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#!/bin/bash
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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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stage=0
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stop_stage=100
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use_gpu=true # if true, we run on GPU.
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. ${MAIN_ROOT}/utils/parse_options.sh || exit -1;
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if [ $# -ne 3 ] ; then
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echo "Usage: $0 [options] <data-dir> <exp-dir> <conf-path>";
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echo "e.g.: $0 ./data/ exp/voxceleb12/ conf/ecapa_tdnn.yaml"
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echo "Options: "
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echo " --use-gpu <true,false|true> # specify is gpu is to be used for training"
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echo " --stage <stage|-1> # Used to run a partially-completed data process from somewhere in the middle."
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echo " --stop-stage <stop-stage|100> # Used to run a partially-completed data process stop stage in the middle"
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exit 1;
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fi
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dir=$1
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exp_dir=$2
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conf_path=$3
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# get the gpu nums for training
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ngpu=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
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echo "using $ngpu gpus..."
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# setting training device
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device="cpu"
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if ${use_gpu}; then
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device="gpu"
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fi
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if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
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# train the speaker identification task with voxceleb data
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# and we will create the trained model parameters in ${exp_dir}/model.pdparams as the soft link
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# Note: we will store the log file in exp/log directory
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python3 -m paddle.distributed.launch --gpus=$CUDA_VISIBLE_DEVICES \
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${BIN_DIR}/train.py --device ${device} --checkpoint-dir ${exp_dir} \
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--data-dir ${dir} --config ${conf_path}
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fi
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if [ $? -ne 0 ]; then
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echo "Failed in training!"
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exit 1
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fi
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exit 0
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