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Add C++ runtime and Python APIs for Moonshine models (#1473)

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This commit is contained in:
Fangjun Kuang
2024-10-26 14:34:07 +08:00
committed by GitHub
parent 0f2732e4e8
commit 669f5ef441
33 changed files with 1572 additions and 36 deletions
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50
.github/scripts/test-offline-moonshine.sh vendored Executable file
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@@ -0,0 +1,50 @@
#!/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]}) $*"
}
export GIT_CLONE_PROTECTION_ACTIVE=false
echo "EXE is $EXE"
echo "PATH: $PATH"
which $EXE
names=(
tiny
base
)
for name in ${names[@]}; do
log "------------------------------------------------------------"
log "Run $name"
log "------------------------------------------------------------"
repo_url=https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-whisper-$name.tar.bz2
repo_url=https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-moonshine-$name-en-int8.tar.bz2
curl -SL -O $repo_url
tar xvf sherpa-onnx-moonshine-$name-en-int8.tar.bz2
rm sherpa-onnx-moonshine-$name-en-int8.tar.bz2
repo=sherpa-onnx-moonshine-$name-en-int8
log "Start testing ${repo_url}"
log "test int8 onnx"
time $EXE \
--moonshine-preprocessor=$repo/preprocess.onnx \
--moonshine-encoder=$repo/encode.int8.onnx \
--moonshine-uncached-decoder=$repo/uncached_decode.int8.onnx \
--moonshine-cached-decoder=$repo/cached_decode.int8.onnx \
--tokens=$repo/tokens.txt \
--num-threads=2 \
$repo/test_wavs/0.wav \
$repo/test_wavs/1.wav \
$repo/test_wavs/8k.wav
rm -rf $repo
done

10
.github/scripts/test-python.sh vendored
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@@ -8,6 +8,16 @@ log() {
echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
}
log "test offline Moonshine"
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-moonshine-tiny-en-int8.tar.bz2
tar xvf sherpa-onnx-moonshine-tiny-en-int8.tar.bz2
rm sherpa-onnx-moonshine-tiny-en-int8.tar.bz2
python3 ./python-api-examples/offline-moonshine-decode-files.py
rm -rf sherpa-onnx-moonshine-tiny-en-int8
log "test offline speaker diarization"
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speaker-segmentation-models/sherpa-onnx-pyannote-segmentation-3-0.tar.bz2