DALI Release 1.3.0

Using DALI 1.3.0

To upgrade to DALI 1.3.0 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 operator:
    • Salt and Pepper noise (noise.salt_and_pepper) for CPU and GPU (#2889, #2934, #2956, and #2976).
  • Added experimental support for inputs via external_source in TensorFlow DALIDataset (#2949, #2993, and #2997).
  • Numpy reader improvements:
    • ROI reading for CPU (#3011).
    • intra-sample threading on GPU (#3010).
  • Improved CPU color_space_conversion operator performance (#2987).
  • Improved brightness and contrast operators performance (#2981).
  • Added a C API call to check backend of an operator (#3031 and #3050).
  • Documentation improvements (#2936, #2960, #2979, #2972, #3013, and #3035).

Fixed Issues

This DALI release includes the following fixes:

  • Fixed an issue in readers.nemo_asr that caused a system error due to keeping too many open files (#3003).
  • Fixed a bug that caused out of bound memory access in mel_filter_bank (#2986).
  • Fixed a cudaErrorLaunchOutOfResources error that appeared in transpose operator on some GPUs (#2971).
  • Fixed handling of non-existing entries in readers.tfrecord (#2952).

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