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
GitHub
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2b201ba401
@ -7,12 +7,15 @@
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class PyDaskXgboost(PythonPackage):
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"""Distributed training with XGBoost and Dask.distributed."""
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"""Distributed training with XGBoost and Dask.distributed.
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Deprecated: use `py-xgboost+dask` instead."""
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homepage = "https://github.com/dask/dask-xgboost/"
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pypi = "dask-xgboost/dask-xgboost-0.1.11.tar.gz"
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version('0.1.11', sha256='3fbe1bf4344dc74edfbe9f928c7e3e6acc26dc57cefd8da8ae56a15469c6941c')
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# Deprecated, see https://github.com/dask/dask-xgboost/issues/80
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version('0.1.11', sha256='3fbe1bf4344dc74edfbe9f928c7e3e6acc26dc57cefd8da8ae56a15469c6941c', deprecated=True)
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variant('sparse', default=False, description='Add sparse support')
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@ -3,6 +3,7 @@
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#
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# SPDX-License-Identifier: (Apache-2.0 OR MIT)
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import os
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from spack import *
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@ -14,15 +15,25 @@ class PyXgboost(PythonPackage):
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homepage = 'https://xgboost.ai/'
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pypi = 'xgboost/xgboost-1.3.3.tar.gz'
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maintainers = ['adamjstewart']
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import_modules = ['xgboost']
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version('1.3.3', sha256='397051647bb837915f3ff24afc7d49f7fca57630ffd00fb5ef66ae2a0881fb43')
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version('0.90', sha256='d69f90d61a63e8889fd39a31ad00c629bac1ca627f8406b9b6d4594c9e29ab84', deprecated=True)
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variant('pandas', default=False, description='Enable Pandas extensions for training.')
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variant('scikit-learn', default=False, description='Enable scikit-learn extensions for training.')
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variant('dask', default=False, description='Enables Dask extensions for distributed training.')
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variant('plotting', default=False, description='Enables tree and importance plotting.')
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depends_on('cmake', type='build')
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depends_on('python@3.6:', type=('build', 'run'))
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for ver in ['1.3.3']:
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depends_on('xgboost@' + ver, when='@' + ver)
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depends_on('cmake@3.12:', when='@1.0:1.2.999', type='build')
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depends_on('llvm-openmp', when='@:1.2.999 %apple-clang')
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depends_on('python@3.6:', when='@1.2:', type=('build', 'run'))
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depends_on('python@3.5:', when='@1.0:', type=('build', 'run'))
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depends_on('python@3.4:', type=('build', 'run'))
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depends_on('py-setuptools', type=('build'))
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depends_on('py-numpy', type=('build', 'run'))
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depends_on('py-scipy', type=('build', 'run'))
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@ -37,3 +48,43 @@ class PyXgboost(PythonPackage):
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depends_on('py-graphviz', when='+plotting', type=('build', 'run'))
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depends_on('py-matplotlib', when='+plotting', type=('build', 'run'))
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conflicts('+pandas', when='@:0.999')
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conflicts('+scikit-learn', when='@:0.999')
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conflicts('+dask', when='@:0.999')
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conflicts('+plotting', when='@:0.999')
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# `--use-system-libxgboost` is only valid for the 'install' phase, but we want to
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# skip building of the C++ library and rely on an external dependency
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phases = ['install']
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@when('@:0.90')
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def patch(self):
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# Fix OpenMP support on macOS
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filter_file("OPENMP_FLAGS = -fopenmp",
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"OPENMP_FLAGS = {0}".format(self.compiler.openmp_flag),
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os.path.join("xgboost", "Makefile"), string=True)
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@when('@1.3:')
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def patch(self):
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# https://github.com/dmlc/xgboost/issues/6706
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# 'setup.py' is hard-coded to search in Python installation prefix
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filter_file("lib_path = os.path.join(sys.prefix, 'lib')",
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"lib_path = '{0}'".format(self.spec['xgboost'].libs.directories[0]),
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"setup.py", string=True)
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# Same for run-time search
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filter_file("os.path.join(curr_path, 'lib'),",
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"'{0}',".format(self.spec['xgboost'].libs.directories[0]),
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os.path.join('xgboost', 'libpath.py'), string=True)
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@when('@1.3:')
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def install_args(self, spec, prefix):
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args = super(PyXgboost, self).install_args(spec, prefix)
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args.append('--use-system-libxgboost')
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return args
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# Tests need to be re-added since `phases` was overridden
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run_after('install')(
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PythonPackage._run_default_install_time_test_callbacks)
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run_after('install')(PythonPackage.sanity_check_prefix)
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@ -7,25 +7,49 @@
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class Xgboost(CMakePackage, CudaPackage):
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"""Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM)
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Library, for Python, R, Java, Scala, C++ and more. Runs on single
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machine, Hadoop, Spark, Flink and DataFlow"""
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"""XGBoost is an optimized distributed gradient boosting library designed to be
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highly efficient, flexible and portable. It implements machine learning algorithms
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under the Gradient Boosting framework. XGBoost provides a parallel tree boosting
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(also known as GBDT, GBM) that solve many data science problems in a fast and
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accurate way. The same code runs on major distributed environment (Hadoop, SGE, MPI)
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and can solve problems beyond billions of examples."""
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homepage = "https://xgboost.ai/"
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url = "https://github.com/dmlc/xgboost/releases/download/v0.81/xgboost-0.81.tar.bz2"
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git = "https://github.com/dmlc/xgboost.git"
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version('0.90', tag='v0.90', submodules=True)
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version('0.81', sha256='9d8ff161699111d45c96bd15229aa6d80eb1cab7cbbef7e8eaa60ccfb5a4f806')
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maintainers = ['adamjstewart']
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version('master', branch='master', submodules=True)
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version('1.3.3', tag='v1.3.3', submodules=True)
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version('0.90', tag='v0.90', submodules=True, deprecated=True)
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version('0.81', tag='v0.81', submodules=True, deprecated=True)
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variant('nccl', default=False, description='Build with NCCL to enable distributed GPU support')
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variant('openmp', default=True, description='Build with OpenMP support')
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depends_on('cmake@3.13:', type='build')
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depends_on('cmake@3.16:', when='platform=darwin', type='build')
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depends_on('ninja', type='build')
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depends_on('cuda@10:', when='+cuda')
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depends_on('nccl', when='+nccl')
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depends_on('llvm-openmp', when='%apple-clang +openmp')
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conflicts('%gcc@:4.999', msg='GCC version must be at least 5.0!')
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conflicts('+nccl', when='~cuda', msg='NCCL requires CUDA')
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conflicts('+cuda', when='~openmp', msg='CUDA requires OpenMP')
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generator = 'Ninja'
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def cmake_args(self):
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return [
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'-DUSE_CUDA={0}'.format('YES' if '+cuda' in self.spec else 'NO')
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# https://xgboost.readthedocs.io/en/latest/build.html
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args = [
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self.define_from_variant('USE_CUDA', 'cuda'),
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self.define_from_variant('USE_NCCL', 'nccl'),
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self.define_from_variant('USE_OPENMP', 'openmp'),
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]
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def install(self, spec, prefix):
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install_tree(str(self.stage.source_path), prefix)
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# create a bin directory for executable "xgboost" which is possibly
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# used in functional testing of the compilation target "libxgboost"
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mkdirp(prefix.bin)
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install('xgboost', prefix.bin)
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if '+cuda' in self.spec and 'cuda_arch=none' not in self.spec:
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args.append(self.define(
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'GPU_COMPUTE_VER', self.spec.variants['cuda_arch'].value))
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return args
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