rocAL Installation

rocAL Installation#

This chapter provides information about the installation of rocAL and related packages.

3.1 Prerequisites#

  • Linux Distribution

  • AMD RPP library

  • MIvisionX (AMD RPP OpenVX extension)

  • Boost lib 1.66 or higher

  • Turbo JPEG with Partial Decoder support

  • Half float library

  • jsoncpp library

  • Google protobuf 3.11.1 or higher

  • LMDB

3.2 Platform Support#

To see the list of supported platforms for rocAL, see the ROCm Installation Guide at https://docs.amd.com.

3.3 Installing rocAL#

rocAL is shipped along with MIVisionX. To build and install the rocAL C++ library, follow the instructions given here.

3.4 Installing rocAL Python Package#

The rocAL Python package (rocal_pybind) is a separate redistributable wheel. rocal_pybind, which is created using Pybind11, enables data transfer between rocAL C++ API and Python API. With the help of rocal_pybind.so wrapper library, the rocAL functionality, which is primarily in C/C++, can be effectively used in Python. The Python package supports PyTorch, TensorFlow, Caffe2, and data readers available for various formats such as FileReader, COCO Reader, TFRecord Reader, and CaffeReader.

To build and install the Python package, see rocAL python.

3.5 Installing rocAL Using Framework Dockers#

To test the rocAL Python APIs using PyTorch or TensorFlow, we recommend building a docker with rocAL and ROCm using any of the links below:

To use rocAL on Ubuntu, use the following dockers:

Contents