mindspore/model_zoo/resnet101/scripts/run_distribute_train.sh

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#!/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