Set batch size to 1 for more streaming ASR models (#1280)

@@ -7,7 +7,6 @@ on:
 
   workflow_dispatch:
 
-
 concurrency:
   group: mobile-asr-models-${{ github.ref }}
   cancel-in-progress: true
@@ -16,11 +15,14 @@ jobs:
   mobile-asr-models:
     if: github.repository_owner == 'k2-fsa' || github.repository_owner == 'csukuangfj' || github.repository_owner == 'csu-fangjun'
     runs-on: ${{ matrix.os }}
+    name: ${{ matrix.index }}/${{ matrix.total }}
     strategy:
       fail-fast: false
       matrix:
         os: [ubuntu-latest]
         python-version: ["3.8"]
+        total: ["11"]
+        index: ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10"]
 
     steps:
       - uses: actions/checkout@v4
@@ -33,7 +35,20 @@ jobs:
       - name: Install dependencies
         shell: bash
         run: |
-          python3 -m pip install onnxruntime==1.16.3 onnx==1.15.0
+          python3 -m pip install onnxruntime==1.16.3 onnx==1.15.0 jinja2
+
+      - name: Generate build script
+        shell: bash
+        run: |
+          cd scripts/mobile-asr-models
+
+          total=${{ matrix.total }}
+          index=${{ matrix.index }}
+
+          ./generate-asr.py --total $total --index $index
+          chmod +x run2.sh
+          mv run2.sh run.sh
+          ls -lh
 
       - name: Run
         shell: bash

+name: mobile-kws-models
+
+on:
+  push:
+    branches:
+      - asr-mobile
+
+  workflow_dispatch:
+
+concurrency:
+  group: mobile-kws-models-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  mobile-kws-models:
+    if: github.repository_owner == 'k2-fsa' || github.repository_owner == 'csukuangfj' || github.repository_owner == 'csu-fangjun'
+    runs-on: ${{ matrix.os }}
+    name: ${{ matrix.index }}/${{ matrix.total }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [ubuntu-latest]
+        python-version: ["3.8"]
+        total: ["2"]
+        index: ["0", "1"]
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Setup Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install dependencies
+        shell: bash
+        run: |
+          python3 -m pip install onnxruntime==1.16.3 onnx==1.15.0 jinja2
+
+      - name: Generate build script
+        shell: bash
+        run: |
+          cd scripts/mobile-asr-models
+
+          total=${{ matrix.total }}
+          index=${{ matrix.index }}
+
+          ./generate-kws.py --total $total --index $index
+          chmod +x run2.sh
+          mv run2.sh run.sh
+          ls -lh
+
+      - name: Run
+        shell: bash
+        run: |
+          cd scripts/mobile-asr-models
+          ./run.sh
+
+      - name: Release
+        uses: svenstaro/upload-release-action@v2
+        with:
+          file_glob: true
+          file: ./kws/*.tar.bz2
+          overwrite: true
+          repo_name: k2-fsa/sherpa-onnx
+          repo_token: ${{ secrets.UPLOAD_GH_SHERPA_ONNX_TOKEN }}
+          tag: kws-models

@@ -2,7 +2,6 @@
 
 import argparse
 from dataclasses import dataclass
-from typing import List, Optional
 
 import jinja2
 

@@ -2,7 +2,6 @@
 
 import argparse
 from dataclasses import dataclass
-from typing import List, Optional
 
 import jinja2
 

@@ -2,7 +2,6 @@
 
 import argparse
 from dataclasses import dataclass
-from typing import List, Optional
 
 import jinja2
 

@@ -2,7 +2,6 @@
 
 import argparse
 from dataclasses import dataclass
-from typing import List, Optional
 
 import jinja2
 

@@ -2,7 +2,7 @@
 
 import argparse
 from dataclasses import dataclass
-from typing import List, Optional
+from typing import List
 
 import jinja2
 
@@ -34,76 +34,99 @@ class SpeakerIdentificationModel:
 
