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new file: b/Boost/Boost-1.63.0-foss-2017a-Python-3.6.1.eb
modified: c/CNTK/CNTK-2.0-GCC-7.1.0-2.28-Python-3.6.1.eb new file: c/CNTKCustomMKL/CNTKCustomMKL-3.0.eb modified: k/Keras/Keras-2.0.5-Theano-0.9.0-Python-3.6.1.eb deleted: k/Keras/.Keras-2.0.5-Theano-0.9.0-Python-3.6.1.eb.swp
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b/Boost/Boost-1.63.0-foss-2017a-Python-3.6.1.eb
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b/Boost/Boost-1.63.0-foss-2017a-Python-3.6.1.eb
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name = 'Boost'
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version = '1.63.0'
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versionsuffix = '-Python-%(pyver)s'
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homepage = 'http://www.boost.org/'
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description = """Boost provides free peer-reviewed portable C++ source libraries."""
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toolchain = {'name': 'foss', 'version': '2017a'}
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toolchainopts = {'pic': True, 'usempi': True}
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source_urls = [SOURCEFORGE_SOURCE]
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sources = ['%%(namelower)s_%s.tar.gz' % '_'.join(version.split('.'))]
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patches = [
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'Boost-%(version)s_python3.patch',
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]
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dependencies = [
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('bzip2', '1.0.6'),
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('zlib', '1.2.11'),
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('Python', '3.6.1', '', True),
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]
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# also build boost_mpi
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boost_mpi = True
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moduleclass = 'devel'
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easyblock = 'PythonPackage'
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easyblock = 'ConfigureMake'
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name = 'CNTK'
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version = '2.0'
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@ -7,7 +7,7 @@ versionsuffix = '-Python-%(pyver)s'
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homepage = 'https://cntk.ai/'
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description = """The Microsoft Cognitive Toolkit is a unified deep-learning toolkit that describes neural networks as a series of computational steps via a directed graph. In this directed graph, leaf nodes represent input values or network parameters, while other nodes represent matrix operations upon their inputs. CNTK allows to easily realize and combine popular model types such as feed-forward DNNs, convolutional nets (CNNs), and recurrent networks (RNNs/LSTMs). It implements stochastic gradient descent (SGD, error backpropagation) learning with automatic differentiation and parallelization across multiple GPUs and servers. """
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toolchain = {'name': 'GCC', 'version': '7.1.0-2.28'}
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toolchain = {'name': 'foss', 'version': '2017a'}
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source_urls = ['https://cntk.ai/PythonWheel/CPU-Only']
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sources = ['cntk-%(version)s-cp36-cp36m-linux_x86_64.whl']
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@ -17,6 +17,10 @@ unpack_sources = False
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dependencies = [
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('Python', '3.6.1', '', True),
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('libzip, '1.2.0', '', True),
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('zlib, '1.2.11', '', True),
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('protobuf, '3.2.0', '-Python-3.6.1', True),
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('CNTKCustomMKL','3.0', '', True),
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('OpenMPI', '1.10.7'),
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]
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c/CNTKCustomMKL/CNTKCustomMKL-3.0.eb
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c/CNTKCustomMKL/CNTKCustomMKL-3.0.eb
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easyblock = 'Tarball'
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name = 'CNTKCustomMKL'
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version = '3.0'
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homepage = 'https://www.microsoft.com/en-us/cognitive-toolkit/'
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description = """The default CNTK math library is the Intel Math Kernel Library (Intel MKL). CNTK supports using the Intel MKL via a custom library version (CNTK custom MKL)."""
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toolchain = {'name': 'dummy', 'version': ''}
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source_urls = ['http://www.microsoft.com/en-us/cognitive-toolkit/wp-content/uploads/sites/3/2017/05']
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sources = ['CNTKCustomMKL-Linux-3.tgz']
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sanity_check_paths = {
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'files': [],
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'dirs': ['include', 'x64'],
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}
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moduleclass = 'numlib'
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dependencies = [
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('Python', '3.6.1'),
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('Theano', '0.9.0', ''),
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('Theano', '0.9.0', '-Python-%(pyver)s'),
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# ('h5py', '2.7.0', '%(versionsuffix)s'), internal Python 3.6.1
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# ('PyYAML', '3.12', versionsuffix), internal Python 3.6.1
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]
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# it defaults to Tensorflow
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modextravars = {'KERAS_BACKEND': 'tensorflow'}
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modextravars = {'KERAS_BACKEND': 'theano'}
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sanity_check_paths = {
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'files': [],
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