Rename models to follow icefall convention (#71)

* Rename to follow icefall convention

* Fix github CI and docs

* Modify name in docs and README

* Rename wenet ci

.github/workflows/run-streaming-conformer-test.yaml

@@ -118,7 +118,7 @@ jobs:
           export PYTHONPATH=~/tmp/kaldifeat/kaldifeat/python:$PYTHONPATH
           export PYTHONPATH=~/tmp/kaldifeat/build/lib:$PYTHONPATH
 
-          ./sherpa/bin/streaming_conformer_rnnt/streaming_server.py \
+          ./sherpa/bin/streaming_pruned_transducer_statelessX/streaming_server.py \
             --port 6006 \
             --max-batch-size 50 \
             --max-wait-ms 5 \
@@ -133,7 +133,7 @@ jobs:
       - name: Start client
         shell: bash
         run: |
-          ./sherpa/bin/streaming_conformer_rnnt/streaming_client.py \
+          ./sherpa/bin/streaming_pruned_transducer_statelessX/streaming_client.py \
             --server-addr localhost \
             --server-port 6006 \
             ./icefall-asr-librispeech-pruned-stateless-streaming-conformer-rnnt4-2022-06-10/test_wavs/1221-135766-0002.wav

.github/workflows/run-streaming-conv-emformer-test.yaml

@@ -118,7 +118,7 @@ jobs:
           export PYTHONPATH=~/tmp/kaldifeat/kaldifeat/python:$PYTHONPATH
           export PYTHONPATH=~/tmp/kaldifeat/build/lib:$PYTHONPATH
 
-          ./sherpa/bin/conv_emformer_transducer_stateless/streaming_server.py \
+          ./sherpa/bin/conv_emformer_transducer_stateless2/streaming_server.py \
             --port 6006 \
             --max-batch-size 50 \
             --max-wait-ms 5 \
@@ -133,7 +133,7 @@ jobs:
       - name: Start client
         shell: bash
         run: |
-          ./sherpa/bin/conv_emformer_transducer_stateless/streaming_client.py \
+          ./sherpa/bin/conv_emformer_transducer_stateless2/streaming_client.py \
             --server-addr localhost \
             --server-port 6006 \
             ./icefall-asr-librispeech-conv-emformer-transducer-stateless2-2022-07-05/test_wavs/1221-135766-0002.wav

.github/workflows/run-test-aishell.yaml

@@ -119,7 +119,7 @@ jobs:
           export PYTHONPATH=~/tmp/kaldifeat/kaldifeat/python:$PYTHONPATH
           export PYTHONPATH=~/tmp/kaldifeat/build/lib:$PYTHONPATH
 
-          sherpa/bin/conformer_rnnt/offline_server.py \
+          sherpa/bin/pruned_transducer_statelessX/offline_server.py \
             --port 6006 \
             --num-device 0 \
             --max-batch-size 10 \
@@ -135,7 +135,7 @@ jobs:
       - name: Start client
         shell: bash
         run: |
-          sherpa/bin/conformer_rnnt/offline_client.py \
+          sherpa/bin/pruned_transducer_statelessX/offline_client.py \
             --server-addr localhost \
             --server-port 6006 \
             ./icefall-aishell-pruned-transducer-stateless3-2022-06-20/test_wavs/BAC009S0764W0121.wav \

.github/workflows/run-test-windows-cpu.yaml

@@ -84,7 +84,7 @@ jobs:
           export PYTHONPATH=~/tmp/kaldifeat/kaldifeat/python:$PYTHONPATH
           export PYTHONPATH=~/tmp/kaldifeat/build/lib:$PYTHONPATH
 
-          sherpa/bin/conformer_rnnt/offline_server.py \
+          sherpa/bin/pruned_transducer_statelessX/offline_server.py \
             --port 6006 \
             --num-device 0 \
             --max-batch-size 10 \
@@ -99,7 +99,7 @@ jobs:
       - name: Start client
         shell: bash
         run: |
-          sherpa/bin/conformer_rnnt/offline_client.py \
+          sherpa/bin/pruned_transducer_statelessX/offline_client.py \
             --server-addr localhost \
             --server-port 6006 \
             icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/test_wavs/1089-134686-0001.wav \

.github/workflows/run-test.yaml

@@ -119,7 +119,7 @@ jobs:
           export PYTHONPATH=~/tmp/kaldifeat/kaldifeat/python:$PYTHONPATH
           export PYTHONPATH=~/tmp/kaldifeat/build/lib:$PYTHONPATH
 