 def get_3dspeaker_models() -> List[SpeakerIdentificationModel]:
     models = [
-        SpeakerIdentificationModel(model_name="3dspeaker_speech_campplus_sv_en_voxceleb_16k.onnx"),
-        SpeakerIdentificationModel(model_name="3dspeaker_speech_campplus_sv_zh-cn_16k-common.onnx"),
-        SpeakerIdentificationModel(model_name="3dspeaker_speech_eres2net_base_200k_sv_zh-cn_16k-common.onnx"),
-        SpeakerIdentificationModel(model_name="3dspeaker_speech_eres2net_base_sv_zh-cn_3dspeaker_16k.onnx"),
-        SpeakerIdentificationModel(model_name="3dspeaker_speech_eres2net_large_sv_zh-cn_3dspeaker_16k.onnx"),
-        SpeakerIdentificationModel(model_name="3dspeaker_speech_eres2net_sv_en_voxceleb_16k.onnx"),
-        SpeakerIdentificationModel(model_name="3dspeaker_speech_eres2net_sv_zh-cn_16k-common.onnx"),
+        SpeakerIdentificationModel(
+            model_name="3dspeaker_speech_campplus_sv_en_voxceleb_16k.onnx"
+        ),
+        SpeakerIdentificationModel(
+            model_name="3dspeaker_speech_campplus_sv_zh-cn_16k-common.onnx"
+        ),
+        SpeakerIdentificationModel(
+            model_name="3dspeaker_speech_eres2net_base_200k_sv_zh-cn_16k-common.onnx"
+        ),
+        SpeakerIdentificationModel(
+            model_name="3dspeaker_speech_eres2net_base_sv_zh-cn_3dspeaker_16k.onnx"
+        ),
+        SpeakerIdentificationModel(
+            model_name="3dspeaker_speech_eres2net_large_sv_zh-cn_3dspeaker_16k.onnx"
+        ),
+        SpeakerIdentificationModel(
+            model_name="3dspeaker_speech_eres2net_sv_en_voxceleb_16k.onnx"
+        ),
+        SpeakerIdentificationModel(
+            model_name="3dspeaker_speech_eres2net_sv_zh-cn_16k-common.onnx"
+        ),
     ]
 
-    prefix = '3dspeaker_speech_'
+    prefix = "3dspeaker_speech_"
     num = len(prefix)
     for m in models:
-        m.framework = '3dspeaker'
+        m.framework = "3dspeaker"
         m.short_name = m.model_name[num:-5]
-        if '_zh-cn_' in m.model_name:
-            m.lang = 'zh'
-        elif '_en_' in m.model_name:
-            m.lang = 'en'
+        if "_zh-cn_" in m.model_name:
+            m.lang = "zh"
+        elif "_en_" in m.model_name:
+            m.lang = "en"
         else:
             raise ValueError(m)
     return models
 
+
 def get_wespeaker_models() -> List[SpeakerIdentificationModel]:
     models = [
         SpeakerIdentificationModel(model_name="wespeaker_en_voxceleb_CAM++.onnx"),
         SpeakerIdentificationModel(model_name="wespeaker_en_voxceleb_CAM++_LM.onnx"),
-        SpeakerIdentificationModel(model_name="wespeaker_en_voxceleb_resnet152_LM.onnx"),
-        SpeakerIdentificationModel(model_name="wespeaker_en_voxceleb_resnet221_LM.onnx"),
-        SpeakerIdentificationModel(model_name="wespeaker_en_voxceleb_resnet293_LM.onnx"),
+        SpeakerIdentificationModel(
+            model_name="wespeaker_en_voxceleb_resnet152_LM.onnx"
+        ),
+        SpeakerIdentificationModel(
+            model_name="wespeaker_en_voxceleb_resnet221_LM.onnx"
+        ),
+        SpeakerIdentificationModel(
+            model_name="wespeaker_en_voxceleb_resnet293_LM.onnx"
+        ),
         SpeakerIdentificationModel(model_name="wespeaker_en_voxceleb_resnet34.onnx"),
         SpeakerIdentificationModel(model_name="wespeaker_en_voxceleb_resnet34_LM.onnx"),
         SpeakerIdentificationModel(model_name="wespeaker_zh_cnceleb_resnet34.onnx"),
         SpeakerIdentificationModel(model_name="wespeaker_zh_cnceleb_resnet34_LM.onnx"),
     ]
 
-    prefix = 'wespeaker_xx_'
+    prefix = "wespeaker_xx_"
     num = len(prefix)
     for m in models:
-        m.framework = 'wespeaker'
+        m.framework = "wespeaker"
         m.short_name = m.model_name[num:-5]
-        if '_zh_' in m.model_name:
-            m.lang = 'zh'
-        elif '_en_' in m.model_name:
-            m.lang = 'en'
+        if "_zh_" in m.model_name:
+            m.lang = "zh"
+        elif "_en_" in m.model_name:
+            m.lang = "en"
         else:
             raise ValueError(m)
     return models
 
