DALI Release 1.15.0

Using DALI 1.15.0

To upgrade to DALI 1.15.0 from an older version of DALI, follow the installation and usage information in the DALI User Guide.

Note: The internal DALI C++ API used for operator’s implementation, and the C++ API that enables using DALI as a library from native code, is not yet officially supported. Hence these APIs may change in the next release without advance notice.

Key Features and Enhancements

This DALI release includes the following key features and enhancements:
  • Added the GPU audio resampling operator (#3884, #3914, and #3911).
  • Improved the performance of the GPU fn.readers.numpy by custom GDS staging (#3894, #3905).
  • Added support for video processing and per-frame (temporal) arguments to the warp_affine operator (#3879, #3900).
  • Added HEVC support to the GPU frames decoder (#3896).
  • Added experimental support for the eager execution of stateless operators as Python functions and readers as iterators (#3887, #3930).
  • Added CUDA 11.7 support (#3906).
  • Profiling improvements:
    • Added more NVTX ranges to the executor (#3928).
    • Added thread names to all DALI threads (#3912).

Fixed Issues

Here are the fixed issues in this release:
  • Added the missing device/device synchronization when copying pipeline outputs with copy_to_external (#3953).
  • Fixed the buffer synchronization between the default and custom stream in a multi-GPU case (#3957).

Breaking Changes

There are no breaking changes in this DALI release.

Deprecated Features

There are no deprecated features in this DALI release.

Known Issues

This DALI release includes the following 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.

  • The 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 plug-in might not be compatible with TensorFlow versions 1.15.0 and later.

    To use DALI with the TensorFlow version that does not have the prebuilt plug-in binary that is shipped with DALI, ensure that the compiler that is used to build TensorFlow exists on the system during the plug-in installation. (Depending on the particular version, you can use GCC 4.8.4, GCC 4.8.5, or GCC 5.4.)

  • Due to some known issues with meltdown/spectra mitigations and DALI, DALI shows the 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