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# Copyright 2013-2020 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)
from spack import *
class PyTorch(PythonPackage, CudaPackage):
"""Tensors and Dynamic neural networks in Python
with strong GPU acceleration."""
homepage = "https://pytorch.org/"
git = "https://github.com/pytorch/pytorch.git"
install_time_test_callbacks = ['install_test', 'import_module_test']
maintainers = ['adamjstewart']
import_modules = [
'tools', 'caffe2', 'torch', 'tools.cwrap', 'tools.autograd',
'tools.setup_helpers', 'tools.shared', 'tools.jit', 'tools.pyi',
'tools.nnwrap', 'tools.cwrap.plugins', 'caffe2.core', 'caffe2.proto',
'caffe2.python', 'caffe2.distributed', 'caffe2.perfkernels',
'caffe2.experiments', 'caffe2.contrib', 'caffe2.quantization',
'caffe2.core.nomnigraph', 'caffe2.python.ideep', 'caffe2.python.mint',
'caffe2.python.layers', 'caffe2.python.onnx', 'caffe2.python.trt',
'caffe2.python.models', 'caffe2.python.docs', 'caffe2.python.modeling',
'caffe2.python.mkl', 'caffe2.python.examples',
'caffe2.python.predictor', 'caffe2.python.helpers',
'caffe2.python.rnn', 'caffe2.python.onnx.bin',
'caffe2.python.models.seq2seq', 'caffe2.experiments.python',
'caffe2.contrib.nnpack', 'caffe2.contrib.warpctc',
'caffe2.contrib.nccl', 'caffe2.contrib.playground',
'caffe2.contrib.gloo', 'caffe2.contrib.script', 'caffe2.contrib.prof',
'caffe2.contrib.tensorboard', 'caffe2.contrib.aten',
'caffe2.contrib.playground.resnetdemo',
'caffe2.contrib.script.examples', 'caffe2.contrib.aten.docs',
'caffe2.quantization.server', 'torch.nn', 'torch.onnx',
'torch.distributed', 'torch.autograd', 'torch.multiprocessing',
'torch.cuda', 'torch.backends', 'torch.optim', 'torch.utils',
'torch.contrib', 'torch.jit', 'torch.sparse',
'torch.for_onnx', 'torch._thnn', 'torch.distributions',
'torch.nn.parallel', 'torch.nn._functions', 'torch.nn.backends',
'torch.nn.utils', 'torch.nn.modules', 'torch.nn.parallel.deprecated',
'torch.nn._functions.thnn', 'torch.distributed.deprecated',
'torch.autograd._functions', 'torch.backends.cuda',
'torch.backends.mkl', 'torch.backends.mkldnn', 'torch.backends.openmp',
'torch.backends.cudnn', 'torch.utils.backcompat',
'torch.utils.bottleneck', 'torch.utils.ffi', 'torch.utils.tensorboard',
'torch.utils.data', 'torch.utils.data._utils'
]
version('master', branch='master', submodules=True)
version('1.5.0', tag='v1.5.0', submodules=True)
version('1.4.1', tag='v1.4.1', submodules=True)
version('1.4.0', tag='v1.4.0', submodules=True,
submodules_delete=['third_party/fbgemm'])
version('1.3.1', tag='v1.3.1', submodules=True)
version('1.3.0', tag='v1.3.0', submodules=True)
version('1.2.0', tag='v1.2.0', submodules=True)
version('1.1.0', tag='v1.1.0', submodules=True)
version('1.0.1', tag='v1.0.1', submodules=True)
version('1.0.0', tag='v1.0.0', submodules=True)
version('0.4.1', tag='v0.4.1', submodules=True,
submodules_delete=['third_party/nervanagpu'])
version('0.4.0', tag='v0.4.0', submodules=True)
version('0.3.1', tag='v0.3.1', submodules=True)
variant('cuda', default=True, description='Build with CUDA')
variant('cudnn', default=True, description='Enables the cuDNN build')
variant('magma', default=False, description='Enables the MAGMA build')
variant('fbgemm', default=False, description='Enables the FBGEMM build')
variant('test', default=False, description='Enables the test build')
variant('miopen', default=False, description='Enables the MIOpen build')
variant('mkldnn', default=True, description='Enables use of MKLDNN')
variant('nnpack', default=False, description='Enables NNPACK build')
variant('qnnpack', default=False, description='Enables QNNPACK build (quantized 8-bit operators)')
variant('xnnpack', default=False, description='Enables XNNPACK build')
variant('distributed', default=False, description='Enables distributed (c10d, gloo, mpi, etc.) build')
variant('nccl', default=True, description='Use Spack-installed NCCL')
variant('caffe2', default=False, description='Enables Caffe2 operators build')
variant('gloo', default=False, description='Enables features related to distributed support')
variant('opencv', default=False, description='Enables use of OpenCV for additional operators')