+
 def get_nemo_models() -> List[SpeakerIdentificationModel]:
     models = [
-        SpeakerIdentificationModel(model_name="nemo_en_speakerverification_speakernet.onnx"),
+        SpeakerIdentificationModel(
+            model_name="nemo_en_speakerverification_speakernet.onnx"
+        ),
         SpeakerIdentificationModel(model_name="nemo_en_titanet_large.onnx"),
         SpeakerIdentificationModel(model_name="nemo_en_titanet_small.onnx"),
     ]
 
-    prefix = 'nemo_en_'
+    prefix = "nemo_en_"
     num = len(prefix)
     for m in models:
-        m.framework = 'nemo'
+        m.framework = "nemo"
         m.short_name = m.model_name[num:-5]
-        if '_zh_' in m.model_name:
-            m.lang = 'zh'
-        elif '_en_' in m.model_name:
-            m.lang = 'en'
+        if "_zh_" in m.model_name:
+            m.lang = "zh"
+        elif "_en_" in m.model_name:
+            m.lang = "en"
         else:
             raise ValueError(m)
     return models
 
 
-
 def main():
     args = get_args()
     index = args.index

@@ -2,7 +2,6 @@
 
 import argparse
 from dataclasses import dataclass
-from typing import List, Optional
 
 import jinja2
 

+run2.sh

@@ -16,3 +16,97 @@ https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipform
 
 The following [colab notebook](https://colab.research.google.com/drive/1RsVZbsxbPjazeGrNNbZNjXCYbEG2F2DU?usp=sharing)
 provides examples to use the above two models.
+
+**WARNING**: Tested with `onnxruntime==1.16.3 onnx==1.15.0`.
+
+```bash
+pip install onnxruntime==1.16.3 onnx==1.15.0
+```
+
+## More examples
+
+### [sherpa-onnx-streaming-zipformer-korean-2024-06-16](https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#sherpa-onnx-streaming-zipformer-korean-2024-06-16-korean)
+
+
+| | encoder-epoch-99-avg-1.onnx | encoder-epoch-99-avg-1.int8.onnx|
+|---|---|---|
+|Dynamic batch size| 279 MB| 122 MB|
+|Batch size fixed to 1| 264 MB | 107 MB |
+
+### [sherpa-onnx-streaming-zipformer-en-20M-2023-02-17](https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#csukuangfj-sherpa-onnx-streaming-zipformer-en-20m-2023-02-17-english)
+
+| | encoder-epoch-99-avg-1.onnx | encoder-epoch-99-avg-1.int8.onnx|
+|---|---|---|
+|Dynamic batch size| 85 MB| 41 MB|
+|Batch size fixed to 1| 75 MB | 32 MB |
+
+### [sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12](https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12-chinese)
+
+| | encoder-epoch-20-avg-1-chunk-16-left-128.onnx | encoder-epoch-20-avg-1-chunk-16-left-128.int8.onnx|
+|---|---|---|
+|Dynamic batch size| 249 MB| 67 MB|
+|Batch size fixed to 1| 247 MB | 65 MB |
+
+### [icefall-asr-zipformer-streaming-wenetspeech-20230615](https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#pkufool-icefall-asr-zipformer-streaming-wenetspeech-20230615-chinese)
+
+| | encoder-epoch-12-avg-4-chunk-16-left-128.onnx | encoder-epoch-12-avg-4-chunk-16-left-128.int8.onnx|
+|---|---|---|
+|Dynamic batch size| 250 MB| 68 MB|
+|Batch size fixed to 1| 247 MB | 65 MB |
+
+### [sherpa-onnx-streaming-zipformer-en-2023-06-26](https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#csukuangfj-sherpa-onnx-streaming-zipformer-en-2023-06-26-english)
+
+
+| | encoder-epoch-99-avg-1-chunk-16-left-128.onnx | encoder-epoch-99-avg-1-chunk-16-left-128.int8.onnx|
+|---|---|---|
+|Dynamic batch size| 250 MB| 68 MB|
+|Batch size fixed to 1| 247 MB | 65 MB |
+
+### [sherpa-onnx-streaming-zipformer-en-2023-06-21](https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#csukuangfj-sherpa-onnx-streaming-zipformer-en-2023-06-21-english)
+
+| | encoder-epoch-99-avg-1.onnx | encoder-epoch-99-avg-1.int8.onnx|
+|---|---|---|
+|Dynamic batch size| 338 MB| 180 MB|
+|Batch size fixed to 1| 264 MB | 107 MB |
+
+### [sherpa-onnx-streaming-zipformer-en-2023-02-21](https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#csukuangfj-sherpa-onnx-streaming-zipformer-en-2023-02-21-english)
+
+| | encoder-epoch-99-avg-1.onnx | encoder-epoch-99-avg-1.int8.onnx|
+|---|---|---|
+|Dynamic batch size| 279 MB| 122 MB|
+|Batch size fixed to 1| 264 MB | 107 MB |
+
+### [sherpa-onnx-streaming-zipformer-fr-2023-04-14](https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#shaojieli-sherpa-onnx-streaming-zipformer-fr-2023-04-14-french)
+
+| | encoder-epoch-29-avg-9-with-averaged-model.onnx | encoder-epoch-29-avg-9-with-averaged-model.int8.onnx|
+|---|---|---|
+|Dynamic batch size| 279 MB| 121 MB|
+|Batch size fixed to 1| 264 MB | 107 MB |
+
+### [sherpa-onnx-streaming-zipformer-small-bilingual-zh-en-2023-02-16](https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#sherpa-onnx-streaming-zipformer-small-bilingual-zh-en-2023-02-16-bilingual-chinese-english)
+
+| | encoder-epoch-99-avg-1.onnx | encoder-epoch-99-avg-1.int8.onnx|
+|---|---|---|
+|Dynamic batch size| 85 MB| 41 MB|
+|Batch size fixed to 1| 75 MB | 32 MB |
+
+### [sherpa-onnx-streaming-zipformer-zh-14M-2023-02-23](https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#csukuangfj-sherpa-onnx-streaming-zipformer-zh-14m-2023-02-23-chinese)
+
+| | encoder-epoch-99-avg-1.onnx | encoder-epoch-99-avg-1.int8.onnx|
+|---|---|---|
+|Dynamic batch size| 40 MB| 21 MB|
+|Batch size fixed to 1| 33 MB | 15 MB |
+
+### [sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01](https://k2-fsa.github.io/sherpa/onnx/kws/pretrained_models/index.html#sherpa-onnx-kws-zipformer-wenetspeech-3-3m-2024-01-01-chinese)
+
+| | encoder-epoch-12-avg-2-chunk-16-left-64.onnx | encoder-epoch-12-avg-2-chunk-16-left-64.int8.onnx|
+|---|---|---|
+|Dynamic batch size| 12 MB| 4.6 MB|
+|Batch size fixed to 1| 11 MB | 3.9 MB |
+
+### [sherpa-onnx-kws-zipformer-gigaspeech-3.3M-2024-01-01](https://k2-fsa.github.io/sherpa/onnx/kws/pretrained_models/index.html#sherpa-onnx-kws-zipformer-gigaspeech-3-3m-2024-01-01-english)
+
+| | encoder-epoch-12-avg-2-chunk-16-left-64.onnx | encoder-epoch-12-avg-2-chunk-16-left-64.int8.onnx|
+|---|---|---|
+|Dynamic batch size| 12 MB| 4.6 MB|
+|Batch size fixed to 1| 11 MB | 3.9 MB |

