|
||
|
|
'Topic :: Scientific/Engineering :: Mathematics',
|
||
|
|
'Topic :: Scientific/Engineering :: Artificial Intelligence',
|
||
|
|
'Topic :: Software Development',
|
||
|
|
'Topic :: Software Development :: Libraries',
|
||
|
|
'Topic :: Software Development :: Libraries :: Python Modules',
|
||
|
|
]),
|
||
|
|
license='Apache 2.0',
|
||
|
|
keywords='tensorflow tensor machine learning',
|
||
|
|
)
|