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Provide models for mobile-only platforms by fixing batch size to 1 (#…
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csukuangfj committed Aug 22, 2024
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52 changes: 52 additions & 0 deletions .github/workflows/mobile-asr-models.yaml
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name: mobile-asr-models

on:
push:
branches:
- asr-mobile

workflow_dispatch:


concurrency:
group: mobile-asr-models-${{ github.ref }}
cancel-in-progress: true

jobs:
mobile-asr-models:
if: github.repository_owner == 'k2-fsa' || github.repository_owner == 'csukuangfj' || github.repository_owner == 'csu-fangjun'
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
os: [ubuntu-latest]
python-version: ["3.8"]

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
- 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: ./*.tar.bz2
overwrite: true
repo_name: k2-fsa/sherpa-onnx
repo_token: ${{ secrets.UPLOAD_GH_SHERPA_ONNX_TOKEN }}
tag: asr-models
18 changes: 18 additions & 0 deletions scripts/mobile-asr-models/README.md
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# Introduction

This folder contains scripts to convert ASR models for mobile platforms
supporting only batch size equal to 1.

The advantage of fixing the batch size to 1 is that it provides more
opportunities for model optimization and quantization.

To give you a concrete example, for the following model
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#csukuangfj-sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20-bilingual-chinese-english

| | encoder-epoch-99-avg-1.onnx | encoder-epoch-99-avg-1.int8.onnx|
|---|---|---|
|Dynamic batch size| 315 MB| 174 MB|
|Batch size fixed to 1| 242 MB | 100 MB |

The following [colab notebook](https://colab.research.google.com/drive/1RsVZbsxbPjazeGrNNbZNjXCYbEG2F2DU?usp=sharing)
provides examples to use the above two models.
38 changes: 38 additions & 0 deletions scripts/mobile-asr-models/dynamic_quantization.py
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#!/usr/bin/env python3
import argparse

from onnxruntime.quantization import QuantType, quantize_dynamic


def get_args():
parser = argparse.ArgumentParser()
parser.add_argument(
"--input",
type=str,
required=True,
help="Input onnx model",
)

parser.add_argument(
"--output",
type=str,
required=True,
help="Output onnx model",
)
return parser.parse_args()


def main():
args = get_args()
print(vars(args))

quantize_dynamic(
model_input=args.input,
model_output=args.output,
op_types_to_quantize=["MatMul"],
weight_type=QuantType.QInt8,
)


if __name__ == "__main__":
main()
97 changes: 97 additions & 0 deletions scripts/mobile-asr-models/parse_options.sh
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#!/usr/bin/env bash

# Copyright 2012 Johns Hopkins University (Author: Daniel Povey);
# Arnab Ghoshal, Karel Vesely

# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
# WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
# MERCHANTABLITY OR NON-INFRINGEMENT.
# See the Apache 2 License for the specific language governing permissions and
# limitations under the License.


# Parse command-line options.
# To be sourced by another script (as in ". parse_options.sh").
# Option format is: --option-name arg
# and shell variable "option_name" gets set to value "arg."
# The exception is --help, which takes no arguments, but prints the
# $help_message variable (if defined).


###
### The --config file options have lower priority to command line
### options, so we need to import them first...
###

# Now import all the configs specified by command-line, in left-to-right order
for ((argpos=1; argpos<$#; argpos++)); do
if [ "${!argpos}" == "--config" ]; then
argpos_plus1=$((argpos+1))
config=${!argpos_plus1}
[ ! -r $config ] && echo "$0: missing config '$config'" && exit 1
. $config # source the config file.
fi
done


###
### Now we process the command line options
###
while true; do
[ -z "${1:-}" ] && break; # break if there are no arguments
case "$1" in
# If the enclosing script is called with --help option, print the help
# message and exit. Scripts should put help messages in $help_message
--help|-h) if [ -z "$help_message" ]; then echo "No help found." 1>&2;
else printf "$help_message\n" 1>&2 ; fi;
exit 0 ;;
--*=*) echo "$0: options to scripts must be of the form --name value, got '$1'"
exit 1 ;;
# If the first command-line argument begins with "--" (e.g. --foo-bar),
# then work out the variable name as $name, which will equal "foo_bar".
--*) name=`echo "$1" | sed s/^--// | sed s/-/_/g`;
# Next we test whether the variable in question is undefned-- if so it's
# an invalid option and we die. Note: $0 evaluates to the name of the
# enclosing script.
# The test [ -z ${foo_bar+xxx} ] will return true if the variable foo_bar
# is undefined. We then have to wrap this test inside "eval" because
# foo_bar is itself inside a variable ($name).
eval '[ -z "${'$name'+xxx}" ]' && echo "$0: invalid option $1" 1>&2 && exit 1;

oldval="`eval echo \\$$name`";
# Work out whether we seem to be expecting a Boolean argument.
if [ "$oldval" == "true" ] || [ "$oldval" == "false" ]; then
was_bool=true;
else
was_bool=false;
fi

# Set the variable to the right value-- the escaped quotes make it work if
# the option had spaces, like --cmd "queue.pl -sync y"
eval $name=\"$2\";

# Check that Boolean-valued arguments are really Boolean.
if $was_bool && [[ "$2" != "true" && "$2" != "false" ]]; then
echo "$0: expected \"true\" or \"false\": $1 $2" 1>&2
exit 1;
fi
shift 2;
;;
*) break;
esac
done


# Check for an empty argument to the --cmd option, which can easily occur as a
# result of scripting errors.
[ ! -z "${cmd+xxx}" ] && [ -z "$cmd" ] && echo "$0: empty argument to --cmd option" 1>&2 && exit 1;


true; # so this script returns exit code 0.
42 changes: 42 additions & 0 deletions scripts/mobile-asr-models/run-impl.sh
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#!/usr/bin/env bash
#
# usage of this file:
# ./run.sh --input in.onnx --output1 out1.onnx --output2 out2.onnx
# where out1.onnx is a float32 model with batch size fixed to 1
# and out2.onnx is an int8 quantized version of out1.onnx

set -ex

input=
output1=
output2=
batch_dim=N
source ./parse_options.sh

if [ -z $input ]; then
echo 'Please provide input model filename'
exit 1
fi

if [ -z $output1 ]; then
echo 'Please provide output1 model filename'
exit 1
fi

if [ -z $output2 ]; then
echo 'Please provide output2 model filename'
exit 1
fi


echo "input: $input"
echo "output1: $output1"
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

rm tmp.fixed.onnx
40 changes: 40 additions & 0 deletions scripts/mobile-asr-models/run.sh
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#!/usr/bin/env bash

set -ex

curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20.tar.bz2
tar xvf sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20.tar.bz2
rm sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20.tar.bz2

src=sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20
dst=$src-mobile

mkdir -p $dst

./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

echo "---$src---"
ls -lh $src
echo "---$dst---"
ls -lh $dst
rm -rf $src

tar cjfv $dst.tar.bz2 $dst
mv *.tar.bz2 ../../
rm -rf $dst

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