Skip to main content

NVIDIA DALI nightly TensorFlow plugin for CUDA 12.0. Git SHA: 0824e7e0a4abd2828c92c9f4e9dfa0ae74509a95

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_cuda120-1.41.0.dev20240801.tar.gz.

File metadata

File hashes

Hashes for nvidia_dali_tf_plugin_nightly_cuda120-1.41.0.dev20240801.tar.gz
Algorithm Hash digest
SHA256 2d8924b4c0ed67aad46f4a739a6ae891a8b89e4d4bbf6f016023c5daa6eecaa1
MD5 66590f43b94aca59f41bfe9b36c8ff75
BLAKE2b-256 009c5204cc7077a10dacf887f71a4995d09e47948c13e3f71e6403563bfddf48

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