Skip to main content

NVIDIA DALI nightly TensorFlow plugin for CUDA 12.0. Git SHA: 2d67119abe08ba2e8571d1bbdbb74532e906635c

Project description

The TensorFlow plugin enables usage of DALI with TensorFlow.

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.

DALI Diagram

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

File details

Details for the file nvidia_dali_tf_plugin_nightly_cuda120-1.42.0.dev20240816.tar.gz.

File metadata

File hashes

Hashes for nvidia_dali_tf_plugin_nightly_cuda120-1.42.0.dev20240816.tar.gz
Algorithm Hash digest
SHA256 b53382e1692c4bef69bb202613112aeb895bbdd3a9d53c3a7c7ae1300dfa1ca1
MD5 9e1f3eb6c833d9e84039beccd67943d5
BLAKE2b-256 096a32c0228742bf2a5ad21790d2fcd8474df40bba2ae6e497921124b9accd93

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page