Files
spack/var/spack/repos/builtin/packages/py-dgl/package.py
Adam J. Stewart 3540f8200a PythonPackage: install packages with pip (#27798)
* Use pip to bootstrap pip

* Bootstrap wheel from source

* Update PythonPackage to install using pip

* Update several packages

* Add wheel as base class dep

* Build phase no longer exists

* Add py-poetry package, fix py-flit-core bootstrapping

* Fix isort build

* Clean up many more packages

* Remove unused import

* Fix unit tests

* Don't directly run setup.py

* Typo fix

* Remove unused imports

* Fix issues caught by CI

* Remove custom setup.py file handling

* Use PythonPackage for installing wheels

* Remove custom phases in PythonPackages

* Remove <phase>_args methods

* Remove unused import

* Fix various packages

* Try to test Python packages directly in CI

* Actually run the pipeline

* Fix more packages

* Fix mappings, fix packages

* Fix dep version

* Work around bug in concretizer

* Various concretization fixes

* Fix gitlab yaml, packages

* Fix typo in gitlab yaml

* Skip more packages that fail to concretize

* Fix? jupyter ecosystem concretization issues

* Solve Jupyter concretization issues

* Prevent duplicate entries in PYTHONPATH

* Skip fenics-dolfinx

* Build fewer Python packages

* Fix missing npm dep

* Specify image

* More package fixes

* Add backends for every from-source package

* Fix version arg

* Remove GitLab CI stuff, add py-installer package

* Remove test deps, re-add install_options

* Function declaration syntax fix

* More build fixes

* Update spack create template

* Update PythonPackage documentation

* Fix documentation build

* Fix unit tests

* Remove pip flag added only in newer pip

* flux: add explicit dependency on jsonschema

* Update packages that have been added since this was branched off of develop

* Move Python 2 deprecation to a separate PR

* py-neurolab: add build dep on py-setuptools

* Use wheels for pip/wheel

* Allow use of pre-installed pip for external Python

* pip -> python -m pip

* Use python -m pip for all packages

* Fix py-wrapt

* Add both platlib and purelib to PYTHONPATH

* py-pyyaml: setuptools is needed for all versions

* py-pyyaml: link flags aren't needed

* Appease spack audit packages

* Some build backend is required for all versions, distutils -> setuptools

* Correctly handle different setup.py filename

* Use wheels for py-tomli to avoid circular dep on py-flit-core

* Fix busco installation procedure

* Clarify things in spack create template

* Test other Python build backends

* Undo changes to busco

* Various fixes

* Don't test other backends
2022-01-14 12:37:57 -06:00

138 lines
5.1 KiB
Python

# Copyright 2013-2021 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
class PyDgl(CMakePackage):
"""Deep Graph Library (DGL).
DGL is an easy-to-use, high performance and scalable Python package for
deep learning on graphs. DGL is framework agnostic, meaning if a deep graph
model is a component of an end-to-end application, the rest of the logics
can be implemented in any major frameworks, such as PyTorch, Apache MXNet
or TensorFlow."""
homepage = "https://www.dgl.ai/"
git = "https://github.com/dmlc/dgl.git"
maintainers = ['adamjstewart']
version('master', branch='master', submodules=True)
version('0.4.3', tag='0.4.3', submodules=True)
version('0.4.2', tag='0.4.2', submodules=True)
variant('cuda', default=True, description='Build with CUDA')
