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Source: tiny-dnn
Section: science
Priority: optional
Maintainer: Debian Deep Learning Team <debian-ai@lists.debian.org>
Uploaders:
Andrius Merkys <merkys@debian.org>,
Build-Depends:
cmake,
debhelper-compat (= 13),
doxygen,
graphviz,
libcereal-dev,
libgemmlowp-dev,
libgmock-dev <!nocheck>,
libgtest-dev <!nocheck>,
libstb-dev,
libtbb-dev,
Standards-Version: 4.6.2
Homepage: https://github.com/tiny-dnn/tiny-dnn
Vcs-Browser: https://salsa.debian.org/deeplearning-team/tiny-dnn
Vcs-Git: https://salsa.debian.org/deeplearning-team/tiny-dnn.git
Rules-Requires-Root: no
Package: tiny-dnn
Architecture: all
Multi-Arch: foreign
Depends:
${misc:Depends},
Suggests:
tiny-dnn-doc,
Description: header only deep learning framework in C++
tiny-dnn is a C++ implementation of deep learning. It is suitable for deep
learning on limited computational resource, embedded systems and IoT devices.
.
Features:
.
* Reasonably fast, without GPU;
* Portable & header-only;
* Easy to integrate with real applications;
* Simply implemented.
Package: tiny-dnn-doc
Architecture: all
Multi-Arch: foreign
Section: doc
Depends:
${misc:Depends},
Description: header only deep learning framework in C++ -- documentation
tiny-dnn is a C++ implementation of deep learning. It is suitable for deep
learning on limited computational resource, embedded systems and IoT devices.
.
Features:
.
* Reasonably fast, without GPU;
* Portable & header-only;
* Easy to integrate with real applications;
* Simply implemented.
.
This package contains the documentation.
|
