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nvidia-dali-nightly-cuda110

v1.45.0.dev20241122

NVIDIA DALI nightly for CUDA 11.0. Git SHA: ddd2bfd0274b3e7809598299bc4da857400f1a2a For more information about how to use this package see README

Latest version published 6 days ago

License: Apache-2.0

PyPI

Package Health Score

61 / 100

security
No known security issues
popularity
Small
maintenance
Sustainable
community
Limited

Popularity

Small

GitHub Stars: ?
Forks: ?
Contributors: -

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package nvidia-dali-nightly-cuda110, we found that it has been starred ? times.

Security

No known security issues

Security and license risk for latest version

Release Date: Nov 22, 2024
Direct Vulnerabilities: 0
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Indirect Vulnerabilities: 0
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License Risk: 0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

Apache-2.0

Security Policy

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Maintenance

Sustainable

Commit Frequency

Unavailable commit data

Open Issues: ?
Open PR: ?
Last Release: 6 days ago
Last Commit: unknown

Further analysis of the maintenance status of nvidia-dali-nightly-cuda110 based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Sustainable.

We found that nvidia-dali-nightly-cuda110 demonstrates a positive version release cadence with at least one new version released in the past 3 months.

In the past month we didn't find any pull request activity or change in issues status has been detected for the GitHub repository.

Community

Limited

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 0
Funding: No

This project has seen only 10 or less contributors.

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Package

Python Versions Compatibility: <3.14,>=3.8

Age: 2 years
Latest Release: 6 days ago
Dependencies: 0 Direct
Versions: 183
Maintainers: 1
Wheels: No

Readme

NVIDIA DALI

The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provides a collection of highly optimized building blocks for loading and processing image, video and audio data. It can be used as a portable drop-in replacement for built in data loaders and data iterators in popular deep learning frameworks.

Deep learning applications require complex, multi-stage data processing pipelines that include loading, decoding, cropping, resizing, and many other augmentations. These data processing pipelines, which are currently executed on the CPU, have become a bottleneck, limiting the performance and scalability of training and inference.

DALI addresses the problem of the CPU bottleneck by offloading data preprocessing to the GPU. Additionally, DALI relies on its own execution engine, built to maximize the throughput of the input pipeline. Features such as prefetching, parallel execution, and batch processing are handled transparently for the user.

In addition, the deep learning frameworks have multiple data pre-processing implementations, resulting in challenges such as portability of training and inference workflows, and code maintainability. Data processing pipelines implemented using DALI are portable because they can easily be retargeted to TensorFlow, PyTorch, MXNet and PaddlePaddle.

For more details please check the latest DALI Documentation.

FAQs

What is nvidia-dali-nightly-cuda110?

NVIDIA DALI nightly for CUDA 11.0. Git SHA: ddd2bfd0274b3e7809598299bc4da857400f1a2a. Visit Snyk Advisor to see a full health score report for nvidia-dali-nightly-cuda110, including popularity, security, maintenance & community analysis.

Is nvidia-dali-nightly-cuda110 popular?

The python package nvidia-dali-nightly-cuda110 receives a total of 1,196 weekly downloads. As such, nvidia-dali-nightly-cuda110 popularity was classified as small. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is nvidia-dali-nightly-cuda110 safe to use?

The python package nvidia-dali-nightly-cuda110 was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 25 November-2024, at 18:22 (UTC).

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