Tensor Bindings: CPU Read and Write

Tensor bindings map physics-object path patterns to typed tensor views, including authored USD objects and runtime-only clones. This enables bulk data exchange with NumPy, PyTorch, Warp, or any other DLPack-compatible framework.

When to Use

Use this skill when a caller needs bulk CPU tensor reads or writes for simulation state, such as poses, velocities, or joint targets, through the public TensorBindingsAPI.

Instructions

1. Read docs/tutorials/tensor_bindings.md and the sample for the caller's language before changing code.
2. Populate an ovstage, attach it at that ordinal, create bindings once from stable physics-object path patterns, then reuse them to read or write tensors with the binding shape and dtype.
3. Use Shell to run the Python sample or compile the C sample after adapting the scene path and tensor type.

Python