DeepCL v5.8.0

python wrapper for DeepCL deep convolutional neural network library for OpenCL

DeepCL Python wrappers

Python wrapper for DeepCL

To install from pip

pip install DeepCL

• related pypi page: https://pypi.python.org/pypi/DeepCL

How to use

See test_deepcl.py for an example of:

• creating a network, with several layers

• loading mnist data

• training the network using a higher-level interface (NetLearner)

For examples of using lower-level entrypoints, see test_lowlevel.py:

• creating layers directly

• running epochs and forward/backprop directly

For example of using q-learning, see test_qlearning.py.

To build from source

Pre-requisites:

• on Windows:

• Python 2.7 or Python 3.4

• A compiler:

  • Python 2.7 build: need Visual Studio 2008 for Python 2.7 from Microsoft

  • Python 3.4 build: need Visual Studio 2010, eg Visual C++ 2010 Express

• on linux:

• Python 2.7 or Python 3.4

• g++, supporting c++0x, eg 4.4 or higher

To build:

cd python
python setup.py build_ext -i

Then, you can run from this directory, by making sure to add it to the path, eg:

PYTHONPATH=. python test_lowlevel.py /my/mnist/data/dir

To install:

cd python
python setup.py install

Notes on how the wrapper works

• cDeepCL.pxd contains the definitions of the underlying DeepCL c++ libraries classes

• PyDeepCL.pyx contains Cython wrapper classes around the underlying c++ classes

• setup.py is a setup file for compiling the PyDeepCL.pyx Cython file

to run unit-tests

From the python directory:

nosetests -sv

Development builds

• If you want to modify the sourcecode, you’ll need to re-run cython, so you’ll need cython:

  pip install cython

• If you want to update this readme, you might want to re-generate the README.rst, so you’ll need pypandoc:

  pip install pypandoc

• (note that pypandoc depends on pandoc)