Agent skill · nvidia
cuequivariance-jax
Use when writing or debugging cuEquivariance JAX polynomials, irrep dictionaries, Flax NNX layers, or CPU/CUDA execution and layouts.
What it needs
About 9k tokens when loaded.
What this skill does
cuEquivariance in JAX Purpose Execute cuequivariance (cue) descriptors with cuequivariancejax (cuex). Preserve the project's framework and devices. Custom representations use core cuequivariance; PyTorch modules use cuequivariancetorch. Inputs Required inputs: operation, SO3/O3 irreps, layout, batch shapes, dtype, device, and weight ownership. Derive them from the request/code; state defaults. Graphs also need indices and destination count. Operand sizes/output irreps come from descriptors. Optional inputs: backend/performance preferences. Instructions 1. Probe the project interpreter once and reuse working packages. Environment setup/recovery must not recursively delete directories, including temporary environments. Use a fresh unique path when isolation is needed. 2. Select method="naive" for CPU; Flax is needed only for NNX. High-level dictionary blocks are (..., mul, ir.dim); uniform CUDA arrays differ. 3. Adapt one matching recipe into a script. Build descriptors outside transformed functions, broadcast leading input axes, and enable x64 before array creation for float64 checks. 4. Finish installation before running the saved script with the completion recipe below. A running session/task ID, empty output, or a file write is not a completed check. Poll the same session until it exits; then read its results before reporting success. 5. Investigate a concrete failure using its error and the affected installed API. Rerun affected checks after a fix. Once the requested checks pass, finish; avoid repeated probes, unrelated examples, or exploration of other backends for a CPU reference. Prerequisites and environment recovery Probe imports independently so a missing frontend does not hide working JAX. For an NNX task, include "flax.nnx" in the same loop: Reuse working packages; install only missing dependencies when needed. Honor the project's lockfile or supplied scripts/requirements.txt and compatible core/frontend revisions. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/bionemo-cuequivariance-jax