Overhaul xgboost packages (#21661)

* Overhaul xgboost packages
* Don't deprecate xgboost 0.90
* Add py-xgboost@0.90, but deprecate it
* extras_require added in 1.0.0
* Deprecate py-dask-xgboost
* Simplify setting cuda arch
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Adam J. Stewart 2021-02-24 21:42:17 -06:00 committed by GitHub
parent d55384a46d
commit 2b201ba401
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3 changed files with 96 additions and 18 deletions

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@ -7,12 +7,15 @@
class PyDaskXgboost(PythonPackage): class PyDaskXgboost(PythonPackage):
"""Distributed training with XGBoost and Dask.distributed.""" """Distributed training with XGBoost and Dask.distributed.
Deprecated: use `py-xgboost+dask` instead."""
homepage = "https://github.com/dask/dask-xgboost/" homepage = "https://github.com/dask/dask-xgboost/"
pypi = "dask-xgboost/dask-xgboost-0.1.11.tar.gz" pypi = "dask-xgboost/dask-xgboost-0.1.11.tar.gz"
version('0.1.11', sha256='3fbe1bf4344dc74edfbe9f928c7e3e6acc26dc57cefd8da8ae56a15469c6941c') # Deprecated, see https://github.com/dask/dask-xgboost/issues/80
version('0.1.11', sha256='3fbe1bf4344dc74edfbe9f928c7e3e6acc26dc57cefd8da8ae56a15469c6941c', deprecated=True)
variant('sparse', default=False, description='Add sparse support') variant('sparse', default=False, description='Add sparse support')

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@ -3,6 +3,7 @@
# #
# SPDX-License-Identifier: (Apache-2.0 OR MIT) # SPDX-License-Identifier: (Apache-2.0 OR MIT)
import os
from spack import * from spack import *
@ -14,15 +15,25 @@ class PyXgboost(PythonPackage):
homepage = 'https://xgboost.ai/' homepage = 'https://xgboost.ai/'
pypi = 'xgboost/xgboost-1.3.3.tar.gz' pypi = 'xgboost/xgboost-1.3.3.tar.gz'
maintainers = ['adamjstewart']
import_modules = ['xgboost']
version('1.3.3', sha256='397051647bb837915f3ff24afc7d49f7fca57630ffd00fb5ef66ae2a0881fb43') version('1.3.3', sha256='397051647bb837915f3ff24afc7d49f7fca57630ffd00fb5ef66ae2a0881fb43')
version('0.90', sha256='d69f90d61a63e8889fd39a31ad00c629bac1ca627f8406b9b6d4594c9e29ab84', deprecated=True)
variant('pandas', default=False, description='Enable Pandas extensions for training.') variant('pandas', default=False, description='Enable Pandas extensions for training.')
variant('scikit-learn', default=False, description='Enable scikit-learn extensions for training.') variant('scikit-learn', default=False, description='Enable scikit-learn extensions for training.')
variant('dask', default=False, description='Enables Dask extensions for distributed training.') variant('dask', default=False, description='Enables Dask extensions for distributed training.')
variant('plotting', default=False, description='Enables tree and importance plotting.') variant('plotting', default=False, description='Enables tree and importance plotting.')
depends_on('cmake', type='build') for ver in ['1.3.3']:
depends_on('python@3.6:', type=('build', 'run')) depends_on('xgboost@' + ver, when='@' + ver)
depends_on('cmake@3.12:', when='@1.0:1.2.999', type='build')
depends_on('llvm-openmp', when='@:1.2.999 %apple-clang')
depends_on('python@3.6:', when='@1.2:', type=('build', 'run'))
depends_on('python@3.5:', when='@1.0:', type=('build', 'run'))
depends_on('python@3.4:', type=('build', 'run'))
depends_on('py-setuptools', type=('build')) depends_on('py-setuptools', type=('build'))
depends_on('py-numpy', type=('build', 'run')) depends_on('py-numpy', type=('build', 'run'))
depends_on('py-scipy', type=('build', 'run')) depends_on('py-scipy', type=('build', 'run'))
@ -37,3 +48,43 @@ class PyXgboost(PythonPackage):
depends_on('py-graphviz', when='+plotting', type=('build', 'run')) depends_on('py-graphviz', when='+plotting', type=('build', 'run'))
depends_on('py-matplotlib', when='+plotting', type=('build', 'run')) depends_on('py-matplotlib', when='+plotting', type=('build', 'run'))
conflicts('+pandas', when='@:0.999')
conflicts('+scikit-learn', when='@:0.999')
conflicts('+dask', when='@:0.999')
conflicts('+plotting', when='@:0.999')
# `--use-system-libxgboost` is only valid for the 'install' phase, but we want to
# skip building of the C++ library and rely on an external dependency
phases = ['install']
@when('@:0.90')
def patch(self):
# Fix OpenMP support on macOS
filter_file("OPENMP_FLAGS = -fopenmp",
"OPENMP_FLAGS = {0}".format(self.compiler.openmp_flag),
os.path.join("xgboost", "Makefile"), string=True)
@when('@1.3:')
def patch(self):
# https://github.com/dmlc/xgboost/issues/6706
# 'setup.py' is hard-coded to search in Python installation prefix
filter_file("lib_path = os.path.join(sys.prefix, 'lib')",
"lib_path = '{0}'".format(self.spec['xgboost'].libs.directories[0]),
"setup.py", string=True)
# Same for run-time search
filter_file("os.path.join(curr_path, 'lib'),",
"'{0}',".format(self.spec['xgboost'].libs.directories[0]),
os.path.join('xgboost', 'libpath.py'), string=True)
@when('@1.3:')
def install_args(self, spec, prefix):
args = super(PyXgboost, self).install_args(spec, prefix)
args.append('--use-system-libxgboost')
return args
# Tests need to be re-added since `phases` was overridden
run_after('install')(
PythonPackage._run_default_install_time_test_callbacks)
run_after('install')(PythonPackage.sanity_check_prefix)

