NVIDIA/DALI v1.27.0 on GitHub

Key Features and Enhancements

This DALI release includes the following key features and enhancements:

Added O_DIRECT support mode support to fn.readers.tfrecord (#4820).
Added JAX integration (#4867, #4883, #4853).
Added the GPU backend for fn.experimental.readers.fits images that are stored in the FITS format (#4752).

Fixed Issues

Assured deterministic outputs for multiple instances of auto_augment pipelines that are built with the same seeds (#4885).
Fixed the blocking option in the external source operator (#4874).
Fixed the returning empty pixel mask for COCO samples with no objects (#4856).
Fixed the handling of unsupported images by image decoders in fn.experimental.decoders (#4846).

Improvements

Update deps 23/06 (#4902)
Add O_DIRECT support to the TFRecord reader (#4820)
Relax the gast version requirement (#4896)
Add DALI iterator for JAX (#4867)
Fix coverity issues (#4897)
Add deprecation warning for Python3.6 (#4895)
Use memory pool for large host allocs (#4886)
Improve the feed_input documentation regarding prefetching (#4875)
Support nesting data structures in conditionals (#4880)
Add JAX multi GPU tests (#4883)
Move the mention of the EfficientNet example to a box (#4882)
Update the Protobuf version to 23.01 and adjust the build system to it (#4861)
Add basic JAX integration (#4853)
Limit the version of typing_extensions for the TensorFlow test (#4863)
Add GPU implementation for Fits reader (#4752)
Disable Numba CPU tests on AARCH64. (#4862)
Update readme text and code highlighting (#4858)
Disable NUMBA CPU test for runs with memory sanitizer (#4854)
Adjust numpy reader tests for nose2 (#4851)
Update support for Numba 0.57 (#4845)
Move to CUTLASS 3.1 (#4841)
Add a test that triggers a failure in Python (#4836)
Improve VA reservation robustness (#4826)
fix: bad relative path (#4822)

Bug Fixes

Skip DLPack CPU export test for incompatible Numpy (#4904)
Fix parsing numpy header (#4903)
Remove outdated info from iterators docs. (#4899)
Bugfix (async_pool): Store original alignment in 'padded_'. (#4898)
Fix the augmentation coalescing in AA (#4887)
Skip tests for incompatible env (#4894)
Make nesting conditionals supported only for Python 3.7+ (#4888)
Fix DALI FW iterator reset for DROP last batch policy (#4881)
Assure same operator initialization order in the AA graph (#4885)
Fix the lack of support for the blocking option in the external source operator (#4874)
Disable container overflow errors (#4878)
Fix the wrong assignment of the default values in build_helper.sh (#4871)
Disable JAX support for unsupported Python versions (#4870)
Disable FITS test when not building with CFITSIO support. Fix build without libTIFF. (#4866)
Fix layout propagation in jpeg compression distortion (#4864)
Fix returning empty pixel mask for COCO samples with no objects (#4856)
Bugfix in imgcodec: filter should happen after set decode result (#4846)
Don't run image decoder tests in test discovery stage. (#4833)

Breaking API changes

There are no breaking changes in this DALI release.

Deprecated features

DALI 1.27 is the final release that will support Python 3.6.

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==1.27.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.27.0

or for CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.27.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.27.0

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 v1.27.0 DALI v1.27.0 on GitHub