Export silero_vad v4 to RKNN (#2067)

scripts/silero_vad/v4/export-onnx.py

@@ -0,0 +1,49 @@
+#!/usr/bin/env python3
+# Copyright    2025  Xiaomi Corp.        (authors: Fangjun Kuang)
+
+import onnx
+import torch
+from onnxsim import simplify
+
+
+@torch.no_grad()
+def main():
+    m = torch.jit.load("./silero_vad.jit")
+    x = torch.rand((1, 512), dtype=torch.float32)
+    h = torch.rand((2, 1, 64), dtype=torch.float32)
+    c = torch.rand((2, 1, 64), dtype=torch.float32)
+    torch.onnx.export(
+        m._model,
+        (x, h, c),
+        "m.onnx",
+        input_names=["x", "h", "c"],
+        output_names=["prob", "next_h", "next_c"],
+    )
+
+    print("simplifying ...")
+    model = onnx.load("m.onnx")
+
+    meta_data = {
+        "model_type": "silero-vad-v4",
+        "sample_rate": 16000,
+        "version": 4,
+        "h_shape": "2,1,64",
+        "c_shape": "2,1,64",
+    }
+
+    while len(model.metadata_props):
+        model.metadata_props.pop()
+
+    for key, value in meta_data.items():
+        meta = model.metadata_props.add()
+        meta.key = key
+        meta.value = str(value)
+    print("--------------------")
+    print(model.metadata_props)
+
+    model_simp, check = simplify(model)
+    onnx.save(model_simp, "m.onnx")
+
+
+if __name__ == "__main__":
+    main()