variant('openmp', default=True, description='Enables use of OpenMP for parallelization')
variant('ffmpeg', default=False, description='Enables use of ffmpeg for additional operators')
variant('leveldb', default=False, description='Enables use of LevelDB for storage')
variant('lmdb', default=False, description='Enables use of LMDB for storage')
variant('binary', default=False, description='Enables the additional binaries/ build')
variant('redis', default=False, description='Use Redis for distributed workflows')
variant('zstd', default=False, description='Enables use of ZSTD')
variant('tbb', default=False, description='Enables TBB support')
conflicts('+cudnn', when='~cuda')
conflicts('+magma', when='~cuda')
conflicts('+fbgemm', when='@:0.4')
conflicts('+miopen', when='@:0.4')
conflicts('+mkldnn', when='@:0.3')
conflicts('+qnnpack', when='@:0.4')
conflicts('+xnnpack', when='@:1.4')
conflicts('+nccl', when='~cuda')
conflicts('+opencv', when='@:0.4')
conflicts('+ffmpeg', when='@:0.4')
conflicts('+leveldb', when='@:0.4')
conflicts('+lmdb', when='@:0.4')
conflicts('+binary', when='@:0.4')
conflicts('+redis', when='@:1.0')
conflicts('+zstd', when='@:1.0')
conflicts('+tbb', when='@:1.1')
# https://github.com/pytorch/pytorch/issues/35149
conflicts('+fbgemm', when='@1.4.0')
# https://github.com/pytorch/pytorch/issues/35478
conflicts('%clang@11.0.3-apple',
msg='Apple Clang 11.0.3 segfaults at build-time')
conflicts('cuda_arch=none', when='+cuda',
msg='Must specify CUDA compute capabilities of your GPU, see '
'https://developer.nvidia.com/cuda-gpus')
# Required dependencies
depends_on('cmake@3.5:', type='build')
# Use Ninja generator to speed up build times
# Automatically used if found
depends_on('ninja@1.5:', type='build')
depends_on('python@3.5:', when='@1.5:', type=('build', 'run'))
depends_on('python@2.7:2.8,3.5:', type=('build', 'run'))
depends_on('py-setuptools', type='build')
depends_on('py-numpy', type=('build', 'run'))
depends_on('py-future', when='@1.1: ^python@:2', type='build')
depends_on('py-pyyaml', type=('build', 'run'))
depends_on('py-typing', when='@0.4: ^python@:3.4', type=('build', 'run'))
depends_on('py-pybind11', when='@0.4:', type=('build', 'run'))
depends_on('blas')
depends_on('lapack')
depends_on('protobuf', when='@0.4:')
depends_on('eigen', when='@0.4:')
# TODO: replace all third_party packages with Spack packages
# Optional dependencies
depends_on('cuda@7.5:', when='+cuda', type=('build', 'link', 'run'))
depends_on('cuda@9:', when='@1.1:+cuda', type=('build', 'link', 'run'))
depends_on('cudnn@6:', when='+cudnn')
depends_on('cudnn@7:', when='@1.1:+cudnn')
depends_on('magma', when='+magma')
# TODO: add dependency: https://github.com/pytorch/FBGEMM
# depends_on('fbgemm', when='+fbgemm')
# TODO: add dependency: https://github.com/ROCmSoftwarePlatform/MIOpen
# depends_on('miopen', when='+miopen')
# TODO: See if there is a way to use an external mkldnn installation.
# Currently, only older versions of py-torch use an external mkldnn
# library.
depends_on('onednn', when='@0.4:0.4.1+mkldnn')
# TODO: add dependency: https://github.com/Maratyszcza/NNPACK
# depends_on('nnpack', when='+nnpack')
depends_on('qnnpack', when='+qnnpack')
# TODO: add dependency: https://github.com/google/XNNPACK
# depends_on('xnnpack', when='+xnnpack')
depends_on('mpi', when='+distributed')
depends_on('nccl', when='+nccl')
depends_on('gloo', when='+gloo')
depends_on('opencv', when='+opencv')
depends_on('llvm-openmp', when='%clang platform=darwin +openmp')
depends_on('ffmpeg', when='+ffmpeg')
depends_on('leveldb', when='+leveldb')
depends_on('lmdb', when='+lmdb')
depends_on('redis', when='+redis')
depends_on('zstd', when='+zstd')
depends_on('tbb', when='+tbb')
# Test dependencies
depends_on('py-hypothesis', type='test')
depends_on('py-six', type='test')
depends_on('py-psutil', type='test')
# Both build and install run cmake/make/make install
# Only run once to speed up build times
phases = ['install']
def setup_build_environment(self, env):
def enable_or_disable(variant, keyword='USE', var=None, newer=False):
"""Set environment variable to enable or disable support for a
particular variant.