-          sherpa/bin/conformer_rnnt/offline_server.py \
+          sherpa/bin/pruned_transducer_statelessX/offline_server.py \
             --port 6006 \
             --num-device 0 \
             --max-batch-size 10 \
@@ -134,7 +134,7 @@ jobs:
       - name: Start client
         shell: bash
         run: |
-          sherpa/bin/conformer_rnnt/offline_client.py \
+          sherpa/bin/pruned_transducer_statelessX/offline_client.py \
             --server-addr localhost \
             --server-port 6006 \
             icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/test_wavs/1089-134686-0001.wav \

.github/workflows/run-wenetspeech-streaming-conformer-rnnt-test.yaml

@@ -107,7 +107,7 @@ jobs:
         run: |
           export PYTHONPATH=~/tmp/kaldifeat/kaldifeat/python:$PYTHONPATH
           export PYTHONPATH=~/tmp/kaldifeat/build/lib:$PYTHONPATH
-          ./sherpa/bin/streaming_conformer_rnnt/streaming_server.py \
+          ./sherpa/bin/streaming_pruned_transducer_statelessX/streaming_server.py \
             --port 6006 \
             --max-batch-size 50 \
             --max-wait-ms 5 \
@@ -120,7 +120,7 @@ jobs:
       - name: Start client
         shell: bash
         run: |
-          ./sherpa/bin/streaming_conformer_rnnt/streaming_client.py \
+          ./sherpa/bin/streaming_pruned_transducer_statelessX/streaming_client.py \
             --server-addr localhost \
             --server-port 6006 \
             ./icefall_asr_wenetspeech_pruned_transducer_stateless5_streaming/test_wavs/DEV_T0000000001.wav

README.md

@@ -184,7 +184,7 @@ following command:
 # If you provide a bpe.model, e.g., for LibriSpeech,
 # you can use the following command:
 #
-sherpa/bin/conformer_rnnt/offline_server.py \
+sherpa/bin/pruned_transducer_statelessX/offline_server.py \
   --port 6006 \
   --num-device 1 \
   --max-batch-size 10 \
@@ -200,7 +200,7 @@ sherpa/bin/conformer_rnnt/offline_server.py \
 # If you provide a tokens.txt, e.g., for aishell,
 # you can use the following command:
 #
-sherpa/bin/conformer_rnnt/offline_server.py \
+sherpa/bin/pruned_transducer_statelessX/offline_server.py \
   --port 6006 \
   --num-device 1 \
   --max-batch-size 10 \
@@ -212,7 +212,7 @@ sherpa/bin/conformer_rnnt/offline_server.py \
   --token-filename ./path/to/data/lang_char/tokens.txt
 ```
 
-You can use `./sherpa/bin/conformer_rnnt/offline_server.py --help` to view the help message.
+You can use `./sherpa/bin/pruned_transducer_statelessX/offline_server.py --help` to view the help message.
 
 **HINT**: If you don't have GPU, please set `--num-device` to `0`.
 
@@ -235,7 +235,7 @@ The following shows how to use the above pretrained models to start the server.
 git lfs install
 git clone https://huggingface.co/csukuangfj/icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13
 
-sherpa/bin/conformer_rnnt/offline_server.py \
+sherpa/bin/pruned_transducer_statelessX/offline_server.py \
   --port 6006 \
   --num-device 1 \
   --max-batch-size 10 \
@@ -253,7 +253,7 @@ sherpa/bin/conformer_rnnt/offline_server.py \
 git lfs install
 git clone https://huggingface.co/csukuangfj/icefall-aishell-pruned-transducer-stateless3-2022-06-20
 
-sherpa/bin/conformer_rnnt/offline_server.py \
+sherpa/bin/pruned_transducer_statelessX/offline_server.py \
   --port 6006 \
   --num-device 1 \
   --max-batch-size 10 \
@@ -269,21 +269,21 @@ sherpa/bin/conformer_rnnt/offline_server.py \
 After starting the server, you can use the following command to start the client:
 
 ```bash
-./sherpa/bin/conformer_rnnt/offline_client.py \
+./sherpa/bin/pruned_transducer_statelessX/offline_client.py \
     --server-addr localhost \
     --server-port 6006 \
     /path/to/foo.wav \
     /path/to/bar.wav
 ```
 
-You can use `./sherpa/bin/conformer_rnnt/offline_client.py --help` to view the usage message.
+You can use `./sherpa/bin/pruned_transducer_statelessX/offline_client.py --help` to view the usage message.
 
 The following shows how to use the client to send some test waves to the server
 for recognition.
 
