DALI Release 0.8 Beta

The DALI 0.8 is a beta release. Hence, for all the features, the functionality and performance will likely be limited.

Using DALI 0.8 Beta

The DALI 0.8 can be used with the 19.03 NVIDIA GPU Cloud (NGC) optimized container for MXNet, PyTorch, and TensorFlow. Also, the 19.04 container will be shipped with DALI 0.8.

To upgrade to DALI 0.8 beta from an older version of DALI, follow the installation instructions in the DALI Quick Start Guide.

Refer to the DALI Developer Guide for usage details.

Note: The internal DALI C++ API used for operators implementation, and the C++ API that enables using DALI as a library from native code, are 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.

  • Provides the CUDA 10-based DALI prebuilt binary.
  • Added the customizable and decoupled executor stages. The CPU and GPU prefetch queues can now have different depths.
  • The nvJPEG decoder now supports ROI-based decoding.
  • The nvJPEG decoder now has split variants. The CPU and GPU part can be concurrently executed and independently prefetched.
  • Improved the resize operator to support bilinear and triangular resampling. This improves the quality during aggressive down-scaling.
  • Added the ability to return sparse tensor on CPU for TF DALI op.
  • Fixed bugs in the detection pipeline operators. These bugs might have lead to inferior training accuracy.

Breaking API Changes

  • None.

Known Issues

  • The new video reader operator requires NVIDIA VIDEO CODEC SDK support in the platform. Prior to 19.01, the NVIDIA GPU Cloud (NGC) optimized containers lack this functionality in the default configuration. To enable the functionality, run the container with the "video" capability enabled, as below:
    -e "NVIDIA_DRIVER_CAPABILITIES=compute,utility,video"
  • 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 lesser frequency, then the returned frames may be out of sync.