mindspore/model_zoo/resnet101/scripts/run_distribute_train.sh

#!/bin/bash
# Copyright 2020 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================

if [ $# != 2 ] && [ $# != 3 ]
then 
    echo "Usage: sh run_distribute_train.sh [MINDSPORE_HCCL_CONFIG_PATH] [DATASET_PATH] [PRETRAINED_PATH](optional)"
exit 1
fi

get_real_path(){
  if [ "${1:0:1}" == "/" ]; then
    echo "$1"
  else
    echo "$(realpath -m $PWD/$1)"
  fi
}
PATH1=$(get_real_path $1)
PATH2=$(get_real_path $2)
echo $PATH1
echo $PATH2
if [ $# == 3 ]
then 
    PATH3=$(get_real_path $3)
    echo $PATH3
fi

if [ ! -f $PATH1 ]
then 
    echo "error: MINDSPORE_HCCL_CONFIG_PATH=$PATH1 is not a file"
exit 1
fi 

if [ ! -d $PATH2 ]
then 
    echo "error: DATASET_PATH=$PATH2 is not a directory"
exit 1
fi 

if [ $# == 3 ] && [ ! -f $PATH3 ]
then
    echo "error: PRETRAINED_PATH=$PATH3 is not a file"
exit 1
fi

ulimit -u unlimited
export DEVICE_NUM=8
export RANK_SIZE=8
export MINDSPORE_HCCL_CONFIG_PATH=$PATH1
export RANK_TABLE_FILE=$PATH1

for((i=0; i<${DEVICE_NUM}; i++))
do
    export DEVICE_ID=$i
    export RANK_ID=$i
    rm -rf ./train_parallel$i
    mkdir ./train_parallel$i
    cp ../*.py ./train_parallel$i
    cp *.sh ./train_parallel$i
    cp -r ../src ./train_parallel$i
    cd ./train_parallel$i || exit
    echo "start training for rank $RANK_ID, device $DEVICE_ID"
    env > env.log
    if [ $# == 2 ]
    then	    
        python train.py --do_train=True --run_distribute=True --device_num=$DEVICE_NUM --dataset_path=$PATH2 &> log &
    fi
    
    if [ $# == 3 ]
    then
        python train.py --do_train=True --run_distribute=True --device_num=$DEVICE_NUM --dataset_path=$PATH2 --pre_trained=$PATH3 &> log &
    fi

    cd ..
done