pynvml | Provide Python access to the NVML library | GPU library

by gpuopenanalytics Python Version: Current License: BSD-3-Clause

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | pynvml Summary

pynvml is a Python library typically used in Hardware, GPU, Numpy, Pandas applications. pynvml 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.

Provides a Python interface to GPU management and monitoring functions. This is a wrapper around the NVML library. For information about the NVML library, see the NVML developer page As of version 11.0.0, the NVML-wrappers used in pynvml are identical to those published through [nvidia-ml-py] Note that this file can be run with python -m doctest -v README.txt although the results are system dependent.

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pynvml has a low active ecosystem.

It has 81 star(s) with 18 fork(s). There are 9 watchers for this library.

It had no major release in the last 6 months.

There are 7 open issues and 18 have been closed. On average issues are closed in 115 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pynvml is current.

Quality

pynvml has 0 bugs and 0 code smells.

Security

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

pynvml code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pynvml 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

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

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

Installation instructions are not available. Examples and code snippets are available.

pynvml saves you 2489 person hours of effort in developing the same functionality from scratch.

It has 7118 lines of code, 389 functions and 8 files.

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

Top functions reviewed by kandi - BETA

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

XMLDevice query
Return a dict containing the command - line tool .
Return a generator of git pieces from a git repository .
Create the versioneer config file .
Extract git versions from keywords .
Return git versions .
Return the project root directory .
Install versioneer .
Scans the setup . py file and checks if it is missing .
Run git commands .

Get all kandi verified functions for this library.

pynvml Key Features

No Key Features are available at this moment for pynvml.

pynvml Examples and Code Snippets

No Code Snippets are available at this moment for pynvml.

Community Discussions

Trending Discussions on pynvml

How to install cuDF on google colab with GPU Tesla K80?

Feature extraction in loop seems to cause memory leak in pytorch

QUESTION

How to install cuDF on google colab with GPU Tesla K80?

Asked 2022-Mar-10 at 22:05

I am trying to install cuDF on Google Colab for hours. One of the requirements I should install cuDF with GPU Tesla T4. While google colab gives me every time GPU Tesla K80 and I cannot install cuDF. I tried this snippet of code to check what type of GPU I have every time:

...

ANSWER

Answered 2022-Mar-10 at 22:05

The K80 use Kepler GPU architecture, which is not supported by RAPIDS. Colab itself no longer can run the latest versions of RAPIDS. You can try SageMaker Studio Lab for your Try it Now experience. https://github.com/rapidsai-community/rapids-smsl.

Source https://stackoverflow.com/questions/71294926

QUESTION

Feature extraction in loop seems to cause memory leak in pytorch

Asked 2020-Aug-27 at 12:31

I have spent considerable time trying to debug some pytorch code which I have created a minimal example of for the purpose of helping to better understand what the issue might be.

I have removed all necessary portions of the code which are unrelated to the issue so the remaining piece of code won't make much sense from a functional standpoint but it still displays the error I'm facing.

The overall task I'm working on is in a loop and every pass of the loop is computing the embedding of the image and adding it to a variable storing it. It's effectively aggregating it (not concatenating, so the size remains the same). I don't expect the number of iterations to force the datatype to overflow, I don't see this happening here nor in my code.

I have added multiple metrics to evaluate the size of the tensors I'm working with to make sure they're not growing in memory footprint
I'm checking the overall GPU memory usage to verify the issue leading to the final RuntimeError: CUDA out of memory..

My environment is as follows:

...

ANSWER

Answered 2020-Aug-27 at 12:31

Add this to your code as soon as you load the model

Source https://stackoverflow.com/questions/63588069

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

Vulnerabilities

No vulnerabilities reported

Install pynvml

You can download it from GitHub.
You can use pynvml like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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