| # Performance Report |
|
|
| - Board: AX650N (`10.126.29.50`) |
| - Runtime: AX Engine 2.12.0s / pyaxengine `AxEngineExecutionProvider` |
| - Model: H-GTCRN neural core (`feat -> mask`) |
| - Sample duration for RTF: 10.0 s |
| - Input tensor: `feat[1, 6, 626, 257]`, FP32 |
| - Output tensor: `mask[1, 2, 626, 257]`, FP32 |
|
|
| | Runtime | First run | 20-run average | Core RTF | |
| |---|---:|---:|---:| |
| | Python SDK | 31.831 ms | 21.142 ms | 0.002114 | |
| | C++ SDK | 22.023 ms | 20.123 ms | 0.002012 | |
|
|
| | Check | Value | |
| |---|---:| |
| | Python/C++ output cosine | 1.0 | |
| | Python/C++ output MAE | 0.0 | |
| | Python/C++ max absolute difference | 0.0 | |
| | Board/reference mask cosine | 0.99876 | |
| | Board/original infer audio cosine | 0.999468371 | |
| | Board/original infer audio MAE | 0.000655536079 | |
| | ONNX/original infer audio cosine | 0.9999999998 | |
| | ONNX/original infer audio MAE | 0.0000000109 | |
|
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| Audio sample: |
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|
| - Input: `samples/Samples1_noisy.wav`, 16 kHz, 10.0 s, 2 channels, RMS 0.09499 |
| - Original `infer.py` output RMS: 0.02980 |
| - Board output: `samples/Samples1_board_enhanced.wav`, RMS 0.02932 |
|
|
| The RTF number covers only the compiled NPU neural core. CPU-side STFT/WPE/IVA, |
| feature construction, mask application, and ISTFT are not included. |
|
|
| The export was fixed on 2026-08-13: `FoldedConvTranspose2d` now preserves the |
| original activation (`PReLU`/`Tanh`) after folding BatchNorm into ConvTranspose. |
| Before this fix, ONNX and AXMODEL were mutually consistent but did not match the |
| original `GTCRN_IVA.forward()` audio. |
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