This release is a pre-release and may not be stable for production use.
Features
Dynamic and incremental graph construction
On-demand memory allocation
Automatic minibatch broadcasting
Mostly device-independent
Simple usage
Install
Prerequisites:
Python 3 (3.5 or later)
NumPy (1.11.0 or later)
Cython (0.27 or later)
CMake (3.1.0 or later)
scikit-build (0.6.1 or later)
(optional) CUDA (7.5 or later)
(optional) OpenCL (1.2 or later) and OpenCL C++ binding v2
Install required packages:
pip3 install numpy cython cmake scikit-build
Build and install primitiv without CUDA and OpenCL:
pip3 install primitiv
Build and install primitiv with CUDA and/or OpenCL support:
# Enable only CUDA pip3 install primitiv --global-option --enable-cuda # Enable both CUDA and OpenCL pip3 install primitiv --global-option --enable-cuda --global-option --enable-opencl
Notes
We are providing only a source pacakge for now, and pip command downloads the source package and builds it before installing. This is mainly because of keeping compatibility with the manylinux1 standard described in PEP 513 while maintaining supports of non-standard backends such as CUDA/OpenCL.
Resources
1 maintainer
Metadata
1 maintainer
Release files for primitiv 0.4.0.dev159
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| primitiv-0.4.0.dev159.tar.gz | 185.4 kB | Details |
Release files / primitiv-0.4.0.dev159.tar.gz
| Download URL | primitiv-0.4.0.dev159.tar.gz |
|---|---|
| Size | 185.4 kB |
| Tags | Source |
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