Begin to support https://github.com/usefulsensors/moonshine (#1470)

scripts/moonshine/export-onnx.py

@@ -0,0 +1,40 @@
+#!/usr/bin/env python3
+# Copyright      2024  Xiaomi Corp.        (authors: Fangjun Kuang)
+
+from pathlib import Path
+
+import tokenizers
+from onnxruntime.quantization import QuantType, quantize_dynamic
+
+
+def generate_tokens():
+    if Path("./tokens.txt").is_file():
+        return
+    print("Generating tokens.txt")
+    tokenizer = tokenizers.Tokenizer.from_file("./tokenizer.json")
+    vocab_size = tokenizer.get_vocab_size()
+    with open("tokens.txt", "w", encoding="utf-8") as f:
+        for i in range(vocab_size):
+            s = tokenizer.id_to_token(i).strip()
+            f.write(f"{s}\t{i}\n")
+
+
+def main():
+    generate_tokens()
+
+    # Note(fangjun): Don't use int8 for the preprocessor since it has
+    # a larger impact on the accuracy
+    for f in ["uncached_decode", "cached_decode", "encode"]:
+        if Path(f"{f}.int8.onnx").is_file():
+            continue
+
+        print("processing", f)
+        quantize_dynamic(
+            model_input=f"{f}.onnx",
+            model_output=f"{f}.int8.onnx",
+            weight_type=QuantType.QInt8,
+        )
+
+
+if __name__ == "__main__":
+    main()