Types of Tensors

Currently, NvMedia only supports 4-dimensional tensors:

NvMedia Tensors are used with NvMedia DLA components.

NvMedia Tensors can be created by allocating NvSciBuf through NvMedia Tensor attributes using NvSciBuf API. As NvSciBuf APIs facilitate data sharing between NvMedia and NVIDIA® CUDA®, this allows tensors allocated to be reused as permitted by NvSciBuf API. For more information, see the NvSciBuf API and use cases.

NvMedia Tensor have two types of attributes:

• Tensor format attributes describe a tensor's order and format in memory.
• Tensor allocation attributes describe additional properties of a tensor, such as:
  • Width, height, channels, and number of tensor surfaces.
  • CPU access mapping (cached/uncached/unmapped).
  • Shared memory space across virtual machine partitions.