 ```bash
 # If you use the pretrained model from the LibriSpeech dataset
-sherpa/bin/conformer_rnnt/offline_client.py \
+sherpa/bin/pruned_transducer_statelessX/offline_client.py \
   --server-addr localhost \
   --server-port 6006 \
   icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13//test_wavs/1089-134686-0001.wav \
@@ -293,7 +293,7 @@ sherpa/bin/conformer_rnnt/offline_client.py \
 
 ```bash
 # If you use the pretrained model from the aishell dataset
-sherpa/bin/conformer_rnnt/offline_client.py \
+sherpa/bin/pruned_transducer_statelessX/offline_client.py \
   --server-addr localhost \
   --server-port 6006 \
   ./icefall-aishell-pruned-transducer-stateless3-2022-06-20/test_wavs/BAC009S0764W0121.wav \
@@ -303,7 +303,7 @@ sherpa/bin/conformer_rnnt/offline_client.py \
 
 #### RTF test
 
-We provide a demo [./sherpa/bin/conformer_rnnt/decode_manifest.py](./sherpa/bin/conformer_rnnt/decode_manifest.py)
+We provide a demo [./sherpa/bin/pruned_transducer_statelessX/decode_manifest.py](./sherpa/bin/pruned_transducer_statelessX/decode_manifest.py)
 to decode the `test-clean` dataset from the LibriSpeech corpus.
 
 It creates 50 connections to the server using websockets and sends audio files

docs/source/offline_asr/conformer/aishell.rst

@@ -80,7 +80,7 @@ Start the server
 ----------------
 
 The entry point of the server is
-`sherpa/bin/conformer_rnnt/offline_server.py <https://github.com/k2-fsa/sherpa/blob/master/sherpa/bin/conformer_rnnt/offline_server.py>`_.
+`sherpa/bin/pruned_transducer_statelessX/offline_server.py <https://github.com/k2-fsa/sherpa/blob/master/sherpa/bin/pruned_transducer_statelessX/offline_server.py>`_.
 
 One thing worth mentioning is that the entry point is a Python script.
 In `sherpa`_, the server is implemented using `asyncio`_, where **IO-bound**
@@ -100,12 +100,12 @@ To view the usage information of the server, you can use:
 
 .. code-block:: bash
 
-   $ ./sherpa/bin/conformer_rnnt/offline_server.py --help
+   $ ./sherpa/bin/pruned_transducer_statelessX/offline_server.py --help
 
 which gives the following output:
 
 .. literalinclude:: ./code/offline-server-help.txt
-   :caption: Output of ``./sherpa/bin/conformer_rnnt/offline_server.py --help``
+   :caption: Output of ``./sherpa/bin/pruned_transducer_statelessX/offline_server.py --help``
 
 The following shows an example about how to use the above pre-trained model
 to start the server:
@@ -128,16 +128,16 @@ Start the client
 ----------------
 
 We also provide a Python script
-`sherpa/bin/conformer_rnnt/offline_client.py <https://github.com/k2-fsa/sherpa/blob/master/sherpa/bin/conformer_rnnt/offline_client.py>`_ for the client.
+`sherpa/bin/pruned_transducer_statelessX/offline_client.py <https://github.com/k2-fsa/sherpa/blob/master/sherpa/bin/pruned_transducer_statelessX/offline_client.py>`_ for the client.
 
 .. code-block:: bash
 
-   ./sherpa/bin/conformer_rnnt/offline_client.py --help
+   ./sherpa/bin/pruned_transducer_statelessX/offline_client.py --help
 
 shows the following help information:
 
 .. literalinclude:: ./code/offline-client-help.txt
-   :caption: Output of ``./sherpa/bin/conformer_rnnt/offline_client.py --help``
+   :caption: Output of ``./sherpa/bin/pruned_transducer_statelessX/offline_client.py --help``
 
 We provide some test waves in the git repo you just cloned. The following command
 shows you how to start the client:

docs/source/offline_asr/conformer/code/start-the-client-librispeech.sh

@@ -2,7 +2,7 @@
 
 export CUDA_VISIBLE_DEVICES=0
 
-sherpa/bin/conformer_rnnt/offline_client.py \
+sherpa/bin/pruned_transducer_statelessX/offline_client.py \
   --server-addr localhost \
   --server-port 6010 \
