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python wrapper for DeepCL deep convolutional neural network library for OpenCL

Project description

DeepCL Python wrappers

Python wrapper for DeepCL

To install from pip

pip install DeepCL

How to use

See 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

  • creating layers directly
  • running epochs and forward/backprop directly

For example of using q-learning, see

To build from source


To build:

cd python
python build_ext -i

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

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

To install:

cd python
python 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
  • 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)

Project details

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Files for DeepCL, version 5.10.1
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