 #!/usr/bin/env python3
 import argparse
 
+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)
+
+
 def get_args():
     parser = argparse.ArgumentParser()
     parser.add_argument(
@@ -25,6 +39,9 @@ def get_args():
 def main():
     args = get_args()
     print(vars(args))
+    print(f"----------{args.input}----------")
+    show(args.input)
+    print("------------------------------")
 
     quantize_dynamic(
         model_input=args.input,

+#!/usr/bin/env python3
+
+import argparse
+from dataclasses import dataclass
+import jinja2
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--total",
+        type=int,
+        default=1,
+        help="Number of runners",
+    )
+    parser.add_argument(
+        "--index",
+        type=int,
+        default=0,
+        help="Index of the current runner",
+    )
+    return parser.parse_args()
+
+
+@dataclass
+class Model:
+    # We will download
+    # https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/{model_name}.tar.bz2
+    model_name: str
+
+    cmd: str
+
+
+def get_streaming_zipformer_transducer_models():
+    models = [
+        Model(
+            model_name="sherpa-onnx-streaming-zipformer-korean-2024-06-16",
+            cmd="""
+            ./run-impl.sh \
+              --input $src/encoder-epoch-99-avg-1.onnx \
+              --output1 $dst/encoder-epoch-99-avg-1.onnx \
+              --output2 $dst/encoder-epoch-99-avg-1.int8.onnx
+
+            cp -v $src/bpe.model $dst/ || true
+            cp -v $src/tokens.txt $dst/
+            cp -av $src/test_wavs $dst/
+            cp -v $src/decoder-epoch-99-avg-1.onnx $dst/
+            cp -v $src/joiner-epoch-99-avg-1.int8.onnx $dst/
+
+            cat > $dst/notes.md <<EOF
+# Introduction
+This model is converted from
+https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/$src.tar.bz2
+and it supports only batch size equal to 1.
+EOF
+            """,
+        ),
+        Model(
+            model_name="sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12",
+            cmd="""
+            ./run-impl.sh \
+              --input $src/encoder-epoch-20-avg-1-chunk-16-left-128.onnx \
+              --output1 $dst/encoder-epoch-20-avg-1-chunk-16-left-128.onnx \
+              --output2 $dst/encoder-epoch-20-avg-1-chunk-16-left-128.int8.onnx
+
+            cp -v $src/bpe.model $dst/ || true
+            cp -v $src/README.md $dst/
+            cp -v $src/tokens.txt $dst/
+            cp -av $src/test_wavs $dst/
+            cp -v $src/decoder-epoch-20-avg-1-chunk-16-left-128.onnx $dst/
+            cp -v $src/joiner-epoch-20-avg-1-chunk-16-left-128.int8.onnx $dst/
+
+            cat > $dst/notes.md <<EOF
+# Introduction
+This model is converted from
+https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/$src.tar.bz2
+and it supports only batch size equal to 1.
+EOF
+            """,
+        ),
+        Model(
+            model_name="icefall-asr-zipformer-streaming-wenetspeech-20230615",
+            cmd="""
+            ./run-impl.sh \
+              --input $src/exp/encoder-epoch-12-avg-4-chunk-16-left-128.onnx \
+              --output1 $dst/encoder-epoch-12-avg-4-chunk-16-left-128.onnx \
+              --output2 $dst/encoder-epoch-12-avg-4-chunk-16-left-128.int8.onnx
+
+            cp -fv $src/README.md $dst/
+            cp -v $src/data/lang_char/tokens.txt $dst/
+            cp -av $src/test_wavs $dst/
+            cp -v $src/exp/decoder-epoch-12-avg-4-chunk-16-left-128.onnx $dst/
+            cp -v $src/exp/joiner-epoch-12-avg-4-chunk-16-left-128.int8.onnx $dst/
+
+            cat > $dst/notes.md <<EOF
+# Introduction
+This model is converted from
+https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/$src.tar.bz2
+and it supports only batch size equal to 1.
+EOF
+            """,
+        ),
+        Model(
+            model_name="sherpa-onnx-streaming-zipformer-en-2023-06-26",
+            cmd="""
+            ./run-impl.sh \
+              --input $src/encoder-epoch-99-avg-1-chunk-16-left-128.onnx \
+              --output1 $dst/encoder-epoch-99-avg-1-chunk-16-left-128.onnx \
+              --output2 $dst/encoder-epoch-99-avg-1-chunk-16-left-128.int8.onnx
+
+            cp -v $src/bpe.model $dst/ || true
+            cp -v $src/README.md $dst/
+            cp -v $src/tokens.txt $dst/
