Modernize py-torch-geometric and dependencies (#43984)
* Modernize py-torch-geometric and dependencies * Forgot one maintainer
This commit is contained in:
Adam J. Stewart
GitHub
parent
a1d69f8661
commit
8a1b69c1d3
5 changed files with 173 additions and 110 deletions
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@ -7,25 +7,33 @@
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class PyTorchCluster(PythonPackage):
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"""This package consists of a small extension library of highly optimized graph cluster
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algorithms for the use in PyTorch.
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"""
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"""PyTorch Extension Library of Optimized Graph Cluster Algorithms."""
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homepage = "https://github.com/rusty1s/pytorch_cluster"
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url = "https://github.com/rusty1s/pytorch_cluster/archive/1.5.7.tar.gz"
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pypi = "torch-cluster/torch_cluster-1.6.3.tar.gz"
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git = "https://github.com/rusty1s/pytorch_cluster.git"
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license("MIT")
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maintainers("adamjstewart")
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version("1.6.3", sha256="0e2b08095e03cf87ce9b23b7a7352236a25d3ed92d92351dc020fd927ea8dbfe")
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version("1.5.8", sha256="95c6e81e9c4a6235e1b2152ab917021d2060ad995199f6bd7fb39986d37310f0")
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version("1.5.7", sha256="71701d2f7f3e458ebe5904c982951349fdb60e6f1654e19c7e102a226e2de72e")
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variant("cuda", default=False, description="Enables CUDA support")
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version("1.6.3", sha256="78d5a930a5bbd0d8788df8c6d66addd68d6dd292fe3edb401e3dacba26308152")
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version(
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"1.5.8",
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sha256="a0a32f63faac40a026ab1e9da31f6babdb4d937e53be40bd1c91d9b5a286eee6",
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deprecated=True,
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)
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version(
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"1.5.7",
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sha256="62a3ec1bebadda1a4a2c867203f4c957b9c0b9d11ffb03b40b8ea9f95a0a4d3b",
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deprecated=True,
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)
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depends_on("python", type=("build", "link", "run"))
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depends_on("py-setuptools", type="build")
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depends_on("py-scipy", type=("build", "run"))
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depends_on("py-torch+cuda", when="+cuda", type=("build", "link", "run"))
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depends_on("py-torch~cuda", when="~cuda", type=("build", "link", "run"))
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# Undocumented dependencies
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depends_on("py-torch", type=("build", "link", "run"))
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# https://github.com/rusty1s/pytorch_cluster/issues/120
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depends_on("py-torch~openmp", when="@:1.5 %apple-clang", type=("build", "link", "run"))
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@ -34,8 +42,19 @@ class PyTorchCluster(PythonPackage):
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depends_on("py-pytest-runner", when="@:1.5", type="build")
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def setup_build_environment(self, env):
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if "+cuda" in self.spec:
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env.set("FORCE_CUDA", "1")
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env.set("CUDA_HOME", self.spec["cuda"].prefix)
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if self.spec.satisfies("@1.5.9:"):
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if "+cuda" in self.spec["py-torch"]:
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env.set("FORCE_CUDA", 1)
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env.set("FORCE_ONLY_CUDA", 0)
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env.set("FORCE_ONLY_CPU", 0)
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else:
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env.set("FORCE_CUDA", 0)
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env.set("FORCE_ONLY_CUDA", 0)
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env.set("FORCE_ONLY_CPU", 1)
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else:
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env.set("FORCE_CUDA", "0")
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if "+cuda" in self.spec["py-torch"]:
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env.set("FORCE_CUDA", 1)
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env.set("FORCE_CPU", 0)
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else:
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env.set("FORCE_CUDA", 0)
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env.set("FORCE_CPU", 1)
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@ -8,57 +8,51 @@
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class PyTorchGeometric(PythonPackage):
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"""PyTorch Geometric (PyG) is a geometric deep learning extension
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library for PyTorch. It consists of various methods for deep
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learning on graphs and other irregular structures, also known as
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geometric deep learning, from a variety of published papers. In
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addition, it consists of an easy-to-use mini-batch loader for many
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small and single giant graphs, multi gpu-support, a large number
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of common benchmark datasets (based on simple interfaces to create
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your own), and helpful transforms, both for learning on arbitrary
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graphs as well as on 3D meshes or point clouds."""
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"""Graph Neural Network Library for PyTorch."""
