attribute-bindings

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name: attribute-bindings description: > Creating persistent attribute bindings for efficient repeated writes to the same prims and attribute. Use when user asks about persistent bindings, repeated writes, efficient animation loops, bind_attribute, or updating transforms every frame with caller-owned tensors. Use mapping-attributes when the hot path needs zero-copy direct writes into ovrtx buffers. license: LicenseRef-NvidiaProprietary version: "0.3.0" author: NVIDIA ovrtx tags: - ovrtx - attributes - bindings tools: - Read - Grep

Attribute Bindings

When to Use

Use this skill when the user asks about persistent bindings, repeated writes, efficient animation loops, bind_attribute, or updating transforms every frame with caller-owned data. Use mapping-attributes instead when the user specifically needs zero-copy direct access to ovrtx internal buffers, CUDA/Warp kernels writing in place, or map/unmap lifetimes.

Inputs

Resolve inputs in this order: existing repository files and referenced snippets, explicit user request, then broader agent context.

• Target API surface: Python, C/C++, or both.
• Prim paths, attribute name, element type, semantic conversion, and whether the attribute is scalar or array-valued.
• Repeated-write cadence, sync/async behavior, caller-owned data location, and whether CUDA stream/event synchronization is needed.
• Whether the user needs binding writes, binding maps, or one-shot writes.
• Repository source snippets referenced below. Treat these snippets as the API source of truth.

Prerequisites

• Use an ovrtx checkout that contains the referenced examples and docs tests.
• Read the relevant > **Source:** snippet before writing or explaining API usage.
• Use writing-attributes for one-shot or infrequent writes where descriptor creation cost does not matter.
• Use mapping-attributes for zero-copy direct buffer access; this skill can still apply when creating a persistent binding first and then mapping through it repeatedly.

Instructions

1. Identify whether the user needs repeated write() calls, repeated write_async() calls, or repeated map() calls through a stable binding.
2. Read the matching source snippet and copy its create/use/destroy lifecycle rather than inventing equivalent calls.
3. Validate prim list, attribute name, dtype, shape, semantic, and array/scalar rules before proposing or editing code.
4. Keep the binding alive across repeated updates, and explicitly destroy or unbind it when the hot path ends.
5. Choose mapping-attributes when avoiding the data copy matters more than avoiding descriptor recreation.
6. When changing code, run the narrow docs test or example that owns the snippet whenever practical.

Output Format

• For explanations, cite the relevant API names, source snippets, and caveats.
• For code changes, summarize the files changed, snippets affected, and validation run.

Scripts

This skill has no scripts.

Limitations

• The referenced snippets remain the source of truth; update or add tested snippets before documenting new API usage.

Overview

When writing the same attribute to the same set of prims every frame (e.g., animating transforms), creating a persistent binding avoids the overhead of rebuilding the binding descriptor each time. Create the binding once, then call write() or map() on it repeatedly. For "update transforms every frame", start here unless the request explicitly calls for zero-copy direct buffer writes or GPU kernels that operate on ovrtx-owned memory.

Python

Direct write (no binding)

For one-shot or infrequent writes, renderer.write_attribute() rebuilds the binding descriptor each call:

Source: tests/docs/python/test_attribute_bindings.py snippet doc-write-attribute-async-data-access

Create binding and write

For repeated writes to the same attribute/prims, create a persistent binding once:

Source: tests/docs/python/test_attribute_bindings.py snippet doc-bind-attribute-write

Reuse binding for repeated writes

Source: tests/docs/python/test_attribute_bindings.py snippet doc-binding-write-async

Array attribute binding

Source: tests/docs/python/test_attribute_bindings.py snippet doc-bind-array-attribute

Binding with explicit semantic

Source: tests/docs/python/test_attribute_bindings.py snippet doc-bind-attribute-write

Use binding for mapping (zero-copy)

Source: tests/docs/python/test_attribute_bindings.py snippet doc-map-bound-attribute

C

Create and use a persistent binding

Source: tests/docs/c/test_attribute_bindings.cpp snippets doc-create-attribute-binding-c, doc-write-bound-attribute-c, doc-destroy-attribute-binding-c

Key Types / Functions

Binding flags (C only, set via desc.flags):

• OVRTX_BINDING_FLAG_NONE -- default
• OVRTX_BINDING_FLAG_OPTIMIZE -- optimize internal structures for frequent high-volume writes

Troubleshooting

• Tensor lifetime: When using binding.map(), the returned mapping.tensor is only valid inside the with block (Python) or before unmap (C). All tensor access must happen while the mapping is active — accessing it after unmap is undefined behavior.
• The canonical transform attribute name is "omni:xform". The legacy name "omni:fabric:localMatrix" (used in examples above) is also accepted. New code should prefer "omni:xform".
• Always call unbind() (Python) or ovrtx_destroy_attribute_binding() (C) when done. In Python, the binding auto-unbinds on garbage collection, but explicit cleanup is preferred.
• The binding locks in the prim list, attribute name, and element type. You cannot change these after creation.
• In C, OVRTX_BINDING_FLAG_OPTIMIZE should be used for the primary hot-path binding. The last binding created with this flag takes priority.
• In Python, bind_attribute is synchronous (blocks until the binding is ready). Use bind_attribute_async for non-blocking creation.

References

• Use the > **Source:** directives in this skill to locate tested snippets before reusing API patterns.
• Keep related skills, docs, and snippets synchronized when changing the workflow.