+            cp -av $src/test_wavs $dst/
+            cp -v $src/decoder-epoch-99-avg-1-chunk-16-left-128.onnx $dst/
+            cp -v $src/joiner-epoch-99-avg-1-chunk-16-left-128.int8.onnx $dst/
+
+            cat > $dst/notes.md <<EOF
+# Introduction
+This model is converted from
+https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/$src.tar.bz2
+and it supports only batch size equal to 1.
+EOF
+              """,
+        ),
+        Model(
+            model_name="sherpa-onnx-streaming-zipformer-en-2023-06-21",
+            cmd="""
+            ./run-impl.sh \
+              --input $src/encoder-epoch-99-avg-1.onnx \
+              --output1 $dst/encoder-epoch-99-avg-1.onnx \
+              --output2 $dst/encoder-epoch-99-avg-1.int8.onnx
+
+            cp -fv $src/README.md $dst/
+            cp -v $src/tokens.txt $dst/
+            cp -av $src/test_wavs $dst/
+            cp -v $src/decoder-epoch-99-avg-1.onnx $dst/
+            cp -v $src/joiner-epoch-99-avg-1.int8.onnx $dst/
+
+            cat > $dst/notes.md <<EOF
+# Introduction
+This model is converted from
+https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/$src.tar.bz2
+and it supports only batch size equal to 1.
+EOF
+                """,
+        ),
+        Model(
+            model_name="sherpa-onnx-streaming-zipformer-en-2023-02-21",
+            cmd="""
+            ./run-impl.sh \
+              --input $src/encoder-epoch-99-avg-1.onnx \
+              --output1 $dst/encoder-epoch-99-avg-1.onnx \
+              --output2 $dst/encoder-epoch-99-avg-1.int8.onnx
+
+            cp -v $src/bpe.model $dst/ || true
+            cp -v $src/README.md $dst/ || true
+            cp -v $src/tokens.txt $dst/
+            cp -av $src/test_wavs $dst/
+            cp -v $src/decoder-epoch-99-avg-1.onnx $dst/
+            cp -v $src/joiner-epoch-99-avg-1.int8.onnx $dst/
+
+            cat > $dst/notes.md <<EOF
+# Introduction
+This model is converted from
+https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/$src.tar.bz2
+and it supports only batch size equal to 1.
+EOF
+              """,
+        ),
+        Model(
+            model_name="sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20",
+            cmd="""
+            ./run-impl.sh \
+              --input $src/encoder-epoch-99-avg-1.onnx \
+              --output1 $dst/encoder-epoch-99-avg-1.onnx \
+              --output2 $dst/encoder-epoch-99-avg-1.int8.onnx
+
+            cp -v $src/README.md $dst/
+            cp -v $src/tokens.txt $dst/
+            cp -av $src/test_wavs $dst/
+            cp -v $src/decoder-epoch-99-avg-1.onnx $dst/
+            cp -v $src/joiner-epoch-99-avg-1.int8.onnx $dst/
+
+            cat > $dst/notes.md <<EOF
+# Introduction
+This model is converted from
+https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/$src.tar.bz2
+and it supports only batch size equal to 1.
+EOF
+            """,
+        ),
+        Model(
+            model_name="sherpa-onnx-streaming-zipformer-fr-2023-04-14",
+            cmd="""
+            ./run-impl.sh \
+              --input $src/encoder-epoch-29-avg-9-with-averaged-model.onnx \
+              --output1 $dst/encoder-epoch-29-avg-9-with-averaged-model.onnx \
+              --output2 $dst/encoder-epoch-29-avg-9-with-averaged-model.int8.onnx
+
+            cp -v $src/bpe.model $dst/ || true
+            cp -v $src/README.md $dst/ || true
+            cp -v $src/tokens.txt $dst/
+            cp -av $src/test_wavs $dst/
+            cp -v $src/decoder-epoch-29-avg-9-with-averaged-model.onnx $dst/
+            cp -v $src/joiner-epoch-29-avg-9-with-averaged-model.int8.onnx $dst/
+
+            cat > $dst/notes.md <<EOF
+# Introduction
+This model is converted from
+https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/$src.tar.bz2
+and it supports only batch size equal to 1.
+EOF
+              """,
+        ),
+        Model(
+            model_name="sherpa-onnx-streaming-zipformer-small-bilingual-zh-en-2023-02-16",
+            cmd="""
+            ./run-impl.sh \
+              --input $src/encoder-epoch-99-avg-1.onnx \
+              --output1 $dst/encoder-epoch-99-avg-1.onnx \
+              --output2 $dst/encoder-epoch-99-avg-1.int8.onnx
+
+            mkdir $dst/{64,96}
+
+            ./run-impl.sh \
