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add CI for ljspeech (#1548)
This commit is contained in:
parent
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6
.github/scripts/librispeech/ASR/run.sh
vendored
6
.github/scripts/librispeech/ASR/run.sh
vendored
@ -15,9 +15,9 @@ function prepare_data() {
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# cause OOM error for CI later.
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mkdir -p download/lm
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pushd download/lm
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wget -q http://www.openslr.org/resources/11/librispeech-vocab.txt
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wget -q http://www.openslr.org/resources/11/librispeech-lexicon.txt
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wget -q http://www.openslr.org/resources/11/librispeech-lm-norm.txt.gz
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wget -q https://huggingface.co/csukuangfj/librispeech-for-ci/resolve/main/librispeech-lm-norm.txt.gz
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wget -q https://huggingface.co/csukuangfj/librispeech-for-ci/resolve/main/librispeech-lexicon.txt
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wget -q https://huggingface.co/csukuangfj/librispeech-for-ci/resolve/main/librispeech-vocab.txt
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ls -lh
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gunzip librispeech-lm-norm.txt.gz
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157
.github/scripts/ljspeech/TTS/run.sh
vendored
Executable file
157
.github/scripts/ljspeech/TTS/run.sh
vendored
Executable file
@ -0,0 +1,157 @@
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#!/usr/bin/env bash
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set -ex
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python3 -m pip install piper_phonemize -f https://k2-fsa.github.io/icefall/piper_phonemize.html
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python3 -m pip install espnet_tts_frontend
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python3 -m pip install numba
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log() {
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# This function is from espnet
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local fname=${BASH_SOURCE[1]##*/}
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echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
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}
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cd egs/ljspeech/TTS
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sed -i.bak s/600/8/g ./prepare.sh
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sed -i.bak s/"first 100"/"first 3"/g ./prepare.sh
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sed -i.bak s/500/5/g ./prepare.sh
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git diff
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function prepare_data() {
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# We have created a subset of the data for testing
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#
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mkdir download
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pushd download
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wget -q https://huggingface.co/csukuangfj/ljspeech-subset-for-ci-test/resolve/main/LJSpeech-1.1.tar.bz2
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tar xvf LJSpeech-1.1.tar.bz2
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popd
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./prepare.sh
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tree .
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}
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function train() {
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pushd ./vits
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sed -i.bak s/200/3/g ./train.py
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git diff .
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popd
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for t in low medium high; do
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./vits/train.py \
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--exp-dir vits/exp-$t \
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--model-type $t \
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--num-epochs 1 \
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--save-every-n 1 \
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--num-buckets 2 \
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--tokens data/tokens.txt \
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--max-duration 20
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ls -lh vits/exp-$t
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done
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}
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function infer() {
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for t in low medium high; do
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./vits/infer.py \
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--num-buckets 2 \
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--model-type $t \
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--epoch 1 \
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--exp-dir ./vits/exp-$t \
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--tokens data/tokens.txt \
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--max-duration 20
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done
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}
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function export_onnx() {
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for t in low medium high; do
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./vits/export-onnx.py \
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--model-type $t \
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--epoch 1 \
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--exp-dir ./vits/exp-$t \
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--tokens data/tokens.txt
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ls -lh vits/exp-$t/
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done
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}
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function test_medium() {
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git clone https://huggingface.co/csukuangfj/icefall-tts-ljspeech-vits-medium-2024-03-12
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./vits/export-onnx.py \
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--model-type medium \
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--epoch 820 \
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--exp-dir ./icefall-tts-ljspeech-vits-medium-2024-03-12/exp \
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--tokens ./icefall-tts-ljspeech-vits-medium-2024-03-12/data/tokens.txt
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ls -lh ./icefall-tts-ljspeech-vits-medium-2024-03-12/exp
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./vits/test_onnx.py \
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--model-filename ./icefall-tts-ljspeech-vits-medium-2024-03-12/exp/vits-epoch-820.onnx \
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--tokens ./icefall-tts-ljspeech-vits-medium-2024-03-12/data/tokens.txt \
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--output-filename /icefall/test-medium.wav
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ls -lh /icefall/test-medium.wav
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d=/icefall/vits-icefall-en_US-ljspeech-medium
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mkdir $d
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cp -v ./icefall-tts-ljspeech-vits-medium-2024-03-12/data/tokens.txt $d/
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cp -v ./icefall-tts-ljspeech-vits-medium-2024-03-12/exp/vits-epoch-820.onnx $d/model.onnx
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rm -rf icefall-tts-ljspeech-vits-medium-2024-03-12
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pushd $d
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wget -q https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/espeak-ng-data.tar.bz2
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tar xf espeak-ng-data.tar.bz2
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rm espeak-ng-data.tar.bz2
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cd ..
