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
To install from pip
pip install --upgrade 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)
The same example, using numpy arrays: test_deepcl_numpy.py
For examples of using lower-level entrypoints, see test_lowlevel.py:
creating layers directly
running epochs and forward/backprop directly
note that you need numpy installed to run this example
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:
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
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
To install:
cd python
python setup.py install
Changes
25 July 2016:
added RandomSingleton class, to set the seed for weights initialization
added xor.py example
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distributions
Hashes for DeepCL-8.5.4alpha1-py3.4-linux-x86_64.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | b3aea08cacb36d8c68fded6994e325582875108703df6fc97269bd0ebbdf1678 |
|
MD5 | f2f7f759bb88cdb2f4860277cf4c94b3 |
|
BLAKE2b-256 | 35fd103e1b231f54158683754b238010bfde40261328099371b5548515be741a |
Hashes for DeepCL-8.5.4alpha1-py3.4-linux-i686.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4147a060bf848264cfc8c78de237b9866bcfd56887ada3b08f1dd368e53253fc |
|
MD5 | 6f21e65e8dadc1c7f56b006ab3b5a708 |
|
BLAKE2b-256 | 67a09cb48937613608ac3bee54f8763d8c750571003e0daf973d021049a4ee97 |
Hashes for DeepCL-8.5.4alpha1-py2.7-linux-x86_64.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | ffc00262d2f9af7cb65b0cd40bd3c5dd4f92bb705375fdb5687fc18b2b8d9836 |
|
MD5 | 4c0350a0279e1c90e0a85ef4e609a0e9 |
|
BLAKE2b-256 | f317902ad72dba11806d38307466db58424e9494fca50a624742c15a7878f12d |
Hashes for DeepCL-8.5.4alpha1-py2.7-linux-i686.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4f7b00b32322881845731ea52908879555f4dde1b7e3bbccf93f9350d28f1943 |
|
MD5 | 9b1964bb5e7ce868871350c8c8f7851e |
|
BLAKE2b-256 | 1687bc2180c7ba9d64bda7bee989678482b446875a2209ccaac9ed9414c7759e |