variant('openmp', default=True, description='Build with OpenMP')
variant('backend', default='pytorch', description='Default backend',
values=['pytorch', 'mxnet', 'tensorflow'], multi=False)
depends_on('cmake@3.5:', type='build')
depends_on('cuda', when='+cuda')
depends_on('llvm-openmp', when='%apple-clang +openmp')
# Python dependencies
# See python/setup.py
extends('python')
depends_on('python@3.5:', type=('build', 'run'))
depends_on('py-pip', type='build')
depends_on('py-wheel', type='build')
depends_on('py-setuptools', type='build')
depends_on('py-cython', type='build')
depends_on('py-numpy@1.14.0:', type=('build', 'run'))
depends_on('py-scipy@1.1.0:', type=('build', 'run'))
depends_on('py-networkx@2.1:', type=('build', 'run'))
depends_on('py-requests@2.19.0:', when='@0.4.3:', type=('build', 'run'))
# Backends
# See https://github.com/dmlc/dgl#installation
depends_on('py-torch@1.2.0:', when='@0.4.3: backend=pytorch', type='run')
depends_on('py-torch@0.4.1:', when='backend=pytorch', type='run')
depends_on('mxnet@1.5.1:', when='@0.4.3: backend=pytorch', type='run')
depends_on('mxnet@1.5.0:', when='backend=mxnet', type='run')
depends_on('py-tensorflow@2.1:', when='@0.4.3: backend=tensorflow', type='run')
depends_on('py-tensorflow@2.0:', when='backend=tensorflow', type='run')
depends_on('py-tfdlpack', when='backend=tensorflow', type='run')
build_directory = 'build'
# https://docs.dgl.ai/install/index.html#install-from-source
def cmake_args(self):
args = []
if '+cuda' in self.spec:
args.append('-DUSE_CUDA=ON')
else:
args.append('-DUSE_CUDA=OFF')
if '+openmp' in self.spec:
args.append('-DUSE_OPENMP=ON')
if self.spec.satisfies('%apple-clang'):
args.extend([
'-DOpenMP_CXX_FLAGS=' +
self.spec['llvm-openmp'].headers.include_flags,
'-DOpenMP_CXX_LIB_NAMES=' +
self.spec['llvm-openmp'].libs.names[0],
'-DOpenMP_C_FLAGS=' +
self.spec['llvm-openmp'].headers.include_flags,
'-DOpenMP_C_LIB_NAMES=' +
self.spec['llvm-openmp'].libs.names[0],
'-DOpenMP_omp_LIBRARY=' +
self.spec['llvm-openmp'].libs[0],
])
else:
args.append('-DUSE_OPENMP=OFF')
if self.run_tests:
args.append('-DBUILD_CPP_TEST=ON')
else:
args.append('-DBUILD_CPP_TEST=OFF')
return args
def install(self, spec, prefix):
with working_dir('python'):
args = std_pip_args + ['--prefix=' + prefix, '.']
pip(*args)
# Work around installation bug: https://github.com/dmlc/dgl/issues/1379
install_tree(prefix.dgl, prefix.lib)
def setup_run_environment(self, env):
# https://docs.dgl.ai/install/backend.html
backend = self.spec.variants['backend'].value
env.set('DGLBACKEND', backend)
@property
def import_modules(self):
modules = [
'dgl', 'dgl.nn', 'dgl.runtime', 'dgl.backend', 'dgl.function',
'dgl.contrib', 'dgl._ffi', 'dgl.data', 'dgl.runtime.ir',
'dgl.backend.numpy', 'dgl.contrib.sampling', 'dgl._ffi._cy2',
'dgl._ffi._cy3', 'dgl._ffi._ctypes',
]
if 'backend=pytorch' in self.spec:
modules.extend([
'dgl.nn.pytorch', 'dgl.nn.pytorch.conv', 'dgl.backend.pytorch'
])
elif 'backend=mxnet' in self.spec:
modules.extend([
'dgl.nn.mxnet', 'dgl.nn.mxnet.conv', 'dgl.backend.mxnet'
])
elif 'backend=tensorflow' in self.spec:
modules.extend([
'dgl.nn.tensorflow', 'dgl.nn.tensorflow.conv',
'dgl.backend.tensorflow'
])
return modules
@run_after('install')
@on_package_attributes(run_tests=True)
def import_module_test(self):
with working_dir('spack-test', create=True):
for module in self.import_modules:
python('-c', 'import {0}'.format(module))