Export Pyannote speaker segmentation models to onnx (#1382)

scripts/pyannote/segmentation/preprocess.sh

@@ -0,0 +1,31 @@
+#!/usr/bin/env bash
+
+
+python3 -m onnxruntime.quantization.preprocess --input model.onnx --output tmp.preprocessed.onnx
+mv ./tmp.preprocessed.onnx ./model.onnx
+./show-onnx.py --filename ./model.onnx
+
+<<EOF
+=========./model.onnx==========
+NodeArg(name='x', type='tensor(float)', shape=[1, 1, 'T'])
+-----
+NodeArg(name='y', type='tensor(float)', shape=[1, 'floor(floor(floor(floor(T/10 - 251/10)/3 - 2/3)/3)/3 - 8/3) + 1', 7])
+
+  floor(floor(floor(floor(T/10 - 251/10)/3 - 2/3)/3)/3 - 8/3) + 1
+= floor(floor(floor(floor(T - 251)/30 - 2/3)/3)/3 - 8/3) + 1
+= floor(floor(floor(floor(T - 271)/30)/3)/3 - 8/3) + 1
+= floor(floor(floor(floor(T - 271)/90))/3 - 8/3) + 1
+= floor(floor(floor(T - 271)/90)/3 - 8/3) + 1
+= floor(floor((T - 271)/90)/3 - 8/3) + 1
+= floor(floor((T - 271)/90 - 8)/3) + 1
+= floor(floor((T - 271 - 720)/90)/3) + 1
+= floor(floor((T - 991)/90)/3) + 1
+= floor(floor((T - 991)/270)) + 1
+= (T - 991)/270 + 1
+= (T - 991 + 270)/270
+= (T - 721)/270
+
+It means:
+ - Number of input samples should be at least 721
+ - One frame corresponds to 270 samples. (If we use T + 270, it outputs one more frame)
+EOF