tensorflow-build | Tensorflow C lib for various architectures | Compiler library

by snipsco Shell Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | tensorflow-build Summary

tensorflow-build is a Shell library typically used in Utilities, Compiler, Tensorflow applications. tensorflow-build has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

A set of scripts to (cross-)build the Tensorflow C lib for various architectures / OS

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Quality

Security

License

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Support

tensorflow-build has a low active ecosystem.

It has 177 star(s) with 45 fork(s). There are 39 watchers for this library.

It had no major release in the last 6 months.

There are 7 open issues and 6 have been closed. On average issues are closed in 1 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of tensorflow-build is current.

Quality

tensorflow-build has no bugs reported.

Security

tensorflow-build has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

tensorflow-build is licensed under the MIT License. This license is Permissive.

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

Reuse

tensorflow-build releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

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tensorflow-build Key Features

No Key Features are available at this moment for tensorflow-build.

tensorflow-build Examples and Code Snippets

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Community Discussions

Trending Discussions on tensorflow-build

Failed to load the native TensorFlow runtime. when running g2p-seq2seq --version

Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA

Integrating TensorFlow with OpenCL using bazel

QUESTION

Failed to load the native TensorFlow runtime. when running g2p-seq2seq --version

Asked 2019-Feb-04 at 01:24

mac OS I am trying to use cmu dictionary for speech recognition. Steps I took:

...

ANSWER

Answered 2019-Feb-04 at 01:24

What Oluwafemi Sule says in comment is right.

Source https://stackoverflow.com/questions/54499157

QUESTION

Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA

Asked 2018-Jul-20 at 10:56

I successfully installed Tensorflow with Virtualenv. However, when I run it, I get a warning about the fact that AVX2 FMA is not used:

...

ANSWER

Answered 2018-Jul-20 at 10:45

It is just letting you know that your performance could be improved if compilation was optimised. In order to mute the message or add additional build support, you need to install from source. See here, tensorflow.org/install/install_sources .

Source https://stackoverflow.com/questions/51440490

QUESTION

Integrating TensorFlow with OpenCL using bazel

Asked 2017-Jun-11 at 16:14

Description of the problem / feature request / question:

I am trying to use bazel to build TensorFlow Library. It builds fine.

Additional Feature : I would like to add OpenCL code in one of the files of TensorFlow. Added all the required code AND added the following in one of the build files (tensorflow/core/BUILD), considering 'opencl' as the root directory of opencl.

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ANSWER

Answered 2017-Jun-11 at 16:14

The libOpenCL.so was red in color in terminal, which meant it was archived, replaced the file and issue is resolved

Source https://stackoverflow.com/questions/44476359

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

Vulnerabilities

No vulnerabilities reported

Install tensorflow-build

You'll also need numpy.
Install the package then cargo build should find the lib \o/.
For cross compilation, you need a few more steps, the examples below are for a building for a Raspberry Pi 2/3 from a linux box. First, you need the rust target for the Pi. Then you need a toolchain for the pi, let's use the one provided by RaspberryPi. Configure cargo to use the toochain by adding this snippet to you ~/.cargo/config. We now need the .so file of tensorflow for the target arch, let's build the 1.0.0. The .so is located in target/tensorflow/bazel-bin/tensorflow/libtensorflow.so you may want to move it somewhere else. Let's then generate the .pc file. Now that all is done, we can use cargo to crossbuild the app.

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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