gtensor | GTensor is a multi-dimensional array C++14 | GPU library

by wdmapp C++ Version: pop2020 License: BSD-3-Clause

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kandi X-RAY | gtensor Summary

gtensor is a C++ library typically used in Hardware, GPU applications. gtensor has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

gtensor is a multi-dimensional array C++14 header-only library for hybrid GPU development. It was inspired by xtensor, and designed to support the GPU port of the GENE fusion code.

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gtensor has a low active ecosystem.

It has 30 star(s) with 8 fork(s). There are 3 watchers for this library.

It had no major release in the last 12 months.

There are 40 open issues and 33 have been closed. On average issues are closed in 100 days. There are 4 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of gtensor is pop2020

Quality

gtensor has no bugs reported.

Security

gtensor has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

gtensor 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

gtensor releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

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gtensor Key Features

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gtensor Examples and Code Snippets

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Community Discussions

Trending Discussions on gtensor

Unsure whether function breaks backpropagation

QUESTION

Unsure whether function breaks backpropagation

Asked 2018-May-14 at 09:44

I have been tinkering around a lot with tensorflow in the past few days however I am quite unsure whether a function I wrote would break the backpropagation in a Neural network. I thought I'd ask here before I try to integrate this function in a NN. So the basic setup is I want to add two matricies with

...

ANSWER

Answered 2018-May-13 at 21:17

TensorFlow will backpropagate to everything by default. As per your code, everything will receive gradients with a training operation from an optimizer. So to answer your question, backpropagation will work.

The only thing to consider, is that you say tfObjectMatrix is a list of images that will not change. So you might not want it to receive any gradients. Therefore you might want to look into tf.stop_gradient() and maybe use it like OM = tf.stop_gradient( tfObjectMatrix ) and work with that OM in your function.

Source https://stackoverflow.com/questions/50318493

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

Vulnerabilities

No vulnerabilities reported

Install gtensor

gtensor uses cmake 3.13+ to build the tests and install:. To build for cpu/host only, use -DGTENSOR_DEVICE=host, for AMD/HIP use -DGTENSOR_DEVICE=hip -DCMAKE_CXX_COMPILER=$(which hipcc), and for Intel/SYCL use -DGTENSOR_DEVICE=sycl -DCMAKE_CXX_COMPILER=$(which dpcpp) See sections below for more device specific requirements. Note that gtensor can still be used by applications not using cmake - see Usage (GNU make) for an example. To use the internal data vector implementation instead of thrust, set -DGTENSOR_USE_THRUST=OFF. This has the advantage that device array allocations will not be zero initialized, which can improve performance significantly for some workloads, particularly when temporary arrays are used. To enable experimental C/C++ library features,GTENSOR_BUILD_CLIB, GTENSOR_BUILD_BLAS, or GTENSOR_BUILD_FFT to ON. Note that BLAS includes some LAPACK routines for LU factorization.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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