This chapter provides information about the installation of rocAL and related packages.
- Linux distribution
- AMD RPP
- AMD OpenVX™ and AMD OpenVX™ Extensions:
VX_RPP
andAMD Media
- Turbo JPEG - Version
2.0
or higher - Half-precision floating-point library - Version
1.12.0
or higher - Google Protobuf - Version
3.12.4
or higher - LMBD Library
- RapidJSON
- PyBind11
To see the list of supported platforms for rocAL, see the ROCm Installation Guide at https://docs.amd.com.
rocAL is shipped along with MIVisionX. To build and install the rocAL C++ library, follow the instructions given here
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.
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: