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# Copyright 2013-2022 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)
import json
from spack.package import *
class PyChainer(PythonPackage):
"""
Chainer is a Python-based deep learning framework aiming at flexibility.
It provides automatic differentiation APIs based on the define-by-run
approach (a.k.a. dynamic computational graphs) as well as object-oriented
high-level APIs to build and train neural networks.
It also supports CUDA/cuDNN using CuPy for high performance training
and inference.
"""
homepage = "https://chainer.org/"
url = "https://github.com/chainer/chainer/archive/v7.2.0.tar.gz"
maintainers = ["adamjstewart"]
version("7.2.0", sha256="6e2fba648cc5b8a5421e494385b76fe5ec154f1028a1c5908557f5d16c04f0b3")
version("6.7.0", sha256="87cb3378a35e7c5c695028ec91d58dc062356bc91412384ea939d71374610389")
variant("mn", default=False, description="run with ChainerMN")
depends_on("python@3.5.1:", when="@7:", type=("build", "run"))
depends_on("py-setuptools", type=("build", "run"))
depends_on("py-numpy@1.9:", type=("build", "run"))
depends_on("py-six@1.9.0:", type=("build", "run"))
depends_on("py-typing-extensions", type=("build", "run"))
depends_on("py-typing-extensions@:3.6.6", when="@:6", type=("build", "run"))
depends_on("py-filelock", type=("build", "run"))
depends_on("py-protobuf@3:", type=("build", "run"))
depends_on("py-typing@:3.6.6", when="@:6", type=("build", "run"))
# Dependencies only required for test of ChainerMN
depends_on("py-matplotlib", type=("build", "run"), when="+mn")
depends_on("py-mpi4py", type=("build", "run"), when="+mn")
depends_on("mpi", type=("build", "run"), when="+mn")
@run_after("install")
def cache_test_sources(self):
if "+mn" in self.spec:
self.cache_extra_test_sources("examples")
def test(self):
if "+mn" in self.spec:
# Run test of ChainerMN
test_dir = self.test_suite.current_test_data_dir
mnist_dir = join_path(self.install_test_root, "examples", "chainermn", "mnist")
mnist_file = join_path(mnist_dir, "train_mnist.py")
mpi_name = self.spec["mpi"].prefix.bin.mpirun
python_exe = self.spec["python"].command.path
opts = [
"-n",
"4",
python_exe,
mnist_file,
"-o",
test_dir,
]
env["OMP_NUM_THREADS"] = "4"
self.run_test(
mpi_name,
options=opts,
work_dir=test_dir,
)
# check results
json_open = open(join_path(test_dir, "log"), "r")
json_load = json.load(json_open)
v = dict([(d.get("epoch"), d.get("main/accuracy")) for d in json_load])
if 1 not in v or 20 not in v:
raise RuntimeError("Cannot find epoch 1 or epoch 20")
if abs(1.0 - v[1]) < abs(1.0 - v[20]):
raise RuntimeError("ChainerMN Test Failed !")
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