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tar cjf vits-icefall-en_US-ljspeech-medium.tar.bz2 vits-icefall-en_US-ljspeech-medium
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rm -rf vits-icefall-en_US-ljspeech-medium
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ls -lh *.tar.bz2
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popd
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}
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function test_low() {
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git clone https://huggingface.co/csukuangfj/icefall-tts-ljspeech-vits-low-2024-03-12
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./vits/export-onnx.py \
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--model-type low \
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--epoch 1600 \
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--exp-dir ./icefall-tts-ljspeech-vits-low-2024-03-12/exp \
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--tokens ./icefall-tts-ljspeech-vits-low-2024-03-12/data/tokens.txt
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ls -lh ./icefall-tts-ljspeech-vits-low-2024-03-12/exp
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./vits/test_onnx.py \
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--model-filename ./icefall-tts-ljspeech-vits-low-2024-03-12/exp/vits-epoch-1600.onnx \
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--tokens ./icefall-tts-ljspeech-vits-low-2024-03-12/data/tokens.txt \
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--output-filename /icefall/test-low.wav
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ls -lh /icefall/test-low.wav
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d=/icefall/vits-icefall-en_US-ljspeech-low
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mkdir $d
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cp -v ./icefall-tts-ljspeech-vits-low-2024-03-12/data/tokens.txt $d/
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cp -v ./icefall-tts-ljspeech-vits-low-2024-03-12/exp/vits-epoch-1600.onnx $d/model.onnx
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rm -rf icefall-tts-ljspeech-vits-low-2024-03-12
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pushd $d
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wget -q https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/espeak-ng-data.tar.bz2
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tar xf espeak-ng-data.tar.bz2
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rm espeak-ng-data.tar.bz2
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cd ..
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tar cjf vits-icefall-en_US-ljspeech-low.tar.bz2 vits-icefall-en_US-ljspeech-low
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rm -rf vits-icefall-en_US-ljspeech-low
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ls -lh *.tar.bz2
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popd
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}
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prepare_data
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train
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infer
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export_onnx
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rm -rf vits/exp-{low,medium,high}
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test_medium
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test_low
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102
.github/workflows/ljspeech.yml
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Normal file
102
.github/workflows/ljspeech.yml
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Normal file
@ -0,0 +1,102 @@
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name: ljspeech
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on:
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push:
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branches:
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- master
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pull_request:
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branches:
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- master
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workflow_dispatch:
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concurrency:
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group: ljspeech-${{ github.ref }}
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cancel-in-progress: true
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jobs:
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generate_build_matrix:
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if: github.repository_owner == 'csukuangfj' || github.repository_owner == 'k2-fsa'
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# see https://github.com/pytorch/pytorch/pull/50633
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runs-on: ubuntu-latest
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outputs:
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matrix: ${{ steps.set-matrix.outputs.matrix }}
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steps:
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- uses: actions/checkout@v4
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with:
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fetch-depth: 0
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- name: Generating build matrix
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id: set-matrix
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run: |
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# outputting for debugging purposes
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python ./.github/scripts/docker/generate_build_matrix.py
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MATRIX=$(python ./.github/scripts/docker/generate_build_matrix.py)
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echo "::set-output name=matrix::${MATRIX}"
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ljspeech:
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needs: generate_build_matrix
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name: py${{ matrix.python-version }} torch${{ matrix.torch-version }} v${{ matrix.version }}
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runs-on: ubuntu-latest
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strategy:
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fail-fast: false
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matrix:
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${{ fromJson(needs.generate_build_matrix.outputs.matrix) }}
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steps:
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- uses: actions/checkout@v4
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with:
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fetch-depth: 0
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- name: Free space
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shell: bash
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run: |
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ls -lh
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df -h
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rm -rf /opt/hostedtoolcache
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df -h
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echo "pwd: $PWD"