Parameters:
variant (str): the variant to check
keyword (str): the prefix to use for enabling/disabling
var (str): CMake variable to set. Defaults to variant.upper()
newer (bool): newer variants that never used NO_*
"""
if var is None:
var = variant.upper()
# Version 1.1.0 switched from NO_* to USE_* or BUILD_*
# But some newer variants have always used USE_* or BUILD_*
if self.spec.satisfies('@1.1:') or newer:
if '+' + variant in self.spec:
env.set(keyword + '_' + var, 'ON')
else:
env.set(keyword + '_' + var, 'OFF')
else:
if '+' + variant in self.spec:
env.unset('NO_' + var)
else:
env.set('NO_' + var, 'ON')
# Build in parallel to speed up build times
env.set('MAX_JOBS', make_jobs)
# Spack logs have trouble handling colored output
env.set('COLORIZE_OUTPUT', 'OFF')
# Don't use vendored third-party libraries
env.set('BUILD_CUSTOM_PROTOBUF', 'OFF')
env.set('USE_PYTORCH_QNNPACK', 'OFF')
env.set('USE_SYSTEM_EIGEN_INSTALL', 'ON')
env.set('pybind11_DIR', self.spec['py-pybind11'].prefix)
env.set('pybind11_INCLUDE_DIR',
self.spec['py-pybind11'].prefix.include)
enable_or_disable('cuda')
if '+cuda' in self.spec:
env.set('CUDA_HOME', self.spec['cuda'].prefix)
torch_cuda_arch = ';'.join('{0:.1f}'.format(float(i) / 10.0) for i
in
self.spec.variants['cuda_arch'].value)
env.set('TORCH_CUDA_ARCH_LIST', torch_cuda_arch)
enable_or_disable('cudnn')
if '+cudnn' in self.spec:
env.set('CUDNN_LIB_DIR', self.spec['cudnn'].libs.directories[0])
env.set('CUDNN_INCLUDE_DIR', self.spec['cudnn'].prefix.include)
env.set('CUDNN_LIBRARY', self.spec['cudnn'].libs[0])
enable_or_disable('fbgemm')
enable_or_disable('test', keyword='BUILD')
if '+miopen' in self.spec:
env.set('MIOPEN_LIB_DIR', self.spec['miopen'].libs.directories[0])
env.set('MIOPEN_INCLUDE_DIR', self.spec['miopen'].prefix.include)
env.set('MIOPEN_LIBRARY', self.spec['miopen'].libs[0])
enable_or_disable('mkldnn')
if '@0.4:0.4.1+mkldnn' in self.spec:
env.set('MKLDNN_HOME', self.spec['intel-mkl-dnn'].prefix)
enable_or_disable('nnpack')
enable_or_disable('qnnpack')
enable_or_disable('xnnpack')
enable_or_disable('distributed')
enable_or_disable('nccl')
enable_or_disable('nccl', var='SYSTEM_NCCL')
if '+nccl' in self.spec:
env.set('NCCL_ROOT', self.spec['nccl'].prefix)
env.set('NCCL_LIB_DIR', self.spec['nccl'].libs.directories[0])
env.set('NCCL_INCLUDE_DIR', self.spec['nccl'].prefix.include)
enable_or_disable('caffe2', keyword='BUILD', var='CAFFE2_OPS')
enable_or_disable('gloo', newer=True)
enable_or_disable('opencv', newer=True)
enable_or_disable('openmp', newer=True)
enable_or_disable('ffmpeg', newer=True)
enable_or_disable('leveldb', newer=True)
enable_or_disable('lmdb', newer=True)
enable_or_disable('binary', keyword='BUILD', newer=True)
env.set('PYTORCH_BUILD_VERSION', self.version)
env.set('PYTORCH_BUILD_NUMBER', 0)
# BLAS to be used by Caffe2
if '^mkl' in self.spec:
env.set('BLAS', 'MKL')
elif '^atlas' in self.spec:
env.set('BLAS', 'ATLAS')
elif '^openblas' in self.spec:
env.set('BLAS', 'OpenBLAS')
elif '^veclibfort' in self.spec:
env.set('BLAS', 'vecLib')
elif '^libflame' in self.spec:
env.set('BLAS', 'FLAME')
elif '^eigen' in self.spec:
env.set('BLAS', 'Eigen')
enable_or_disable('redis', newer=True)
enable_or_disable('zstd', newer=True)
enable_or_disable('tbb', newer=True)
def install_test(self):
with working_dir('test'):
python('run_test.py')
# 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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