wehub-resource-sync
65 lines
1.7 KiB
Bash
65 lines
1.7 KiB
Bash
# !/bin/bash
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# Copyright (c) 2023 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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if [ ! -d "./log" ]; then
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mkdir ./log
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echo "Create log floder for store running log"
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fi
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export FLAGS_LAUNCH_BARRIER=0
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export PADDLE_TRAINER_ID=0
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export PADDLE_PSERVER_NUMS=1
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export PADDLE_TRAINERS=1
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export PADDLE_TRAINERS_NUM=${PADDLE_TRAINERS}
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export POD_IP=127.0.0.1
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# set free port if 29011 is occupied
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export PADDLE_PSERVERS_IP_PORT_LIST="127.0.0.1:29011"
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export PADDLE_PSERVER_PORT_ARRAY=(29011)
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# set gpu numbers according to your device
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#export FLAGS_selected_gpus="0,1,2,3,4,5,6,7"
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export FLAGS_selected_gpus="0,1"
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# set your model yaml
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#SC="gpubox_ps_trainer.py"
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SC="static_gpubox_trainer.py"
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# run pserver
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export TRAINING_ROLE=PSERVER
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for((i=0;i<$PADDLE_PSERVER_NUMS;i++))
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do
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cur_port=${PADDLE_PSERVER_PORT_ARRAY[$i]}
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echo "PADDLE WILL START PSERVER "$cur_port
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export PADDLE_PORT=${cur_port}
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python -u $SC &> ./log/pserver.$i.log &
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done
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# run trainer
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export TRAINING_ROLE=TRAINER
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for((i=0;i<$PADDLE_TRAINERS;i++))
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do
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echo "PADDLE WILL START Trainer "$i
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export PADDLE_TRAINER_ID=$i
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python -u $SC &> ./log/worker.$i.log
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done
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if [ $? -eq 0 ];then
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echo "Training log stored in ./log/"
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else
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exit 1
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fi
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