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echo "github.workspace ${{ github.workspace }}"
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- name: Run tests
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uses: addnab/docker-run-action@v3
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with:
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image: ghcr.io/${{ github.repository_owner }}/icefall:cpu-py${{ matrix.python-version }}-torch${{ matrix.torch-version }}-v${{ matrix.version }}
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options: |
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--volume ${{ github.workspace }}/:/icefall
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shell: bash
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run: |
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export PYTHONPATH=/icefall:$PYTHONPATH
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cd /icefall
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git config --global --add safe.directory /icefall
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.github/scripts/ljspeech/TTS/run.sh
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- name: display files
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shell: bash
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run: |
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ls -lh
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- uses: actions/upload-artifact@v4
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if: matrix.python-version == '3.9' && matrix.torch-version == '2.2.0'
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with:
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name: generated-test-files-${{ matrix.python-version }}-${{ matrix.torch-version }}
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path: ./*.wav
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- uses: actions/upload-artifact@v4
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if: matrix.python-version == '3.9' && matrix.torch-version == '2.2.0'
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with:
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name: generated-models-py${{ matrix.python-version }}-torch${{ matrix.torch-version }}
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path: ./*.wav
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- name: Release exported onnx models
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if: matrix.python-version == '3.9' && matrix.torch-version == '2.2.0'
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uses: svenstaro/upload-release-action@v2
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with:
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file_glob: true
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overwrite: true
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file: vits-icefall-*.tar.bz2
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repo_name: k2-fsa/sherpa-onnx
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repo_token: ${{ secrets.UPLOAD_GH_SHERPA_ONNX_TOKEN }}
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tag: tts-models
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@ -13,6 +13,14 @@ with the `LJSpeech <https://keithito.com/LJ-Speech-Dataset/>`_ dataset.
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The VITS paper: `Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech <https://arxiv.org/pdf/2106.06103.pdf>`_
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Install extra dependencies
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--------------------------
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.. code-block:: bash
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pip install piper_phonemize -f https://k2-fsa.github.io/icefall/piper_phonemize.html
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pip install numba espnet_tts_frontend
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Data preparation
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----------------
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@ -130,3 +138,64 @@ by visiting the following link:
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- ``--model-type=medium``: `<https://huggingface.co/csukuangfj/icefall-tts-ljspeech-vits-medium-2024-03-12>`_
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- ``--model-type=low``: `<https://huggingface.co/csukuangfj/icefall-tts-ljspeech-vits-low-2024-03-12>`_
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Usage in sherpa-onnx
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--------------------
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The following describes how to test the exported ONNX model in `sherpa-onnx`_.
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.. hint::
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`sherpa-onnx`_ supports different programming languages, e.g., C++, C, Python,
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Kotlin, Java, Swift, Go, C#, etc. It also supports Android and iOS.
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We only describe how to use pre-built binaries from `sherpa-onnx`_ below.
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Please refer to `<https://k2-fsa.github.io/sherpa/onnx/>`_
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for more documentation.
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Install sherpa-onnx
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^^^^^^^^^^^^^^^^^^^
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.. code-block:: bash
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pip install sherpa-onnx
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To check that you have installed `sherpa-onnx`_ successfully, please run:
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.. code-block:: bash
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which sherpa-onnx-offline-tts
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sherpa-onnx-offline-tts --help
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Download lexicon files
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^^^^^^^^^^^^^^^^^^^^^^
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.. code-block:: bash
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cd /tmp
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wget https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/espeak-ng-data.tar.bz2
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tar xf espeak-ng-data.tar.bz2
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Run sherpa-onnx
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^^^^^^^^^^^^^^^
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.. code-block:: bash
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cd egs/ljspeech/TTS
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sherpa-onnx-offline-tts \
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--vits-model=vits/exp/vits-epoch-1000.onnx \
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--vits-tokens=data/tokens.txt \
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--vits-data-dir=/tmp/espeak-ng-data \
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--num-threads=1 \
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--output-filename=./high.wav \
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"Ask not what your country can do for you; ask what you can do for your country."
