arrayfire-python | Python bindings for ArrayFire : A general purpose GPU library | GPU library

by arrayfire Python Version: 3.8.0 License: BSD-3-Clause

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kandi X-RAY | arrayfire-python Summary

arrayfire-python is a Python library typically used in Hardware, GPU applications. arrayfire-python has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

ArrayFire is a high performance library for parallel computing with an easy-to-use API. It enables users to write scientific computing code that is portable across CUDA, OpenCL and CPU devices. This project provides Python bindings for the ArrayFire library.

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arrayfire-python has a low active ecosystem.

It has 384 star(s) with 61 fork(s). There are 25 watchers for this library.

It had no major release in the last 12 months.

There are 49 open issues and 118 have been closed. On average issues are closed in 73 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of arrayfire-python is 3.8.0

Quality

arrayfire-python has 0 bugs and 0 code smells.

Security

arrayfire-python has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

arrayfire-python code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

arrayfire-python is licensed under the BSD-3-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

arrayfire-python releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

arrayfire-python saves you 2275 person hours of effort in developing the same functionality from scratch.

It has 5848 lines of code, 583 functions and 72 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed arrayfire-python and discovered the below as its top functions. This is intended to give you an instant insight into arrayfire-python implemented functionality, and help decide if they suit your requirements.

Calculate the GMM matrix
Return the data type of this array
Raise an error
Calculate the approximate approximator
Scale the position of the first axis
Scale the position of the axis
The harris demo example
Get the number of dimensions of this array
Get the dimensions of the array
Compute template matching template
Compute the dot product of two arrays
Create an image
Reorder an array
Wrap an array
Calculate the approximator between a signal
Join two arrays together
Decorate a function to broadcast
Select elements from lhs and rhs
Convolve a 2D convolution layer
Unwrap an image
Tile the array at d0
Draw a vector field
Calculate the nearest position of a signal
Calculate approximate approximate approximator
Shift the array
Logs training data

Get all kandi verified functions for this library.

arrayfire-python Key Features

No Key Features are available at this moment for arrayfire-python.

arrayfire-python Examples and Code Snippets

No Code Snippets are available at this moment for arrayfire-python.

Community Discussions

Trending Discussions on arrayfire-python

row/column-wise outer product in arrayfire-python

QUESTION

row/column-wise outer product in arrayfire-python

Asked 2017-Aug-11 at 17:05

How to implement row/column-wise outer product in arrayfire-python?

Here is analogical implementation in numpy.

...

ANSWER

Answered 2017-Aug-11 at 17:05

This isn't available in arrayfire as a native function. You can however implement something using broadcast and moddims like this:

Source https://stackoverflow.com/questions/45635161

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install arrayfire-python

ArrayFire can be installed from a variety of sources. Pre-built wheels are available for a number of systems and toolkits. These will include a distribution of the ArrayFire libraries. Currently, only the python wrapper is available on PyPI. Wrapper-only installations will require a separate installation of the ArrayFire C/C++ libraries. You can get the ArrayFire C/C++ library from the following sources:. Rather than installing and building ArrayFire elsewhere in the system, you can also build directly through python by first setting the AF_BUILD_LOCAL_LIBS=1 environment variable. Additional setup will be required to build ArrayFire, including satisfying dependencies and further CMake configuration. Details on how to pass additional arguments to the build systems can be found in the scikit-build documentation. If you are not using one of the pre-built wheels, you may need to ensure arrayfire-python can find the installed arrayfire libraries. Please follow these instructions to ensure that arrayfire-python can find the arrayfire libraries. To run arrayfire tests, you can run the following command from command line.
Download and install binaries
Build and install from source