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CHANGE: all image and label tensors must be provided as numpy tensors now, array.array no longer valid input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-9.0.1-py3.4-win-amd64.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | 7e2a50adbaf742d95acfb58a1c26c358818323172178f3f84399d4875ac05936 |
|
MD5 | 2724be624444d28244c7c3a751f781c8 |
|
BLAKE2b-256 | 48da6c0c5ea363ce743e4aaf00a0021a555c7f7497f01f2327eb15cbba7048df |
Hashes for DeepCL-9.0.1-py3.4-linux-x86_64.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | 73cb0cbdf2ac2aeb608023a1325085453a6407ef896f86dc8b0ec34bfd919c62 |
|
MD5 | c39c19fc1ed624093efa43851c8990a8 |
|
BLAKE2b-256 | a0b2b385f618da2b396d014aa1dd4cdfe20dd3bb31e9880939a2bff48161da04 |
Hashes for DeepCL-9.0.1-py3.4-linux-i686.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4fe9d5637310426fa20f142c94673f77efd38c67dceee8447894ce6a40bb56ae |
|
MD5 | 1305b5ad484014639c42e3d2893b0ee6 |
|
BLAKE2b-256 | cdf725eb1f556d20f9206be907d60ab8bbe65fc1813b117fac35cd53d62c0941 |
Hashes for DeepCL-9.0.1-py2.7-win-amd64.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3c9d943743dad344e1567f7b069f436a19b9a5f4e74ba6a2be8f76c396ddb87b |
|
MD5 | ca970317d8a591cb75cb3df4aa0b4759 |
|
BLAKE2b-256 | a32fe3aec01b9d962b0968686d8d7549359197203d60a77eac75273f298e7e42 |
Hashes for DeepCL-9.0.1-py2.7-linux-x86_64.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | 6de4fa396d1d2e830ad0721f90738a17cb3e726b4c6aac7073766ca204bd39f7 |
|
MD5 | 53955d6b9aa78a28ff6861c0a26d3454 |
|
BLAKE2b-256 | db13fcf1407f251c88c9a11ad189a47e55808b17adecaf182c2b7d61114c2b5d |
Hashes for DeepCL-9.0.1-py2.7-linux-i686.egg
Algorithm | Hash digest | |
---|---|---|
SHA256 | a1ee950bea57e446cdc97a8b138cc5ced51e6c8b413d458fbff3d8de4b457ec0 |
|
MD5 | 7c812ab0cefad9b847704b5c3a623d4a |
|
BLAKE2b-256 | 1a82e9df7194d8f3f773c217ce7a5d84408d3b5414bbe9c4983199a9eeaff64c |