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102 lines
4.6 KiB
102 lines
4.6 KiB
#!/bin/bash
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source test_tipc/common_func.sh
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FILENAME=$1
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# MODE be one of ['benchmark_train_lite_infer' 'benchmark_train_whole_infer' 'whole_train_whole_infer',
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# 'whole_infer', 'klquant_whole_infer',
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# 'cpp_infer', 'serving_infer', 'benchmark_train']
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MODE=$2
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dataline=$(cat ${FILENAME})
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# parser params
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IFS=$'\n'
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lines=(${dataline})
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python=python
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# The training params
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model_name=$(func_parser_value "${lines[1]}")
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echo "model_name:"${model_name}
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trainer_list=$(func_parser_value "${lines[14]}")
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if [[ ${MODE} = "benchmark_train" ]];then
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curPath=$(readlink -f "$(dirname "$0")")
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echo "curPath:"${curPath} # /PaddleSpeech/tests/test_tipc
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cd ${curPath}/../..
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echo "------------- install for speech "
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apt-get install libsndfile1 -y
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pip install yacs #-i https://pypi.tuna.tsinghua.edu.cn/simple
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pip install pytest-runner #-i https://pypi.tuna.tsinghua.edu.cn/simple
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pip install kaldiio #-i https://pypi.tuna.tsinghua.edu.cn/simple
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pip install setuptools_scm #-i https://pypi.tuna.tsinghua.edu.cn/simple
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pip install . #-i https://pypi.tuna.tsinghua.edu.cn/simple
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pip install jsonlines
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pip list
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cd -
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if [[ ${model_name} == "conformer" ]]; then
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# set the URL for aishell_tiny dataset
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conformer_aishell_URL=${conformer_aishell_URL:-"None"}
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if [[ ${conformer_aishell_URL} == 'None' ]];then
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echo "please contact author to get the URL.\n"
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exit
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else
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rm -rf ${curPath}/../../dataset/aishell/aishell.py
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rm -rf ${curPath}/../../dataset/aishell/data_aishell_tiny*
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wget -P ${curPath}/../../dataset/aishell/ ${conformer_aishell_URL}
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fi
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cd ${curPath}/../../examples/aishell/asr1
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#Prepare the data
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sed -i "s#python3#python#g" ./local/data.sh
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bash run.sh --stage 0 --stop_stage 0 # 执行第一遍的时候会偶现报错
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bash run.sh --stage 0 --stop_stage 0
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mkdir -p ${curPath}/conformer/benchmark_train/
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cp -rf conf ${curPath}/conformer/benchmark_train/
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cp -rf data ${curPath}/conformer/benchmark_train/
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cd ${curPath}
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sed -i "s#accum_grad: 2#accum_grad: 1#g" ${curPath}/conformer/benchmark_train/conf/conformer.yaml
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sed -i "s#data/#test_tipc/conformer/benchmark_train/data/#g" ${curPath}/conformer/benchmark_train/conf/conformer.yaml
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sed -i "s#conf/#test_tipc/conformer/benchmark_train/conf/#g" ${curPath}/conformer/benchmark_train/conf/conformer.yaml
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sed -i "s#data/#test_tipc/conformer/benchmark_train/data/#g" ${curPath}/conformer/benchmark_train/conf/tuning/decode.yaml
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sed -i "s#data/#test_tipc/conformer/benchmark_train/data/#g" ${curPath}/conformer/benchmark_train/conf/preprocess.yaml
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fi
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if [[ ${model_name} == "pwgan" ]]; then
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# 下载 csmsc 数据集并解压缩
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wget -nc https://paddle-wheel.bj.bcebos.com/benchmark/BZNSYP.rar
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mkdir -p BZNSYP
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unrar x BZNSYP.rar BZNSYP
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wget -nc https://paddlespeech.bj.bcebos.com/Parakeet/benchmark/durations.txt
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# 避免网络问题导致的 nltk_data 无法下载使程序 hang 住
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wget -nc https://paddlespeech.bj.bcebos.com/Parakeet/tools/nltk_data.tar.gz
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tar -xzf nltk_data.tar.gz -C ${HOME}
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# 数据预处理
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python ../paddlespeech/t2s/exps/gan_vocoder/preprocess.py --rootdir=BZNSYP/ --dumpdir=dump --num-cpu=20 --cut-sil=True --dur-file=durations.txt --config=../examples/csmsc/voc1/conf/default.yaml
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python ../utils/compute_statistics.py --metadata=dump/train/raw/metadata.jsonl --field-name="feats"
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python ../paddlespeech/t2s/exps/gan_vocoder/normalize.py --metadata=dump/train/raw/metadata.jsonl --dumpdir=dump/train/norm --stats=dump/train/feats_stats.npy
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python ../paddlespeech/t2s/exps/gan_vocoder/normalize.py --metadata=dump/dev/raw/metadata.jsonl --dumpdir=dump/dev/norm --stats=dump/train/feats_stats.npy
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python ../paddlespeech/t2s/exps/gan_vocoder/normalize.py --metadata=dump/test/raw/metadata.jsonl --dumpdir=dump/test/norm --stats=dump/train/feats_stats.npy
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fi
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echo "barrier start"
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PYTHON="${python}" bash test_tipc/barrier.sh
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echo "barrier end"
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if [[ ${model_name} == "mdtc" ]]; then
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# 下载 Snips 数据集并解压缩
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wget https://paddlespeech.bj.bcebos.com/datasets/hey_snips_kws_4.0.tar.gz.1
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wget https://paddlespeech.bj.bcebos.com/datasets/hey_snips_kws_4.0.tar.gz.2
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cat hey_snips_kws_4.0.tar.gz.* > hey_snips_kws_4.0.tar.gz
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rm hey_snips_kws_4.0.tar.gz.*
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tar -xzf hey_snips_kws_4.0.tar.gz
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# 解压后的数据目录 ./hey_snips_research_6k_en_train_eval_clean_ter
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fi
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fi
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