Summary

It seems that the following line in def broadcast_inputs(x, y) triggerred a tensor storage copy that caused a CUDA memory overflow when I tried to run a small bundle adjustment dataset with 31843 pixel observations. Both reshape and contiguous could trigger a memory copy. If we can avoid memory copy in broadcast_inputs, we can avoid overflowing CUDA memory at this step.

Improvements

refactor broadcast_inputs to not use reshape and contiguous.

Risks

TBD

Involved components

• pypose/pypose/lietensor/operation.py

Optional: Intended side effects

TBD

Optional: Missing test coverage

TBD