NVIDIA/DALI v1.29.0 on GitHub

Key Features and Enhancements

This DALI release includes the following key features and enhancements:

Added GPU fn.experimental.median_blur operator. (#4950, #4975)
Improved JAX support:
- Added support for jax.Sharding to dali.plugin.jax.DALIGenericIterator (#4969).
- Improved examples and tutorials (#4973, #4956, #4944, #4937).
Optimized the HWC to CHW transposition variant of the fn.crop_mirror_normalize operator (#4972).
Moved to CUDA 12.2U1 (#4966)

Fixed Issues

Fixed layout broadcasting in arithmetic expressions (#4951).
Added missing layout propagation in fn.reductions (#4947).

Improvements

Trim CV-CUDA to expose only median blur to reduce the binary size (#4985)
Add optimized variant of CMN for HWC to CHW case (#4972)
Enable CV-CUDA build for xavier (#4976)
Update DALI_deps version (#4971)
Add automatic parallelization JAX example (#4973)
Exclude median_blur test from xavier tests (#4975)
Move to CUDA 12.2 U1 (#4966)
Add basic jax.Sharding support for the iterator (#4969)
Enable cv-cuda in conda build (#4968)
Fix wheel bundling with cvcuda for debug builds (#4959)
Fix Getting Started link in README (#4962)
Add multigpu JAX tutorial (#4956)
Add median blur operator (#4950)
Fix updated linter errors (#4960)
Support checkpointing in FileReader (#4954)
Add CV-CUDA as a subproject (#4949)
Remove the direct use of cuda_for_dali auxiliary namespace. (#4953)
Checkpointing classes (#4946)
Make sure that lossless support is disabled when it fails to initialize (#4934)
Add L3 short test for RN50 training (#4614)
DALI_deps update 13 Jul 2023 (#4945)
Add JAX tutorial tests (#4944)
Update OpenCV 4.7.0 to 4.8.0, patch for CVE-2023-1999 (#4941)
Fix L1 Jupyter Conda Job (#4942)
Update the TensorFlow version used in tests (#4940)
Add basic JAX tutorial (#4937)

Bug Fixes

Checkpoint after running epoch (#4983
Propagate layout in fn.reductions (#4947)
Fix layout broadcasting arithm ops (#4951)
Fix coverity issues - July 2023 (#4948)

Breaking API changes

There are no breaking changes in this DALI release.

Deprecated features

No features were deprecated in this release.

Known issues:

The video loader operator requires that the key frames occur, at a minimum, every 10 to 15 frames of the video stream.
If the key frames occur at a frequency that is less than 10-15 frames, the returned frames might be out of sync.
Experimental VideoReaderDecoder does not support open GOP.
It will not report an error and might produce invalid frames. VideoReader uses a heuristic approach to detect open GOP and should work in most common cases.
The DALI TensorFlow plugin might not be compatible with TensorFlow versions 1.15.0 and later.
To use DALI with the TensorFlow version that does not have a prebuilt plugin binary shipped with DALI, make sure that the compiler that is used to build TensorFlow exists on the system during the plugin installation. (Depending on the particular version, you can use GCC 4.8.4, GCC 4.8.5, or GCC 5.4.)
In experimental debug and eager modes, the GPU external source is not properly synchronized with DALI internal streams.
As a workaround, you can manually synchronize the device before returning the data from the callback.
Due to some known issues with meltdown/spectra mitigations and DALI, DALI shows best performance when running in Docker with escalated privileges, for example:
- privileged=yes in Extra Settings for AWS data points
- --privileged or --security-opt seccomp=unconfined for bare Docker.

Binary builds

NOTE: DALI builds for CUDA 12 dynamically link the CUDA toolkit. To use DALI, install the latest CUDA toolkit.

CUDA 11.0 and CUDA 12.0 builds use CUDA toolkit enhanced compatibility. 
They are built with the latest CUDA 11.x/12.x toolkit respectively but they can run on the latest, 
stable CUDA 11.0/CUDA 12.0 capable drivers (450.80 or later and 525.60 or later respectively).
However, using the most recent driver may enable additional functionality. 
More details can be found in enhanced CUDA compatibility guide.

Install via pip for CUDA 12.0:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda120==1.29.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.29.0

or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.29.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.29.0

Or use direct download links (CUDA 12.0):

Or use direct download links (CUDA 11.0):

FFmpeg source code:

This software uses code of FFmpeg licensed under the LGPLv2.1 and its source can be downloaded here

Libsndfile source code:

https://developer.download.nvidia.com/compute/redist/nvidia-dali/libsndfile-1.2.0.tar.gz

NVIDIA/DALI v1.29.0 DALI v1.29.0 on GitHub