Add CI test for Whisper models (#239)

+#!/usr/bin/env bash
+
+set -e
+
+log() {
+  # This function is from espnet
+  local fname=${BASH_SOURCE[1]##*/}
+  echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
+}
+
+echo "EXE is $EXE"
+echo "PATH: $PATH"
+
+which $EXE
+
+names=(
+tiny.en
+base.en
+# small.en
+# medium.en
+)
+
+for name in ${names[@]}; do
+  log "------------------------------------------------------------"
+  log "Run $name"
+  log "------------------------------------------------------------"
+
+  repo_url=https://huggingface.co/csukuangfj/sherpa-onnx-whisper-$name
+  log "Start testing ${repo_url}"
+  repo=$(basename $repo_url)
+  log "Download pretrained model and test-data from $repo_url"
+
+  GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
+  pushd $repo
+  git lfs pull --include "*.onnx"
+  git lfs pull --include "*.ort"
+  ls -lh *.{onnx,ort}
+  popd
+
+  log "test fp32 onnx"
+
+  time $EXE \
+    --tokens=$repo/${name}-tokens.txt \
+    --whisper-encoder=$repo/${name}-encoder.onnx \
+    --whisper-decoder=$repo/${name}-decoder.onnx \
+    --num-threads=2 \
+    $repo/test_wavs/0.wav \
+    $repo/test_wavs/1.wav \
+    $repo/test_wavs/8k.wav
+
+  log "test int8 onnx"
+
+  time $EXE \
+    --tokens=$repo/${name}-tokens.txt \
+    --whisper-encoder=$repo/${name}-encoder.int8.onnx \
+    --whisper-decoder=$repo/${name}-decoder.int8.onnx \
+    --num-threads=2 \
+    $repo/test_wavs/0.wav \
+    $repo/test_wavs/1.wav \
+    $repo/test_wavs/8k.wav
+
+  log "test fp32 ort"
+
+  time $EXE \
+    --tokens=$repo/${name}-tokens.txt \
+    --whisper-encoder=$repo/${name}-encoder.ort \
+    --whisper-decoder=$repo/${name}-decoder.ort \
+    --num-threads=2 \
+    $repo/test_wavs/0.wav \
+    $repo/test_wavs/1.wav \
+    $repo/test_wavs/8k.wav
+
+  log "test int8 ort"
+
+  time $EXE \
+    --tokens=$repo/${name}-tokens.txt \
+    --whisper-encoder=$repo/${name}-encoder.int8.ort \
+    --whisper-decoder=$repo/${name}-decoder.int8.ort \
+    --num-threads=2 \
+    $repo/test_wavs/0.wav \
+    $repo/test_wavs/1.wav \
+    $repo/test_wavs/8k.wav
+
+  rm -rf $repo
+done

@@ -84,6 +84,14 @@ jobs:
           file build/bin/sherpa-onnx
           readelf -d build/bin/sherpa-onnx
 
+      - name: Test offline Whisper
+        shell: bash
+        run: |
+          export PATH=$PWD/build/bin:$PATH
+          export EXE=sherpa-onnx-offline
+
+          .github/scripts/test-offline-whisper.sh
+
       - name: Test offline CTC
         shell: bash
         run: |

@@ -82,6 +82,14 @@ jobs:
           otool -L build/bin/sherpa-onnx
           otool -l build/bin/sherpa-onnx
 
+      - name: Test offline Whisper
+        shell: bash
+        run: |
+          export PATH=$PWD/build/bin:$PATH
+          export EXE=sherpa-onnx-offline
+
+          .github/scripts/test-offline-whisper.sh
+
       - name: Test offline CTC
         shell: bash
         run: |

@@ -74,6 +74,14 @@ jobs:
 
           ls -lh ./bin/Release/sherpa-onnx.exe
 
+      - name: Test offline Whisper for windows x64
+        shell: bash
+        run: |
+          export PATH=$PWD/build/bin/Release:$PATH
+          export EXE=sherpa-onnx-offline.exe
+
+          .github/scripts/test-offline-whisper.sh
+
       - name: Test offline CTC for windows x64
         shell: bash
         run: |

@@ -75,6 +75,14 @@ jobs:
 
           ls -lh ./bin/Release/sherpa-onnx.exe
 
+      - name: Test offline Whisper for windows x64
+        shell: bash
+        run: |
+          export PATH=$PWD/build/bin/Release:$PATH
+          export EXE=sherpa-onnx-offline.exe
+
+          .github/scripts/test-offline-whisper.sh
+
       - name: Test offline CTC for windows x64
         shell: bash
         run: |

@@ -73,6 +73,14 @@ jobs:
 
           ls -lh ./bin/Release/sherpa-onnx.exe
 
+      - name: Test offline Whisper for windows x86
+        shell: bash
+        run: |
+          export PATH=$PWD/build/bin/Release:$PATH
+          export EXE=sherpa-onnx-offline.exe
+
+          .github/scripts/test-offline-whisper.sh
+
       - name: Test offline CTC for windows x86
         shell: bash
         run: |

@@ -5,5 +5,9 @@ and use onnxruntime to replace PyTorch for speech recognition.
 
 You can use [sherpa-onnx][sherpa-onnx] to run the converted model.
 
+Please see
+https://k2-fsa.github.io/sherpa/onnx/pretrained_models/whisper/export-onnx.html
+for details.
+
 [whisper]: https://github.com/openai/whisper
 [sherpa-onnx]: https://github.com/k2-fsa/sherpa-onnx

@@ -18,15 +18,30 @@ import argparse
 def get_args():
     parser = argparse.ArgumentParser()
     parser.add_argument(
-        "--model",
+        "--encoder",
         type=str,
         required=True,
-        # fmt: off
-        choices=[
-            "tiny", "tiny.en", "base", "base.en",
-            "small", "small.en", "medium", "medium.en",
-            "large", "large-v1", "large-v2"],
-        # fmt: on
+        help="Path to the encoder",
+    )
+
+    parser.add_argument(
+        "--decoder",
+        type=str,
+        required=True,
+        help="Path to the decoder",
+    )
+
+    parser.add_argument(
+        "--tokens",
+        type=str,
+        required=True,
+        help="Path to the tokens",
+    )
+
+    parser.add_argument(
+        "sound_file",
+        type=str,
+        help="Path to the test wave",
     )
     return parser.parse_args()
 
@@ -161,11 +176,10 @@ def load_tokens(filename):
 
 def main():
     args = get_args()
-    name = args.model
+    encoder = args.encoder
+    decoder = args.decoder
 
-    encoder = f"./{name}-encoder.onnx"
-    decoder = f"./{name}-decoder.onnx"
-    audio = whisper.load_audio("0.wav")
+    audio = whisper.load_audio(args.sound_file)
 
     features = []
     online_whisper_fbank = knf.OnlineWhisperFbank(knf.FrameExtractionOptions())
@@ -224,17 +238,13 @@ def main():
         logits = logits[0, -1]
         model.suppress_tokens(logits, is_initial=False)
         max_token_id = logits.argmax(dim=-1)
-    token_table = load_tokens(f"./{name}-tokens.txt")
+    token_table = load_tokens(args.tokens)
     s = b""
     for i in results:
         if i in token_table:
             s += base64.b64decode(token_table[i])
-        else:
-            print("oov", i)
 
     print(s.decode().strip())
-    print(results)
-    print(model.sot_sequence)
 
 
 if __name__ == "__main__":