Add long chunk onnx

am-onnx/decoder.chunk64.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3cca47e861640eed6b0693fd68fa25a48ed584ab053e0db8259fa26cbf85054e
+size 2093080

am-onnx/encoder.chunk64.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5423647f6fc579c765c494ef4f6747c3cfc1847d08691cceac7b6b4210620982
+size 90989508

am-onnx/joiner.chunk64.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:df4cd0d4609a5877a0b72a44c439b5baefd1788249cb59327dc3cf476ef34219
+size 1026462

decode-long-chunk.py

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+#!/usr/bin/env python3
+import wave
+from pathlib import Path
+from typing import Tuple
+import sys
+import numpy as np
+import sherpa_onnx
+
+def read_wave(wave_filename: str) -> Tuple[np.ndarray, int]:
+    with wave.open(wave_filename) as f:
+        assert f.getnchannels() == 1, f.getnchannels()
+        assert f.getsampwidth() == 2, f.getsampwidth()  # it is in bytes
+        num_samples = f.getnframes()
+        samples = f.readframes(num_samples)
+        samples_int16 = np.frombuffer(samples, dtype=np.int16)
+        samples_float32 = samples_int16.astype(np.float32)
+        samples_float32 = samples_float32 / 32768
+        return samples_float32, f.getframerate()
+
+def main():
+
+    recognizer = sherpa_onnx.OnlineRecognizer.from_transducer(
+            encoder="am-onnx/encoder.chunk64.onnx",
+            decoder="am-onnx/decoder.chunk64.onnx",
+            joiner="am-onnx/joiner.chunk64.onnx",
+            tokens="lang/tokens.txt",
+            num_threads=4,
+            sample_rate=16000,
+            dither=3e-5,
+            decoding_method="modified_beam_search",
+            max_active_paths=10)
+
+    samples, sample_rate = read_wave("test.wav")
+
+    s = recognizer.create_stream()
+    s.accept_waveform(sample_rate, waveform=samples)
+    tail_padding = np.zeros(int(sample_rate * 2.0)).astype(np.float32)
+    s.accept_waveform(sample_rate, waveform=tail_padding)
+    s.input_finished()
+
+    while recognizer.is_ready(s):
+        recognizer.decode_stream(s)
+        print (recognizer.get_result(s))
+
+if __name__ == "__main__":
+    main()
+