Skip to main content

NVIDIA DALI nightly TensorFlow plugin for CUDA 12.0. Git SHA: 2117f88bfde3d8cdb3358dd1ceec86f75e345c23

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.dev20240910.tar.gz.

File metadata

File hashes

Hashes for nvidia_dali_tf_plugin_nightly_cuda120-1.42.0.dev20240910.tar.gz
Algorithm Hash digest
SHA256 abaca23e6e15dec495a38e09c337175c9693affb9b019b2b240c3d0aa70ff759
MD5 1e0c551c49739839dd991161f4ee686e
BLAKE2b-256 d2f77b3dc3f69f972e01d3018c2a5dc87978922f9eaab8ad88fd751ec5c66970

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