forked from mindspore-Ecosystem/mindspore
88 lines
2.2 KiB
Bash
Executable File
88 lines
2.2 KiB
Bash
Executable File
#!/bin/bash
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# Copyright 2020 Huawei Technologies Co., Ltd
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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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# ============================================================================
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if [ $# != 2 ] && [ $# != 3 ]
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then
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echo "Usage: sh run_distribute_train.sh [MINDSPORE_HCCL_CONFIG_PATH] [DATASET_PATH] [PRETRAINED_PATH](optional)"
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exit 1
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fi
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get_real_path(){
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if [ "${1:0:1}" == "/" ]; then
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echo "$1"
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else
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echo "$(realpath -m $PWD/$1)"
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fi
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}
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PATH1=$(get_real_path $1)
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PATH2=$(get_real_path $2)
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echo $PATH1
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echo $PATH2
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if [ $# == 3 ]
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then
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PATH3=$(get_real_path $3)
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echo $PATH3
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fi
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if [ ! -f $PATH1 ]
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then
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echo "error: MINDSPORE_HCCL_CONFIG_PATH=$PATH1 is not a file"
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exit 1
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fi
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if [ ! -d $PATH2 ]
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then
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echo "error: DATASET_PATH=$PATH2 is not a directory"
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exit 1
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fi
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if [ $# == 3 ] && [ ! -f $PATH3 ]
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then
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echo "error: PRETRAINED_PATH=$PATH3 is not a file"
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exit 1
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fi
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ulimit -u unlimited
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export DEVICE_NUM=8
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export RANK_SIZE=8
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export MINDSPORE_HCCL_CONFIG_PATH=$PATH1
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export RANK_TABLE_FILE=$PATH1
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for((i=0; i<${DEVICE_NUM}; i++))
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do
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export DEVICE_ID=$i
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export RANK_ID=$i
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rm -rf ./train_parallel$i
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mkdir ./train_parallel$i
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cp ../*.py ./train_parallel$i
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cp *.sh ./train_parallel$i
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cp -r ../src ./train_parallel$i
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cd ./train_parallel$i || exit
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echo "start training for rank $RANK_ID, device $DEVICE_ID"
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env > env.log
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if [ $# == 2 ]
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then
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python train.py --do_train=True --run_distribute=True --device_num=$DEVICE_NUM --dataset_path=$PATH2 &> log &
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fi
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if [ $# == 3 ]
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then
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python train.py --do_train=True --run_distribute=True --device_num=$DEVICE_NUM --dataset_path=$PATH2 --pre_trained=$PATH3 &> log &
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fi
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cd ..
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done
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