DLPack: Open In Memory Tensor Structure
DLPack is an open in-memory tensor structure to for sharing tensor among frameworks. DLPack enables
- Easier sharing of operators between deep learning frameworks.
- Easier wrapping of vendor level operator implementations, allowing collaboration when introducing new devices/ops.
- Quick swapping of backend implementations, like different version of BLAS
- For final users, this could bring more operators, and possibility of mixing usage between frameworks.
We do not intend to implement of Tensor and Ops, but instead use this as common bridge to reuse tensor and ops across frameworks.
RFC proposals are opened as issues. The major release will happen as a vote issue to make sure the participants agree on the changes.
There are two major components so far
- include: stabilized headers
- contrib: in progress unstable libraries
Here are list of people who have been involved in DLPack RFC design proposals:
@soumith @piiswrong @Yangqing @naibaf7 @bhack @edgarriba @tqchen @prigoyal @zdevito