DALI Release 0.30.0

The DALI 0.30.0 is not yet a major release, so the features, functionality, and performance might be limited.

Using DALI 0.30.0

To upgrade to DALI 0.30.0 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.

  • Optimized CPU resampling (#2540).

  • Added the following mathematical expressions:

    • Disallowed unwanted __bool__ conversions (#2538).

    • Added the exp and log math functions (#2555).

  • Added the images argument for the COCOReader, which allows for the custom ordering of images and fixed a bug in the segmentation data parsing (#2548, #2597).

  • Added support for the nvJPEG preallocate API for a batched hardware decoder (#2544).

  • Added support surfaces with strides over 2G (#2600).

  • Enabled CUDA 11.2 builds (#2553).

  • Documentation improvements:

    • Added a supported matrix to the documentation (#2519).

    • Added a geometric transform tutorial (#2530).

  • Allowed DALI to be compiled with Clang (#2416).

  • Added CUDA API checks in utility functions (#2517) and tests (#2516).

Fixed Issues

This DALI release includes the following fixes.

  • Fixed the autoreset option in the iterator for the DROP policy (#2567).

Breaking Changes

  • There are no breaking changes in this release.

Deprecated Features

There are no deprecated features in this release.

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 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 that is 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.)

  • 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