DALI Release 1.5.0

Using DALI 1.5.0

To upgrade to DALI 1.5.0 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:

  • Extended decoders.image to support WebP decoding (#3206).
  • Added an indexing (NumPy-like) API for Tensor slicing (#3200 and #3195).
  • Extended external_source to support the source argument in the TensorFlow DALI Dataset (#3215, #3193, #3177, and #3176).
  • Added the following examples:
    • Tensorflow YOLOv4 (#2883).
    • WebDataset usage with external_source (#3153).

Fixed Issues

This DALI release includes the following fixes:

  • Fixed the include paths that prevented the inclusion of some parts of DALI in other C/C++ projects (#3210).
  • Fixed a crash that occurred only when anchors and no shapes were provided in multi_paste (#3166).
  • Fixed an issue in the spectrogram operator when the nfft argument was bigger than the length of the window.

    The extracted windows is now correctly centered before the FFT calculation (#3180).

  • Fixed a minor memory leak in decoders.image (#3148).

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 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