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DALI v1.49.0
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@stiepan stiepan released this 29 Apr 14:58
· 46 commits to main since this release
v1.49.0
ccb1902

Key Features and Enhancements

This DALI release includes the following key features and enhancements:

  • Improved new (experimental) C API (#5879, #5872, #5866, #5857, #5835, #5868)
  • Added support for CUDA 12.8U1 (#5850)
  • Added CPU support to dali.fn.experimental.debayer (#5832)
    Thank you @5had3z for your contribution!
  • Added support for nvImageCodec 0.5.0 (#5854)

Fixed Issues

  • Fixed race-condition in experimental image decoder (#5856)

Improvements

  • Update VERSION to 1.49.0
  • C API 2.0 Checkpointing + unblock dali.h (#5879)
  • Temporarily disable failing test (#5882)
  • Experimental Video Reader Refactoring and API Improvements (#5839)
  • Move to LLVM 20.1.2 (#5870)
  • C API 2.0: External source info (#5872)
  • Add _zmq.cpython to the address sanitizer suppression list (#5873)
  • Set minimum CMake policy version for Horovod build (#5871)
  • Pipeline refactoring (#5866)
  • Add multi-configuration performance benchmarking (#5858)
  • Sort out Python 3.8 support (#5867)
  • Moves to manylinux_2_28 (#5608)
  • Adjust test compatibility with numpy 2.x (#5862)
  • Bump up the minimum version of CMake required by ffts (#5864)
  • Remove unnecessary global declarations and add noqa comments (#5865)
  • Add fallback for missing source info in check_batch (#5861)
  • Bump nvimagecodec requirement to 0.5.0 (#5854)
  • Skip C API2 test using Mixed ImageDecoder when it's not registered. (#5857)
  • C API 2.0 Pipeline & Pipeline Outputs (#5835)
  • Update six package version constraint (#5855)
  • Add info about GIT sha to the documentation (#5853)
  • Bump up the Black version to 25.x (#5849)
  • Bump OpenCV version in conda to 4.11 (#5851)
  • Improve sanitizer configuration and suppress false positives (#5795)
  • Add Debayer CPU based on OpenCV (#5832)
  • FramesDecoder boundary handling, video utils (#5844)
  • Move to CUDA 12.8 U1 (#5850)
  • Added warp perpective tests to other test suites. (#5847)
  • Add operator statefulness info to OpSchema (#5848)
  • Bump up support TF version to 2.18 (#5840)

Bug Fixes

  • Fixed race-condition in experimental image decoder (#5856)

Breaking API changes

There are no breaking changes in this DALI release.

Deprecated features

DALI 1.49 is the last release to support Python 3.8

Known issues:

  • The following operators: experimental.readers.fits, experimental.decoders.video, and experimental.inputs.video do not currently support checkpointing.
  • 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==1.49.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda120==1.49.0

or just:

pip install nvidia-dali-cuda120==1.49.0
pip install nvidia-dali-tf-plugin-cuda120==1.49.0

For CUDA 11:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-cuda110==1.49.0
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/ nvidia-dali-tf-plugin-cuda110==1.49.0

or just:

pip install nvidia-dali-cuda110==1.49.0
pip install nvidia-dali-tf-plugin-cuda110==1.49.0

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:

Contributors

5had3z
Assets 2
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