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homepage = "https://github.com/pyg-team/pytorch_geometric"
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pypi = "torch-geometric/torch_geometric-2.1.0.post1.tar.gz"
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homepage = "https://pyg.org/"
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pypi = "torch-geometric/torch_geometric-2.5.3.tar.gz"
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git = "https://github.com/pyg-team/pytorch_geometric.git"
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license("MIT")
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maintainers("adamjstewart")
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version("2.5.3", sha256="ad0761650c8fa56cdc46ee61c564fd4995f07f079965fe732b3a76d109fd3edc")
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version(
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"2.1.0.post1", sha256="32347402076ccf60fa50312825178f1e3e5ce5e7b3b3a8b2729ac699da24525d"
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"2.1.0.post1",
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sha256="32347402076ccf60fa50312825178f1e3e5ce5e7b3b3a8b2729ac699da24525d",
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deprecated=True,
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)
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version(
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"1.6.3",
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sha256="347f693bebcc8a621eda4867dafab91c04db5f596d7ed7ecb89b242f8ab5c6a1",
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deprecated=True,
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)
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version(
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"1.6.0",
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sha256="fbf43fe15421c9affc4fb361ba4db55cb9d3c64d0c29576bb58d332bf6d27fef",
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deprecated=True,
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)
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version("1.6.3", sha256="347f693bebcc8a621eda4867dafab91c04db5f596d7ed7ecb89b242f8ab5c6a1")
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version("1.6.0", sha256="fbf43fe15421c9affc4fb361ba4db55cb9d3c64d0c29576bb58d332bf6d27fef")
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variant("cuda", default=False, description="Enable CUDA support")
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depends_on("py-flit-core@3.2:3", when="@2.4:", type="build")
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# setup.py
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depends_on("python@3.7:", when="@2:", type=("build", "run"))
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depends_on("python@3.6:", type=("build", "run"))
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depends_on("py-setuptools", type="build")
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depends_on("py-tqdm", type=("build", "run"))
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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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depends_on("py-jinja2", type=("build", "run"))
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depends_on("py-requests", type=("build", "run"))
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depends_on("py-pyparsing", when="@2:", type=("build", "run"))
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depends_on("py-scikit-learn", type=("build", "run"))
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with default_args(type=("build", "run")):
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depends_on("py-tqdm")
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depends_on("py-numpy")
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depends_on("py-scipy")
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depends_on("py-fsspec", when="@2.5:")
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depends_on("py-jinja2")
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depends_on("py-aiohttp", when="@2.5:")
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depends_on("py-requests")
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depends_on("py-pyparsing", when="@1.7.2:")
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depends_on("py-scikit-learn")
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depends_on("py-psutil@5.8:", when="@2.2:")
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# README.md
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depends_on("py-torch-scatter+cuda", when="+cuda", type=("build", "run"))
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depends_on("py-torch-scatter~cuda", when="~cuda", type=("build", "run"))
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depends_on("py-torch-sparse+cuda", when="+cuda", type=("build", "run"))
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depends_on("py-torch-sparse~cuda", when="~cuda", type=("build", "run"))
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# Undocumented dependencies
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depends_on("py-torch")
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# Optional dependencies
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depends_on("py-torch-cluster+cuda", when="+cuda", type=("build", "run"))
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depends_on("py-torch-cluster~cuda", when="~cuda", type=("build", "run"))
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depends_on("py-torch-spline-conv+cuda", when="+cuda", type=("build", "run"))
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depends_on("py-torch-spline-conv~cuda", when="~cuda", type=("build", "run"))
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# Undocumented dependencies
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depends_on("py-torch", type=("build", "run"))
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# Historic or optional dependencies
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# Historical dependencies
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depends_on("py-setuptools", type="build", when="@:2.3")
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with when("@:1"):
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depends_on("py-pytest-runner", type="build")
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depends_on("py-networkx", type=("build", "run"))
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@ -69,10 +63,3 @@ class PyTorchGeometric(PythonPackage):
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depends_on("py-googledrivedownloader", type=("build", "run"))
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depends_on("py-h5py~mpi", type=("build", "run"))
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depends_on("py-ase", type=("build", "run"))
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def setup_build_environment(self, env):
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if "+cuda" in self.spec:
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env.set("FORCE_CUDA", "1")
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env.set("CUDA_HOME", self.spec["cuda"].prefix)
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else:
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env.set("FORCE_CUDA", "0")
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@ -7,29 +7,45 @@
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class PyTorchScatter(PythonPackage):
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"""This package consists of a small extension library of
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highly optimized sparse update (scatter and segment)
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operations for the use in PyTorch, which are missing in the
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main package."""