+              --input $src/64/encoder-epoch-99-avg-1.onnx \
+              --output1 $dst/64/encoder-epoch-99-avg-1.onnx \
+              --output2 $dst/64/encoder-epoch-99-avg-1.int8.onnx
+
+            ./run-impl.sh \
+              --input $src/96/encoder-epoch-99-avg-1.onnx \
+              --output1 $dst/96/encoder-epoch-99-avg-1.onnx \
+              --output2 $dst/96/encoder-epoch-99-avg-1.int8.onnx
+
+            cp -v $src/bpe.model $dst/ || true
+            cp -v $src/README.md $dst/ || true
+            cp -av $src/test_wavs $dst/
+
+            cp -v $src/tokens.txt $dst/
+            cp -v $src/decoder-epoch-99-avg-1.onnx $dst/
+            cp -v $src/joiner-epoch-99-avg-1.int8.onnx $dst/
+
+            cp -v $src/tokens.txt $dst/64/
+            cp -v $src/64/decoder-epoch-99-avg-1.onnx $dst/64/
+            cp -v $src/64/joiner-epoch-99-avg-1.int8.onnx $dst/64/
+
+            cp -v $src/tokens.txt $dst/96/
+            cp -v $src/96/decoder-epoch-99-avg-1.onnx $dst/96/
+            cp -v $src/96/joiner-epoch-99-avg-1.int8.onnx $dst/96/
+
+            cat > $dst/notes.md <<EOF
+# Introduction
+This model is converted from
+https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/$src.tar.bz2
+and it supports only batch size equal to 1.
+EOF
+              """,
+        ),
+        Model(
+            model_name="sherpa-onnx-streaming-zipformer-zh-14M-2023-02-23",
+            cmd="""
+            ./run-impl.sh \
+              --input $src/encoder-epoch-99-avg-1.onnx \
+              --output1 $dst/encoder-epoch-99-avg-1.onnx \
+              --output2 $dst/encoder-epoch-99-avg-1.int8.onnx
+
+            cp -v $src/bpe.model $dst/ || true
+            cp -v $src/README.md $dst/ || true
+            cp -v $src/tokens.txt $dst/
+            cp -av $src/test_wavs $dst/
+            cp -v $src/decoder-epoch-99-avg-1.onnx $dst/
+            cp -v $src/joiner-epoch-99-avg-1.int8.onnx $dst/
+
+            cat > $dst/notes.md <<EOF
+# Introduction
+This model is converted from
+https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/$src.tar.bz2
+and it supports only batch size equal to 1.
+EOF
+            """,
+        ),
+        Model(
+            model_name="sherpa-onnx-streaming-zipformer-en-20M-2023-02-17",
+            cmd="""
+            ./run-impl.sh \
+              --input $src/encoder-epoch-99-avg-1.onnx \
+              --output1 $dst/encoder-epoch-99-avg-1.onnx \
+              --output2 $dst/encoder-epoch-99-avg-1.int8.onnx
+
+            cp -v $src/bpe.model $dst/ || true
+            cp -v $src/README.md $dst/ || true
+            cp -v $src/tokens.txt $dst/
+            cp -av $src/test_wavs $dst/
+            cp -v $src/decoder-epoch-99-avg-1.onnx $dst/
+            cp -v $src/joiner-epoch-99-avg-1.int8.onnx $dst/
+
+            cat > $dst/notes.md <<EOF
+# Introduction
+This model is converted from
+https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/$src.tar.bz2
+and it supports only batch size equal to 1.
+EOF
+            """,
+        ),
+    ]
+
+    return models
+
+
+def get_models():
+    return get_streaming_zipformer_transducer_models()
+
+
+def main():
+    args = get_args()
+    index = args.index
+    total = args.total
+    assert 0 <= index < total, (index, total)
+
+    all_model_list = get_models()
+
+    num_models = len(all_model_list)
+
+    num_per_runner = num_models // total
+    if num_per_runner <= 0:
+        raise ValueError(f"num_models: {num_models}, num_runners: {total}")
+
+    start = index * num_per_runner
+    end = start + num_per_runner
+
+    remaining = num_models - args.total * num_per_runner
+
+    print(f"{index}/{total}: {start}-{end}/{num_models}")
+
+    d = dict()
+    d["model_list"] = all_model_list[start:end]
+    if index < remaining:
+        s = args.total * num_per_runner + index
+        d["model_list"].append(all_model_list[s])
+        print(f"{s}/{num_models}")
+
+    filename_list = [
+        "./run2.sh",
+    ]
+    for filename in filename_list:
+        environment = jinja2.Environment()
+        with open(f"{filename}.in") as f:
+            s = f.read()
+        template = environment.from_string(s)
+
+        s = template.render(**d)
+        with open(filename, "w") as f:
+            print(s, file=f)
+
+
+if __name__ == "__main__":
+    main()

