NVIDIA/DALI v1.24.0 on GitHub

Key Features and Enhancements

This DALI release includes the following key features and enhancements:

Introduced an automatic augmentation module with AutoAugment, RandAugment, and TrivialAugment (#4694, #4699, #4696, #4702, #4704, #4706, #4710).
Added CUDA 12.1 support (#4684).
Added support for the and, or, and not boolean operators in pipelines (#4629, #4676).

Fixed Issues

Reduced memory consumption by video decoder (#4682).

Improvements

Update TF dataset API usage to align with 2.13rc (#4707)
Rename as_param to mag_to_param (#4710)
Add RandAugment and TrivialAugment to auto_aug module (#4704)
Add AutoAugment and ImageNet policy (#4702)
Fix The Canonical Link Relation in the sphinx documentation (#4703)
Rework DALI examples to use native PyTorch amp (#4683)
[AA] Add select operator util (#4696)
Add augmentations used by AA (#4699)
[AA] Add auto augmentation wrapper (#4694)
Add simple sanity test for DALI Conditionals in tf.function (#4689)
Add support for CUDA 12.1 (#4684)
Add CPU-only and variable batch tests for conditionals (#4668)
Make daliPipelineHandle a pointer to an opaque C++ structure. (#4599)
Enable JPEG fancy upsampling for mixed image decoder (#4662)
Release buffered libaviutil packets (#4682)
Overcome problem with testing TensorFlow with sanitizers (#4671)
New CropMirrorNormalize out of experimental module (#4644)
Do not install PaddlePaddle from the wheel in the L3 test (#4665)
Enable Python 3.10 tests in CI (#4598)
Use nvjpeg2k ROI API directly (#4654)
Add a long DALI description in DALI wheel (#4658)
Update the DALI roadmap link in the README to use the 2023 version (#4659)
Add lazy and and or, and not lazy not support (#4629)
Reduce the size of the generated doxygen docs (#4657)
Naive histogram custom operator example/template (#4615)

Bug Fixes

Do not use numpy.typing when not available (#4706)
Fix SkipTest usage for fancy upsampling tests (#4698)
Add missing constexpr to set_size in the tensorlayout (#4692)
Augment exception handling with ImportError (#4681)
Fix the logical expression tests to avoid short-cutting them (#4676)
Fix API type check tests for frameworks (#4670)

Breaking API changes

There are no breaking changes in this DALI release.

Deprecated features

No features were deprecated in this release.

Known issues:

The experimental.decoder.image may hang during a pipeline build or a teardown.
The issue has been fixed in nightly builds and will be fixed in release 1.25.
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==1.24.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.24.0

or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.24.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.24.0

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 v1.24.0 DALI v1.24.0 on GitHub