5960d74dca
* Update and fix py-dgl+cuda * [@spackbot] updating style on behalf of meyersbs * Update py-dgl
165 lines
6.3 KiB
Python
165 lines
6.3 KiB
Python
# Copyright 2013-2023 Lawrence Livermore National Security, LLC and other
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# Spack Project Developers. See the top-level COPYRIGHT file for details.
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#
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# SPDX-License-Identifier: (Apache-2.0 OR MIT)
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from spack.package import *
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class PyDgl(CMakePackage, PythonExtension, CudaPackage):
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"""Deep Graph Library (DGL).
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DGL is an easy-to-use, high performance and scalable Python package for
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deep learning on graphs. DGL is framework agnostic, meaning if a deep graph
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model is a component of an end-to-end application, the rest of the logics
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can be implemented in any major frameworks, such as PyTorch, Apache MXNet
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or TensorFlow."""
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homepage = "https://www.dgl.ai/"
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git = "https://github.com/dmlc/dgl.git"
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maintainers("adamjstewart", "meyersbs")
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version("master", branch="master", submodules=True)
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version("1.0.1", tag="1.0.1", submodules=True)
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version("0.4.3", tag="0.4.3", submodules=True)
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version("0.4.2", tag="0.4.2", submodules=True)
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variant("cuda", default=True, description="Build with CUDA")
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variant("openmp", default=True, description="Build with OpenMP")
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variant(
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"backend",
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default="pytorch",
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description="Default backend",
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values=["pytorch", "mxnet", "tensorflow"],
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multi=False,
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)
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depends_on("cmake@3.5:", type="build")
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depends_on("llvm-openmp", when="%apple-clang +openmp")
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# Python dependencies
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# See python/setup.py
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extends("python")
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depends_on("python@3.5:", type=("build", "run"))
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depends_on("py-pip", type="build")
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depends_on("py-wheel", type="build")
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depends_on("py-setuptools", type="build")
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depends_on("py-cython", type="build")
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depends_on("py-numpy@1.14.0:", type=("build", "run"))
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depends_on("py-scipy@1.1.0:", type=("build", "run"))
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depends_on("py-networkx@2.1:", type=("build", "run"))
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depends_on("py-requests@2.19.0:", when="@0.4.3:", type=("build", "run"))
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depends_on("py-tqdm", when="@1.0.1:", type=("build", "run"))
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depends_on("py-psutil@5.8.0:", when="@1.0.1:", type=("build", "run"))
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# Backends
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# See https://docs.dgl.ai/install/index.html#working-with-different-backends
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depends_on("py-torch@1.12.0:", when="@1.0.1: backend=pytorch", type="run")
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depends_on("py-torch@1.2.0:", when="@0.4.3: backend=pytorch", type="run")
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depends_on("py-torch@0.4.1:", when="backend=pytorch", type="run")
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depends_on("mxnet@1.6.0:", when="@1.0.1: backend=mxnet", type="run")
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depends_on("mxnet@1.5.1:", when="@0.4.3: backend=mxnet", type="run")
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depends_on("mxnet@1.5.0:", when="backend=mxnet", type="run")
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depends_on("py-tensorflow@2.3:", when="@1.0.1: backend=tensorflow", type="run")
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depends_on("py-tensorflow@2.1:", when="@0.4.3: backend=tensorflow", type="run")
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depends_on("py-tensorflow@2.0:", when="backend=tensorflow", type="run")
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# Cuda
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# See https://github.com/dmlc/dgl/issues/3083
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depends_on("cuda@:10", when="@:0.4 +cuda", type=("build", "run"))
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# From error: "Your installed Caffe2 version uses cuDNN but I cannot find the
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# cuDNN libraries. Please set the proper cuDNN prefixes and / or install cuDNN."
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depends_on("cudnn", when="+cuda", type=("build", "run"))
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patch(
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"https://patch-diff.githubusercontent.com/raw/dmlc/dgl/pull/5434.patch?full_index=1",
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sha256="8c5f14784637a9bb3dd55e6104715d4a35b4e6594c99884aa19e67bc0544e91a",
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when="@1.0.1",
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)
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build_directory = "build"
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# https://docs.dgl.ai/install/index.html#install-from-source
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def cmake_args(self):
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args = []
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if "+cuda" in self.spec:
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args.append("-DUSE_CUDA=ON")
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# Prevent defaulting to old compute_ and sm_ despite defining cuda_arch
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args.append("-DCUDA_ARCH_NAME=Manual")
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cuda_arch_list = " ".join(list(self.spec.variants["cuda_arch"].value))
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args.append("-DCUDA_ARCH_BIN={0}".format(cuda_arch_list))
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args.append("_DCUDA_ARCH_PTX={0}".format(cuda_arch_list))
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else:
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args.append("-DUSE_CUDA=OFF")
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if "+openmp" in self.spec:
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args.append("-DUSE_OPENMP=ON")
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if self.spec.satisfies("%apple-clang"):
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args.extend(
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[
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"-DOpenMP_CXX_FLAGS=" + self.spec["llvm-openmp"].headers.include_flags,
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"-DOpenMP_CXX_LIB_NAMES=" + self.spec["llvm-openmp"].libs.names[0],
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"-DOpenMP_C_FLAGS=" + self.spec["llvm-openmp"].headers.include_flags,
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"-DOpenMP_C_LIB_NAMES=" + self.spec["llvm-openmp"].libs.names[0],
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"-DOpenMP_omp_LIBRARY=" + self.spec["llvm-openmp"].libs[0],
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]
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)
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else:
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args.append("-DUSE_OPENMP=OFF")
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if self.run_tests:
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args.append("-DBUILD_CPP_TEST=ON")
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else:
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args.append("-DBUILD_CPP_TEST=OFF")
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return args
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def install(self, spec, prefix):
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with working_dir("python"):
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args = std_pip_args + ["--prefix=" + prefix, "."]
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pip(*args)
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# Older versions do not install correctly
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if self.spec.satisfies("@:0.4.3"):
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# Work around installation bug: https://github.com/dmlc/dgl/issues/1379
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install_tree(prefix.dgl, prefix.lib)
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def setup_run_environment(self, env):
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# https://docs.dgl.ai/install/backend.html
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backend = self.spec.variants["backend"].value
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env.set("DGLBACKEND", backend)
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@property
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def import_modules(self):
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modules = [
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"dgl",
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"dgl.nn",
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"dgl.runtime",
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"dgl.backend",
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"dgl.function",
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"dgl.contrib",
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"dgl._ffi",
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"dgl.data",
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"dgl.runtime.ir",
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"dgl.backend.numpy",
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"dgl.contrib.sampling",
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"dgl._ffi._cy2",
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"dgl._ffi._cy3",
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"dgl._ffi._ctypes",
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]
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if "backend=pytorch" in self.spec:
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modules.extend(["dgl.nn.pytorch", "dgl.nn.pytorch.conv", "dgl.backend.pytorch"])
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elif "backend=mxnet" in self.spec:
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modules.extend(["dgl.nn.mxnet", "dgl.nn.mxnet.conv", "dgl.backend.mxnet"])
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elif "backend=tensorflow" in self.spec:
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modules.extend(
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["dgl.nn.tensorflow", "dgl.nn.tensorflow.conv", "dgl.backend.tensorflow"]
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)
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return modules
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