+#!/usr/bin/env python3
+
+import argparse
+from dataclasses import dataclass
+import jinja2
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--total",
+        type=int,
+        default=1,
+        help="Number of runners",
+    )
+    parser.add_argument(
+        "--index",
+        type=int,
+        default=0,
+        help="Index of the current runner",
+    )
+    return parser.parse_args()
+
+
+@dataclass
+class Model:
+    # We will download
+    # https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/{model_name}.tar.bz2
+    model_name: str
+
+    cmd: str
+
+
+def get_kws_models():
+    models = [
+        Model(
+            model_name="sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01",
+            cmd="""
+            ./run-impl.sh \
+              --input $src/encoder-epoch-12-avg-2-chunk-16-left-64.onnx \
+              --output1 $dst/encoder-epoch-12-avg-2-chunk-16-left-64.onnx \
+              --output2 $dst/encoder-epoch-12-avg-2-chunk-16-left-64.int8.onnx
+
+            cp -v $src/README.md $dst/
+            cp -v $src/*.txt $dst/
+            cp -av $src/test_wavs $dst/
+            cp -v $src/decoder-epoch-12-avg-2-chunk-16-left-64.onnx $dst/
+            cp -v $src/joiner-epoch-12-avg-2-chunk-16-left-64.int8.onnx $dst/
+
+            cat > $dst/notes.md <<EOF
+# Introduction
+This model is converted from
+https://github.com/k2-fsa/sherpa-onnx/releases/download/kws-models/$src.tar.bz2
+and it supports only batch size equal to 1.
+EOF
+                  """,
+        ),
+        Model(
+            model_name="sherpa-onnx-kws-zipformer-gigaspeech-3.3M-2024-01-01",
+            cmd="""
+            ./run-impl.sh \
+              --input $src/encoder-epoch-12-avg-2-chunk-16-left-64.onnx \
+              --output1 $dst/encoder-epoch-12-avg-2-chunk-16-left-64.onnx \
+              --output2 $dst/encoder-epoch-12-avg-2-chunk-16-left-64.int8.onnx
+
+            cp -v $src/bpe.model $dst/
+            cp -v $src/README.md $dst/
+            cp -v $src/*.txt $dst/
+            cp -av $src/test_wavs $dst/
+            cp -v $src/decoder-epoch-12-avg-2-chunk-16-left-64.onnx $dst/
+            cp -v $src/joiner-epoch-12-avg-2-chunk-16-left-64.int8.onnx $dst/
+
+            cat > $dst/notes.md <<EOF
+# Introduction
+This model is converted from
+https://github.com/k2-fsa/sherpa-onnx/releases/download/kws-models/$src.tar.bz2
+and it supports only batch size equal to 1.
+EOF
+                  """,
+        ),
+    ]
+    return models
+
+
+def get_models():
+    return get_kws_models()
+
+
+def main():
+    args = get_args()
+    index = args.index
+    total = args.total
+    assert 0 <= index < total, (index, total)
+
+    all_model_list = get_models()
+
+    num_models = len(all_model_list)
+
+    num_per_runner = num_models // total
+    if num_per_runner <= 0:
+        raise ValueError(f"num_models: {num_models}, num_runners: {total}")
+
+    start = index * num_per_runner
+    end = start + num_per_runner
+
+    remaining = num_models - args.total * num_per_runner
+
+    print(f"{index}/{total}: {start}-{end}/{num_models}")
+
+    d = dict()
+    d["model_list"] = all_model_list[start:end]
+    if index < remaining:
+        s = args.total * num_per_runner + index
+        d["model_list"].append(all_model_list[s])
+        print(f"{s}/{num_models}")
+
+    filename_list = [
+        "./run2.sh",
+    ]
+    for filename in filename_list:
+        environment = jinja2.Environment()
+        with open(f"{filename}.in") as f:
+            s = f.read()
+        template = environment.from_string(s)
+
+        s = template.render(**d)
+        with open(filename, "w") as f:
+            print(s, file=f)
+
+
+if __name__ == "__main__":
+    main()

