The DALI 0.10.0
is a beta release. Hence, for all the features, the functionality and performance will
likely be limited.
Using DALI 0.10.0 Beta
The DALI 0.10.0 can be used with the 19.06 NVIDIA GPU Cloud (NGC) optimized container for
MXNet, PyTorch, and TensorFlow. Also, the 19.06 container will be shipped with DALI
0.10.0.
To upgrade to DALI 0.10.0 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.
- Reduced peak memory consumption. DALI tends to do new allocation before releasing the old
memory during buffer resize. As it does not copy the old memory content, the old
memory can be freed before allocating the new memory.
- Started publishing DALI nightly builds for CUDA 9 and CUDA 10, and weekly for
CUDA 10.
- Added Python function operator. Now the user can create a Python-based operator
that accepts one input and produces one output.