DALI Release 1.7.0

Using DALI 1.7.0

To upgrade to DALI 1.7.0 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:

  • New operators:
    • Readers.webdataset, which is a reader for the Webdataset format (#3395, #3385, #3375, #3372, #3360, and #3306).
    • experimental.readers.video (CPU), which is an experimental video reader and decoder that includes support for the variable frame rate (#3412, #3411, #3391, and #3362).
  • Performance improvements:
    • warp_affine performance has been improved for some common cases (#3370).
    • Other minor general performance improvements (#3363 and #3338).
  • Added the DALI_DISABLE_NVML and DALI_RESTRICT_PINNED_MEM environment variables (#3404 and #3382).

    These variables allow you to limit the use of NVML and pinned memory and enable DALI on more platforms .

Fixed Issues

This DALI release includes the following fixes:

  • Fixed an issue in the pad operator that caused a crash when the operator was used with a variable batch size (#3354).
  • Fixed a race condition that occurred in the readers.video operator (#3355).
  • Fixed a bug in the C API that caused invalid memory access in some use cases (#3350).

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