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.. hint::
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You can also use ``sherpa-onnx-offline-tts-play`` to play the audio
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as it is generating.
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You should get a file ``high.wav`` after running the above command.
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Congratulations! You have successfully trained and exported a text-to-speech
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model and run it with `sherpa-onnx`_.
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@ -23,7 +23,11 @@ This file reads the texts in given manifest and save the new cuts with phoneme t
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import logging
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from pathlib import Path
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import tacotron_cleaner.cleaners
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try:
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import tacotron_cleaner.cleaners
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except ModuleNotFoundError as ex:
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raise RuntimeError(f"{ex}\nPlease run\n pip install espnet_tts_frontend\n")
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from lhotse import CutSet, load_manifest
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from piper_phonemize import phonemize_espeak
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@ -28,7 +28,7 @@ if [ $stage -le -1 ] && [ $stop_stage -ge -1 ]; then
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log "Stage -1: build monotonic_align lib"
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if [ ! -d vits/monotonic_align/build ]; then
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cd vits/monotonic_align
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python setup.py build_ext --inplace
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python3 setup.py build_ext --inplace
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cd ../../
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else
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log "monotonic_align lib already built"
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@ -82,8 +82,7 @@ if [ $stage -le 3 ] && [ $stop_stage -ge 3 ]; then
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log "Stage 3: Prepare phoneme tokens for LJSpeech"
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# We assume you have installed piper_phonemize and espnet_tts_frontend.
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# If not, please install them with:
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# - piper_phonemize: refer to https://github.com/rhasspy/piper-phonemize,
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# could install the pre-built wheels from https://github.com/csukuangfj/piper-phonemize/releases/tag/2023.12.5
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# - piper_phonemize: pip install piper_phonemize -f https://k2-fsa.github.io/icefall/piper_phonemize.html,
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# - espnet_tts_frontend, `pip install espnet_tts_frontend`, refer to https://github.com/espnet/espnet_tts_frontend/
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if [ ! -e data/spectrogram/.ljspeech_with_token.done ]; then
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./local/prepare_tokens_ljspeech.py
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|
@ -10,7 +10,11 @@ import warnings
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import numpy as np
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import torch
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from numba import njit, prange
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try:
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from numba import njit, prange
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except ModuleNotFoundError as ex:
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raise RuntimeError(f"{ex}/nPlease run\n pip install numba")
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try:
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from .core import maximum_path_c
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|
@ -23,8 +23,8 @@ try:
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from piper_phonemize import phonemize_espeak
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except Exception as ex:
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raise RuntimeError(
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f"{ex}\nPlease follow instructions in "
|
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"../prepare.sh to install piper-phonemize"
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f"{ex}\nPlease run\n"
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"pip install piper_phonemize -f https://k2-fsa.github.io/icefall/piper_phonemize.html"
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)
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from utils import intersperse
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|
@ -255,6 +255,7 @@ class LJSpeechTtsDataModule:
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valid_sampler = DynamicBucketingSampler(
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cuts_valid,
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max_duration=self.args.max_duration,
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num_buckets=self.args.num_buckets,
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shuffle=False,
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)
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logging.info("About to create valid dataloader")
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@ -294,6 +295,7 @@ class LJSpeechTtsDataModule:
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test_sampler = DynamicBucketingSampler(
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cuts,
|
||||
max_duration=self.args.max_duration,
|
||||
num_buckets=self.args.num_buckets,
|
||||
shuffle=False,
|
||||
)
|
||||
logging.info("About to create test dataloader")
|
||||
|
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Reference in New Issue
Block a user