Skip to main content

python wrapper for DeepCL deep convolutional neural network library for OpenCL

Project description

Python wrapper for DeepCL

Pre-requisites

  • You must have first installed and activated DeepCL native libraries, see Build.md

  • numpy

To install from pip

pip install --upgrade 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 install from source

Pre-requisites:

  • on Windows:

  • Python 2.7 or Python 3.4

  • A compiler:

  • on linux:

  • Python 2.7 or Python 3.4

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

  • have first already built the native libraries, see Build.md

  • have activated the native library installation, ie called dist/bin/activate.sh, or dist/bin/activate.bat

  • numpy installed

To install:

cd python
python setup.py install

Changes

  • 30 July 2016:

  • Added net.getNetdef(). Note that this is only an approximate representation of the network

  • 29 July 2016:

  • New feature: can provide image tensor as 4d tensor now ,instead of 1d tensor (1d tensor ok too)

  • CHANGE: all image and label tensors must be provided as numpy tensors now, array.array no longer valid input

  • bug fix: qlearning works again :-)

  • 25 July 2016:

  • added RandomSingleton class, to set the seed for weights initialization

  • added xor.py example

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page