@@ -11,6 +11,7 @@ input=
 output1=
 output2=
 batch_dim=N
+
 source ./parse_options.sh
 
 if [ -z $input ]; then
@@ -35,6 +36,7 @@ echo "output2: $output2"
 
 python3 -m onnxruntime.tools.make_dynamic_shape_fixed --dim_param $batch_dim --dim_value 1 $input tmp.fixed.onnx
 python3 -m onnxruntime.quantization.preprocess --input tmp.fixed.onnx --output $output1
+
 python3 ./dynamic_quantization.py --input $output1 --output $output2
 
 ls -lh $input tmp.fixed.onnx $output1 $output2

+#!/usr/bin/env bash
+set -e
+
+{% for model in model_list %}
+
+src={{ model.model_name }}
+
+if [[ $src == *kws* ]]; then
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/kws-models/$src.tar.bz2
+
+else
+  curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/$src.tar.bz2
+fi
+
+tar xvf $src.tar.bz2
+rm $src.tar.bz2
+
+dst=$src-mobile
+
+mkdir -p $dst
+
+{{ model.cmd }}
+
+echo "---$src---"
+ls -lh $src
+echo "---$dst---"
+ls -lh $dst
+rm -rf $src
+
+tar cjfv $dst.tar.bz2 $dst
+
+if [[ $src == *kws* ]]; then
+  mkdir -p ../../kws
+  mv *.tar.bz2 ../../kws/
+else
+  mv *.tar.bz2 ../../
+fi
+rm -rf $dst
+
+{% endfor %}