DALI Release 1.2.0

Using DALI 1.2.0

To upgrade to DALI 1.2.0 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:
    • noise.shot CPU and GPU operators (#2861).
    • noise.gaussian CPU and GPU operators (#2846).
    • jpeg_compression_distortion CPU and GPU operators (#2823).
  • New mathematical operations (#2853):
    • Square and cubic root (sqrt, rsqrt, and cbrt).
    • Logarithms of different bases (log2 and log10)
    • Power (** operator and pow functions).
    • Absolute value (abs and fabs).
    • Roundings (ceil and floor).
    • Trigonometric functions (sin, cos, and tan).
    • Inverse trigonometric functions (asin, acos, atan, and atan2).
    • Hyperbolic functions (sinh, cosh, and tanh).
    • Inverse hyperbolic functions (asinh, acosh, and atanh).
  • Added a Python wrapper for the fn.experimental.numba_function (#2886, #2835, #2903, #2893, and #2887).
  • Image decoder improvements:
    • Enabled ROI decoding in the hardware decoder (#2734).
    • Added support for the Alpha channel in PNG and JP2 decoding (#2867).
    • Added support for YCbCr and BGR in JP2 decoding (#2867).
  • Updated the CUDA version to 11.3 (#2870).
  • Improved the documentation (#2915, #2911, #2927, #2862, and #2858).

Fixed Issues

This DALI release includes the following fixes:

  • Fixed the readers.numpy cache issue (#2932).
  • Fixed an error in readers.nemo_asr (#2928).
  • Fixed a bug that caused the video reader to hang (#2916).

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