vllm_omni/edge/decoder_export.py exports a stateless windowed decoder (context
72 frames + chunk, one program per ramp chunk size) via torch.export (.pt2,
verified here on CPU for chunks 2 and 25 with the real 0.6B decoder: exact
match vs eager, 460 MB fp32 per program) or ExecuTorch XNNPACK (.pte; written
against the executorch 1.x API, not executed: package not installed, install
is permission gated; QNN partitioner export-only/unverified). The WP5 client
gains --decoder-backend executorch --pte-manifest for phone/NPU targets.
benchmarks/tts/edge_results/summarize.py renders all committed JSON as tables.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
