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
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 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
numpy installed
To install:
cd python
python setup.py install
Changes
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CHANGE: all image and label tensors must be provided as numpy tensors now, array.array no longer valid input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
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-10.0.1-py3.4-win-amd64.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | 62faba4f339e935635b95a57f4731efa432af9006314e5bc9c3ae372c4e2ed55 |
|
MD5 | 81356eaa6aef9a99e2ff63b735780d42 |
|
BLAKE2b-256 | 008fa5867e058c0c76c3972aef77e34a4b73542536c45af299d46edc8fc5f481 |
Hashes for DeepCL-10.0.1-py3.4-linux-x86_64.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | 983e7b9e74421730609e3fa0d7928f69721b80aedf5890adfa36c143792f28e1 |
|
MD5 | 2d938966fee95363e9bc9220f3f3f395 |
|
BLAKE2b-256 | 1bac87f13d26375b50063397749c08b59d3024c409d7d1a51bd576bbf72d30e6 |
Hashes for DeepCL-10.0.1-py3.4-linux-i686.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | 08cb968ab08101a4c57e05e19c973f8b21758004d742abd98b21eff78318a0ba |
|
MD5 | ca3b3962ab5a6be05ab49588d5abad5c |
|
BLAKE2b-256 | 06edfbab51fdcdf6ab6f8d0829b96d653093f9618eba65ed3900524ef1999010 |
Hashes for DeepCL-10.0.1-py2.7-win-amd64.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4a2d4e464409699f8b53dd40bdc5c3846b552c1d35a1f290ce74d909c6a62202 |
|
MD5 | b6f3fc9eb4307e8f5ab191c229678b1a |
|
BLAKE2b-256 | 0a0d34f425807327f8159cb2f02f1504bc09e382fb8f690d2064b46074fdafa7 |
Hashes for DeepCL-10.0.1-py2.7-linux-x86_64.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3c96f4c9aeb0ba9e1809c5cf210648080517ba7ca1e5465f130f4ee5b691b1c7 |
|
MD5 | 1c4a2959734c596e020e52718cd9569d |
|
BLAKE2b-256 | eeeb782b649009b75d9a739856e343b2c449d662d6005c7a23d2563bf8e6c7aa |
Hashes for DeepCL-10.0.1-py2.7-linux-i686.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3d55527ff3ec70588b0aeeb3350b032fafbf15bae6b5518a3d0ef76ebc2dbaca |
|
MD5 | 285f45a0304739fd88e08de4bafc09bc |
|
BLAKE2b-256 | 267ec4d2928d98db8426b3ba06759dbde87dd9537fbfdb63d669b5da55cb25fe |