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@ -7,25 +7,49 @@
class Xgboost(CMakePackage, CudaPackage): class Xgboost(CMakePackage, CudaPackage):
"""Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) """XGBoost is an optimized distributed gradient boosting library designed to be
Library, for Python, R, Java, Scala, C++ and more. Runs on single highly efficient, flexible and portable. It implements machine learning algorithms
machine, Hadoop, Spark, Flink and DataFlow""" under the Gradient Boosting framework. XGBoost provides a parallel tree boosting
(also known as GBDT, GBM) that solve many data science problems in a fast and
accurate way. The same code runs on major distributed environment (Hadoop, SGE, MPI)
and can solve problems beyond billions of examples."""
homepage = "https://xgboost.ai/" homepage = "https://xgboost.ai/"
url = "https://github.com/dmlc/xgboost/releases/download/v0.81/xgboost-0.81.tar.bz2"
git = "https://github.com/dmlc/xgboost.git" git = "https://github.com/dmlc/xgboost.git"
version('0.90', tag='v0.90', submodules=True) maintainers = ['adamjstewart']
version('0.81', sha256='9d8ff161699111d45c96bd15229aa6d80eb1cab7cbbef7e8eaa60ccfb5a4f806')
version('master', branch='master', submodules=True)
version('1.3.3', tag='v1.3.3', submodules=True)
version('0.90', tag='v0.90', submodules=True, deprecated=True)
version('0.81', tag='v0.81', submodules=True, deprecated=True)
variant('nccl', default=False, description='Build with NCCL to enable distributed GPU support')
variant('openmp', default=True, description='Build with OpenMP support')
depends_on('cmake@3.13:', type='build')
depends_on('cmake@3.16:', when='platform=darwin', type='build')
depends_on('ninja', type='build')
depends_on('cuda@10:', when='+cuda')
depends_on('nccl', when='+nccl')
depends_on('llvm-openmp', when='%apple-clang +openmp')
conflicts('%gcc@:4.999', msg='GCC version must be at least 5.0!')
conflicts('+nccl', when='~cuda', msg='NCCL requires CUDA')
conflicts('+cuda', when='~openmp', msg='CUDA requires OpenMP')
generator = 'Ninja'
def cmake_args(self): def cmake_args(self):
return [ # https://xgboost.readthedocs.io/en/latest/build.html
'-DUSE_CUDA={0}'.format('YES' if '+cuda' in self.spec else 'NO') args = [
self.define_from_variant('USE_CUDA', 'cuda'),
self.define_from_variant('USE_NCCL', 'nccl'),
self.define_from_variant('USE_OPENMP', 'openmp'),
] ]
def install(self, spec, prefix): if '+cuda' in self.spec and 'cuda_arch=none' not in self.spec:
install_tree(str(self.stage.source_path), prefix) args.append(self.define(
# create a bin directory for executable "xgboost" which is possibly 'GPU_COMPUTE_VER', self.spec.variants['cuda_arch'].value))
# used in functional testing of the compilation target "libxgboost"
mkdirp(prefix.bin) return args
install('xgboost', prefix.bin)