Refactor kokoro export (#2302)

- generate samples for https://k2-fsa.github.io/sherpa/onnx/tts/all/
- provide int8 model for kokoro v0.19 kokoro-int8-en-v0_19.tar.bz2

scripts/kokoro/v0.19/dynamic_quantization.py

@@ -0,0 +1,47 @@
+#!/usr/bin/env python3
+# Copyright    2025  Xiaomi Corp.        (authors: Fangjun Kuang)
+
+from pathlib import Path
+
+import onnxruntime
+from onnxruntime.quantization import QuantType, quantize_dynamic
+
+
+def show(filename):
+    session_opts = onnxruntime.SessionOptions()
+    session_opts.log_severity_level = 3
+    sess = onnxruntime.InferenceSession(filename, session_opts)
+    for i in sess.get_inputs():
+        print(i)
+
+    print("-----")
+
+    for i in sess.get_outputs():
+        print(i)
+
+
+"""
+NodeArg(name='tokens', type='tensor(int64)', shape=[1, 'tokens1'])
+NodeArg(name='style', type='tensor(float)', shape=[1, 256])
+NodeArg(name='speed', type='tensor(float)', shape=[1])
+-----
+NodeArg(name='audio', type='tensor(float)', shape=['audio0'])
+"""
+
+
+def main():
+    show("./model.onnx")
+
+    if not Path("./model.int8.onnx").is_file():
+        quantize_dynamic(
+            model_input="model.onnx",
+            model_output="model.int8.onnx",
+            #  op_types_to_quantize=["MatMul"],
+            weight_type=QuantType.QUInt8,
+        )
+    else:
+        print("./model.int8.onnx exists - skip")
+
+
+if __name__ == "__main__":
+    main()