   ./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/test_wavs/1089-134686-0001.wav \

docs/source/offline_asr/conformer/code/start-the-client.sh

@@ -1,6 +1,6 @@
 #!/usr/bin/env bash
 
-sherpa/bin/conformer_rnnt/offline_client.py \
+sherpa/bin/pruned_transducer_statelessX/offline_client.py \
   --server-addr localhost \
   --server-port 6010 \
   ./icefall-aishell-pruned-transducer-stateless3-2022-06-20/test_wavs/BAC009S0764W0121.wav \

docs/source/offline_asr/conformer/code/start-the-server-librispeech.sh

@@ -5,7 +5,7 @@ export CUDA_VISIBLE_DEVICES=0
 nn_model_filename=./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/cpu_jit-torch-1.6.0.pt
 bpe_model=./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/data/lang_bpe_500/bpe.model
 
-sherpa/bin/conformer_rnnt/offline_server.py \
+sherpa/bin/pruned_transducer_statelessX/offline_server.py \
   --port 6010 \
   --num-device 1 \
   --max-batch-size 10 \

docs/source/offline_asr/conformer/code/start-the-server.sh

@@ -5,7 +5,7 @@ export CUDA_VISIBLE_DEVICES=1
 nn_model_filename=./icefall-aishell-pruned-transducer-stateless3-2022-06-20/exp/cpu_jit-epoch-29-avg-5-torch-1.6.0.pt
 token_filename=./icefall-aishell-pruned-transducer-stateless3-2022-06-20/data/lang_char/tokens.txt
 
-sherpa/bin/conformer_rnnt/offline_server.py \
+sherpa/bin/pruned_transducer_statelessX/offline_server.py \
   --port 6010 \
   --num-device 1 \
   --max-batch-size 10 \

docs/source/offline_asr/conformer/librispeech.rst

@@ -81,7 +81,7 @@ Start the server
 ----------------
 
 The entry point of the server is
-`sherpa/bin/conformer_rnnt/offline_server.py <https://github.com/k2-fsa/sherpa/blob/master/sherpa/bin/conformer_rnnt/offline_server.py>`_.
+`sherpa/bin/pruned_transducer_statelessX/offline_server.py <https://github.com/k2-fsa/sherpa/blob/master/sherpa/bin/pruned_transducer_statelessX/offline_server.py>`_.
 
 One thing worth mentioning is that the entry point is a Python script.
 In `sherpa`_, the server is implemented using `asyncio`_, where **IO-bound**
@@ -101,12 +101,12 @@ To view the usage information of the server, you can use:
 
 .. code-block:: bash
 
-   $ ./sherpa/bin/conformer_rnnt/offline_server.py --help
+   $ ./sherpa/bin/pruned_transducer_statelessX/offline_server.py --help
 
 which gives the following output:
 
 .. literalinclude:: ./code/offline-server-help.txt
-   :caption: Output of ``./sherpa/bin/conformer_rnnt/offline_server.py --help``
+   :caption: Output of ``./sherpa/bin/pruned_transducer_statelessX/offline_server.py --help``
 
 The following shows an example about how to use the above pre-trained model
 to start the server:
@@ -129,16 +129,16 @@ Start the client
 ----------------
 
 We also provide a Python script
-`sherpa/bin/conformer_rnnt/offline_client.py <https://github.com/k2-fsa/sherpa/blob/master/sherpa/bin/conformer_rnnt/offline_client.py>`_ for the client.
+`sherpa/bin/pruned_transducer_statelessX/offline_client.py <https://github.com/k2-fsa/sherpa/blob/master/sherpa/bin/pruned_transducer_statelessX/offline_client.py>`_ for the client.
 
 .. code-block:: bash
 
-   ./sherpa/bin/conformer_rnnt/offline_client.py --help
+   ./sherpa/bin/pruned_transducer_statelessX/offline_client.py --help
 
 shows the following help information:
 
 .. literalinclude:: ./code/offline-client-help.txt
-   :caption: Output of ``./sherpa/bin/conformer_rnnt/offline_client.py --help``
+   :caption: Output of ``./sherpa/bin/pruned_transducer_statelessX/offline_client.py --help``
 
 We provide some test waves in the git repo you just cloned. The following command
 shows you how to start the client:

docs/source/streaming_asr/conv_emformer/server.rst

@@ -19,7 +19,7 @@ Usage
 .. code-block::
 
    cd /path/to/sherpa
