DALI Release 1.20.0

Using DALI 1.20.0

To upgrade to DALI 1.20.0 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 fn.experimental.remap operator for the generic geometric transformation of images and video (#4379, #4419, #4365, #4374, 4425).
  • Added MPEG4 support to the GPU video decoder (#4424, #4327).
  • Added an inflate operator that enables the decompression of the LZ4 compressed input (#4366).
  • Added support for broadcasting in arithmetic operators (CPU and GPU) (#4348).
  • Added an experimental split and merged operators for conditional execution (#4359, #4405, #4358).
  • The following optimizations in GPU operators:
    • MelScale kernel optimization.
    • Optimizations in the GPU decoder (#4351).
    • Simplified arithmetic operator GPU implementation (#4411).
    • Split reduction kernels (#4383).
    • Avoid copying from non-pinned memory in PreemphasisFilter operator (#4380).
    • Refactored the ConvertTimeMajorSpectrogram kernel.

Fixed Issues

Here are the fixed issues in this release:
  • Fixed TensorList copy synchronization issues (#4458, #4453).
  • Fixed an issue with hint grid size in OpticalFlow (#4443).
  • Fixed the ES synchronization issues in integrated memory devices (#4321, #4423).
  • Added a missing CUDA stream synchronization before cuvidUnmapVideoFrame in nvDecoder (#4426).
  • Fixed the pipeline initialization in Python after deserialization (#4350).
  • Fixed issues with the serialization of functions in recent notebook versions (#4406).
  • Fixed the integration with new TensorFlow version by replacing Status::OK() with Status() in the TensorFlow plugin (#4442).

Breaking Changes

Here are the breaking changes in this release:
  • Removed the Pipeline/Executor completion callback APIs (#4345).
  • [C++ API] Workspace unification: C++ workspace is no longer templated with backend type (#4339).

Deprecated Features

  • DALI will drop support for CUDA 10.2 in an upcoming release.

Known Issues

This DALI release includes the following known issues:

  • The GPU numpy reader might crash during the DALI process teardown with cufile 1.4.0.

  • 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.)

  • 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 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