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"""PyTorch Extension Library of Optimized Scatter Operations."""
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homepage = "https://github.com/rusty1s/pytorch_scatter"
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url = "https://github.com/rusty1s/pytorch_scatter/archive/2.0.5.tar.gz"
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pypi = "torch-scatter/torch_scatter-2.1.2.tar.gz"
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git = "https://github.com/rusty1s/pytorch_scatter.git"
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license("MIT")
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maintainers("adamjstewart")
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version("2.0.5", sha256="e29b364beaa9c84a99e0e236be89ed19d4452d89010ff736184ddcce488b47f6")
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version("2.1.2", sha256="69b3aa435f2424ac6a1bfb6ff702da6eb73b33ca0db38fb26989c74159258e47")
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version(
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"2.0.5",
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sha256="148fbe634fb9e9465dbde2ab337138f63650ed8abbac42bb3f565e3fe92e9b2f",
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deprecated=True,
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)
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variant("cuda", default=False, description="Enable CUDA support")
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depends_on("python@3.6:", type=("build", "run"))
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depends_on("python", type=("build", "link", "run"))
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depends_on("py-setuptools", type="build")
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depends_on("py-pytest-runner", type="build")
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depends_on("py-torch+cuda", when="+cuda")
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depends_on("py-torch~cuda", when="~cuda")
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# Undocumented dependencies
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depends_on("py-torch", type=("build", "link", "run"))
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# Historical dependencies
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depends_on("py-pytest-runner", type="build", when="@:2.0.7")
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def setup_build_environment(self, env):
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if "+cuda" in self.spec:
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env.set("FORCE_CUDA", "1")
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env.set("CUDA_HOME", self.spec["cuda"].prefix)
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if self.spec.satisfies("@2.0.6:"):
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if "+cuda" in self.spec["py-torch"]:
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env.set("FORCE_CUDA", 1)
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env.set("FORCE_ONLY_CUDA", 0)
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env.set("FORCE_ONLY_CPU", 0)
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else:
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env.set("FORCE_CUDA", 0)
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env.set("FORCE_ONLY_CUDA", 0)
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env.set("FORCE_ONLY_CPU", 1)
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else:
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env.set("FORCE_CUDA", "0")
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if "+cuda" in self.spec["py-torch"]:
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env.set("FORCE_CUDA", 1)
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env.set("FORCE_CPU", 0)
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else:
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env.set("FORCE_CUDA", 0)
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env.set("FORCE_CPU", 1)
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@ -7,31 +7,54 @@
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class PyTorchSparse(PythonPackage):
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"""This package consists of a small extension library of
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optimized sparse matrix operations with autograd support."""
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"""PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations."""
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homepage = "https://github.com/rusty1s/pytorch_sparse/"
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url = "https://github.com/rusty1s/pytorch_sparse/archive/0.6.7.tar.gz"
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homepage = "https://github.com/rusty1s/pytorch_sparse"
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pypi = "torch-sparse/torch_sparse-0.6.18.tar.gz"
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git = "https://github.com/rusty1s/pytorch_sparse.git"
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license("MIT")
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maintainers("adamjstewart")
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version("0.6.17", sha256="c964a70ed978bff65009250eb12fae96317c60c9a04d7d1b07f0beee8b4b9c22")
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version("0.6.8", sha256="98f7ff1f0f9cd5031bc81c70c11970c3864545ae33677025a6efd2466a97e6f9")
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version("0.6.7", sha256="0d038a1502548692972a085cd0496460b5d2050bb7328427add990f081d6c44d")
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variant("cuda", default=False, description="Enable CUDA support")
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version("0.6.18", sha256="2f14c510a6e93f404c6ea357210615b3c15a71731f9dbd86f25434e34fb5a741")
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version("0.6.17", sha256="06e268dd77f73eb641da8f9383306d7afac6423383c9197b9df120955e2a96bd")
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version("0.6.8", sha256="312fb5ae6e4e575fca4bbc0bd092af85e7679d5b8e53459f24492fc2a073c7b6")
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version("0.6.7", sha256="f69b2ed35baf2a9853234756a2b19e6f7ce88d2c1f029d1c7ca166d91e1adbd0")
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depends_on("py-setuptools", type="build")
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depends_on("py-pytest-runner", when="@:0.6.8", type="build")
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depends_on("py-scipy", type=("build", "run"))
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depends_on("py-torch", type=("build", "run"))