-   ./sherpa/bin/conv_emformer_transducer_stateless/streaming_server.py --help
+   ./sherpa/bin/conv_emformer_transducer_stateless2/streaming_server.py --help
 
 shows the usage message.
 
@@ -51,7 +51,7 @@ The following shows you how to start the server with the above pretrained model.
     git lfs install
     git clone https://huggingface.co/Zengwei/icefall-asr-librispeech-conv-emformer-transducer-stateless2-2022-07-05
 
-    ./sherpa/bin/conv_emformer_transducer_stateless/streaming_server.py \
+    ./sherpa/bin/conv_emformer_transducer_stateless2/streaming_server.py \
       --port 6007 \
       --max-batch-size 50 \
       --max-wait-ms 5 \

sherpa/bin/README.md

@@ -8,9 +8,9 @@ where `X>=2`.
 
 | Filename | Description |
 |----------|-------------|
-| [conformer_rnnt/offline_server.py](./conformer_rnnt/offline_server.py) | The server for offline ASR |
-| [conformer_rnnt/offline_client.py](./conformer/offline_client.py) | The client for offline ASR |
-| [conformer_rnnt/decode_manifest.py](./conformer_rnnt/decode_manifest.py) | Demo for computing RTF and WER|
+| [pruned_transducer_statelessX/offline_server.py](./pruned_transducer_statelessX/offline_server.py) | The server for offline ASR |
+| [pruned_transducer_statelessX/offline_client.py](./pruned_transducer_statelessX/offline_client.py) | The client for offline ASR |
+| [pruned_transducer_statelessX/decode_manifest.py](./pruned_transducer_statelessX/decode_manifest.py) | Demo for computing RTF and WER|
 
 If you want to test the offline server without training your own model, you
 can download pretrained models on the LibriSpeech corpus by visiting
@@ -42,9 +42,9 @@ where `X>=2`. And the model is trained for streaming recognition.
 
 | Filename | Description |
 |----------|-------------|
-| [streaming_conformer_rnnt/streaming_conformer_rnnt/streaming_server.py](./streaming_conformer_rnnt/streaming_server.py) | The server for streaming ASR |
-| [streaming_conformer_rnnt/streaming_client.py](./streaming_conformer_rnnt/streaming_client.py) | The client for streaming ASR |
-| [streaming_conformer_rnnt/decode.py](./streaming_conformer_rnnt/decode.py) | Utilities for streaming ASR|
+| [streaming_pruned_transducer_statelessX/streaming_server.py](./streaming_pruned_transducer_statelessX/streaming_server.py) | The server for streaming ASR |
+| [streaming_pruned_transducer_statelessX/streaming_client.py](./streaming_pruned_transducer_statelessX/streaming_client.py) | The client for streaming ASR |
+| [streaming_pruned_transducer_statelessX/decode.py](./streaming_pruned_transducer_statelessX/decode.py) | Utilities for streaming ASR|
 
 You can use the pretrained model from
 <https://huggingface.co/pkufool/icefall-asr-librispeech-pruned-stateless-streaming-conformer-rnnt4-2022-06-10>

sherpa/bin/conformer_rnnt/offline_asr.py → sherpa/bin/pruned_transducer_statelessX/offline_asr.py

@@ -57,7 +57,7 @@
     wav2=./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/test_wavs/1221-135766-0001.wav
     wav3=./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/test_wavs/1221-135766-0002.wav
 
-    sherpa/bin/conformer_rnnt/offline_asr.py \
+    sherpa/bin/pruned_transducer_statelessX/offline_asr.py \
       --nn-model-filename $nn_model_filename \
       --bpe-model $bpe_model \
       $wav1 \
@@ -77,7 +77,7 @@
     wav2=./icefall-aishell-pruned-transducer-stateless3-2022-06-20/test_wavs/BAC009S0764W0122.wav
     wav3=./icefall-aishell-pruned-transducer-stateless3-2022-06-20/test_wavs/BAC009S0764W0123.wav
 
-    sherpa/bin/conformer_rnnt/offline_asr.py \
+    sherpa/bin/pruned_transducer_statelessX/offline_asr.py \
       --nn-model-filename $nn_model_filename \
       --token-filename $token_filename \
       $wav1 \