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depends_on("py-torch-scatter+cuda", when="+cuda")
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depends_on("py-torch-scatter~cuda", when="~cuda")
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# Undocumented dependencies
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depends_on("py-torch", type=("build", "link", "run"))
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depends_on("py-torch-scatter", type=("build", "run"))
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depends_on("parallel-hashmap", when="@0.6.17:")
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# Historical dependencies
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depends_on("py-pytest-runner", when="@:0.6.8", type="build")
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def patch(self):
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# Force build against externally-installed hashmap
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filter_file(
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"include_dirs=[extensions_dir, phmap_dir]",
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"include_dirs=[extensions_dir]",
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"setup.py",
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string=True,
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)
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def setup_build_environment(self, env):
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if "+cuda" in self.spec:
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env.set("FORCE_CUDA", "1")
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env.set("CUDA_HOME", self.spec["cuda"].prefix)
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if self.spec.satisfies("@0.6.9:"):
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if "+cuda" in self.spec["py-torch"]:
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env.set("FORCE_CUDA", 1)
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env.set("FORCE_ONLY_CUDA", 0)
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env.set("FORCE_ONLY_CPU", 0)
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else:
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env.set("FORCE_CUDA", 0)
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env.set("FORCE_ONLY_CUDA", 0)
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env.set("FORCE_ONLY_CPU", 1)
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else:
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env.set("FORCE_CUDA", "0")
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if "+cuda" in self.spec["py-torch"]:
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env.set("FORCE_CUDA", 1)
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env.set("FORCE_CPU", 0)
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else:
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env.set("FORCE_CUDA", 0)
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env.set("FORCE_CPU", 1)
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@ -7,27 +7,45 @@
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class PyTorchSplineConv(PythonPackage):
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"""This is a PyTorch implementation of the spline-based
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convolution operator of SplineCNN."""
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"""Implementation of the Spline-Based Convolution Operator of SplineCNN in PyTorch."""
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homepage = "https://github.com/rusty1s/pytorch_spline_conv"
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url = "https://github.com/rusty1s/pytorch_spline_conv/archive/1.2.0.tar.gz"
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pypi = "torch-spline-conv/torch_spline_conv-1.2.2.tar.gz"
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git = "https://github.com/rusty1s/pytorch_spline_conv.git"
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license("MIT")
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maintainers("adamjstewart")
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version("1.2.0", sha256="ab8da41357c8a4785662366655bb6dc5e84fd0e938008194955409aefe535009")
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version("1.2.2", sha256="ed45a81da29f774665dbdd4709d7e534cdf16d2e7006dbd06957f35bd09661b2")
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version(
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"1.2.0",
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sha256="b7a1788004f6c6143d47040f2dd7d8a579a0c69a0cb0b5d7537416bf37c082a5",
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deprecated=True,
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)
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variant("cuda", default=False, description="Enable CUDA support")
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depends_on("python@3.6:", type=("build", "run"))
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depends_on("python", type=("build", "link", "run"))
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depends_on("py-setuptools", type="build")
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depends_on("py-pytest-runner", type="build")
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depends_on("py-torch+cuda", when="+cuda")
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depends_on("py-torch~cuda", when="~cuda")
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# Undocumented dependencies
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depends_on("py-torch", type=("build", "link", "run"))
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# Historical dependencies
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depends_on("py-pytest-runner", type="build", when="@:1.2.1")
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def setup_build_environment(self, env):
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if "+cuda" in self.spec:
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env.set("FORCE_CUDA", "1")
|
||||
env.set("CUDA_HOME", self.spec["cuda"].prefix)
|
||||
if self.spec.satisfies("@1.2.1:"):
|
||||
if "+cuda" in self.spec["py-torch"]:
|
||||
env.set("FORCE_CUDA", 1)
|
||||
env.set("FORCE_ONLY_CUDA", 0)
|
||||
env.set("FORCE_ONLY_CPU", 0)
|
||||
else:
|
||||
env.set("FORCE_CUDA", 0)
|
||||
env.set("FORCE_ONLY_CUDA", 0)
|
||||
env.set("FORCE_ONLY_CPU", 1)
|
||||
else:
|
||||
env.set("FORCE_CUDA", "0")
|
||||
if "+cuda" in self.spec["py-torch"]:
|
||||
env.set("FORCE_CUDA", 1)
|
||||
env.set("FORCE_CPU", 0)
|
||||
else:
|
||||
env.set("FORCE_CUDA", 0)
|
||||
env.set("FORCE_CPU", 1)
|
||||
|
|
|
|||
Loading…
Reference in a new issue