forked from mindspore-Ecosystem/mindspore
add training scripts and modify readme of mobilenetv2_quant and
resnet50_quant modify readme
This commit is contained in:
hwjiaorui
parent
a50bc2182e
commit
aaa0436882
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@ -70,7 +70,7 @@ For FP16 operators, if the input data type is FP32, the backend of MindSpore wil
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├── mobileNetv2_quant
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├── Readme.md # descriptions about MobileNetV2-Quant
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├── scripts
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│ ├──run_train_quant.sh # shell script for train on Ascend
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│ ├──run_train.sh # shell script for train on Ascend and GPU
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│ ├──run_infer_quant.sh # shell script for evaluation on Ascend
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├── src
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│ ├──config.py # parameter configuration
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@ -91,19 +91,22 @@ For FP16 operators, if the input data type is FP32, the backend of MindSpore wil
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You can start training using python or shell scripts. The usage of shell scripts as follows:
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- Ascend: sh run_train_quant.sh Ascend [DEVICE_NUM] [SERVER_IP(x.x.x.x)] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH] [CKPT_PATH]
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- bash run_train.sh [Ascend] [RANK_TABLE_FILE] [DATASET_PATH] [PRETRAINED_CKPT_PATH]\(optional)
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- bash run_train.sh [GPU] [DEVICE_ID_LIST] [DATASET_PATH] [PRETRAINED_CKPT_PATH]\(optional)
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### Launch
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```
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# training example
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shell:
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Ascend: sh run_train_quant.sh Ascend 8 10.222.223.224 0,1,2,3,4,5,6,7 ~/imagenet/train/ mobilenet_199.ckpt
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``` bash
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# training example
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>>> bash run_train.sh Ascend ~/hccl_4p_0123_x.x.x.x.json ~/imagenet/train/ ~/mobilenet.ckpt
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>>> bash run_train.sh GPU 1,2 ~/imagenet/train/ ~/mobilenet.ckpt
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```
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### Result
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Training result will be stored in the example path. Checkpoints will be stored at `. /checkpoint` by default, and training log will be redirected to `./train/train.log` like followings.
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Training result will be stored in the example path. Checkpoints trained by `Ascend` will be stored at `./train/device$i/checkpoint` by default, and training log will be redirected to `./train/device$i/train.log`. Checkpoints trained by `GPU` will be stored in `./train/checkpointckpt_$i` by default, and training log will be redirected to `./train/train.log`.
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`train.log` is as follows:
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```
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epoch: [ 0/200], step:[ 624/ 625], loss:[5.258/5.258], time:[140412.236], lr:[0.100]
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@ -0,0 +1,300 @@
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#!/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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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/$1)"
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fi
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}
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# check_and_get_Ascend_device(){
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# #device_list=(${1//,/ })
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# IFS=',' read -ra device_list <<<"$1"
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# last_device_id=0
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# first_device_id=8
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# device_used=(0 0 0 0 0 0 0 0)
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# for var in "${device_list[@]}"
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# do
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# if [ $((var)) -lt 0 ] || [ $((var)) -ge 8 ]
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# then
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# echo "error: device id=${var} is incorrect, device id must be in range [0,8), please check your device id list!"
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# exit 1
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# fi
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# if [ ${device_used[$((var))]} -eq 0 ]
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# then
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# device_used[ $((var)) ]=1
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# else
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# echo "error: device id is duplicate, please check your device id list!"
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# exit 1
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# fi
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# if [ ${last_device_id} \< $((var)) ]
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# then
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# last_device_id=$((var))
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# fi
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# if [ ${first_device_id} \> $((var)) ]
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# then
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# first_device_id=$((var))
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# fi
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# done
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# device_num=`expr ${last_device_id} - ${first_device_id} + 1`
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# if [ ${device_num} != ${#device_list[*]} ]
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# then
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# echo "error: the Ascend chips used must be continuous, please check your device id list!"
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# exit 1
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# fi
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# if [ ${first_device_id} -lt 4 ] && [ ${last_device_id} -ge 4 ]
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# then
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# if [ ${first_device_id} != 0 ] || [ ${last_device_id} != 7 ]
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# then
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# echo "error: device id list must be in the same group of [0,4) or [4,8) when using Ascend chips."
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# exit 1
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# fi
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# fi
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# echo "${first_device_id},`expr ${last_device_id} + 1`"
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# }
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# get_hccl_name(){
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# server_ip=$(ifconfig -a | grep inet | grep -v 127.0.0.1 | grep -v inet6 | awk '{print $2}' | tr -d "addr:")
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# device_num=`expr $2 - $1`
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# device_id_list=""
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# for(( i=$1 ; i < $2 ; i++ ))
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# do
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# device_id_list=${device_id_list}$i
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# done
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# hccl_name="hccl_${device_num}p_${device_id_list}_${server_ip}.json"
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# echo ${hccl_name}
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# }
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get_gpu_device_num(){
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#device_list=(${1//,/ })
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IFS=',' read -ra device_list <<<"$1"
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device_used=(0 0 0 0 0 0 0 0)
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device_num=0
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for var in "${device_list[@]}"
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do
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if [ $((var)) -lt 0 ] || [ $((var)) -ge 8 ]
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then
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echo "error: device id=${var} is incorrect, device id must be in range [0,8), please check your device id list!"
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exit 1
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fi
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if [ ${device_used[$((var))]} -eq 0 ]
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then
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device_used[ $((var)) ]=1
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device_num=$((device_num+1))
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fi
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done
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echo ${device_num}
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}
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run_ascend(){
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if [ $# -gt 4 ] || [ $# -lt 3 ]
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then
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echo "Usage: bash run_train.sh [Ascend] [RANK_TABLE_FILE] [DATASET_PATH] [PRETRAINED_CKPT_PATH](optional)\n "
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exit 1
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fi
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#first_last_device=$(check_and_get_Ascend_device $2)
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#devices=(${first_last_device//,/ })
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#IFS=',' read -ra devices <<<"${first_last_device}"
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# first_device=${first_last_device:0:1}
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# last_device=${first_last_device:2:1}
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# device_num=`expr $((last_device)) - $((first_device))`
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#single ascend or multiple ascend
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# if [ ${device_num} -gt 1 ]
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# then
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# ori_path=$(dirname "$(readlink -f "$0" )")
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# #generate hccl config file
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# cd ../../../../utils/hccl_tools/ || exit
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# device_num_arg="[${first_device},${last_device})"
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# python hccl_tools.py --device_num=${device_num_arg}
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# hccl_name=$(get_hccl_name ${first_device} ${last_device})
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# if [ ! -e ${hccl_name} ]
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# then
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# echo "error: failed to generate the hccl config file!"
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# exit 1
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# fi
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# mv ${hccl_name} ${ori_path}
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# cd ${ori_path} || exit
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# PATH1=$(get_real_path ${hccl_name})
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# if [ ! -f $PATH1 ]
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# then
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# echo "error: RANK_TABLE_FILE=$PATH1 is not a file"
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# exit 1
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# fi
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# export RANK_TABLE_FILE=$PATH1
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# fi
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PATH1=$(get_real_path $2)
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PATH2=$(get_real_path $3)
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if [ $# == 4 ]
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then
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PATH3=$(get_real_path $4)
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fi
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if [ ! -f $PATH1 ]
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then
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echo "error: RANK_TABLE_FILE=$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 [ $# == 4 ] && [ ! -f $PATH3 ]
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then
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echo "error: PRETRAINED_CKPT_PATH=$PATH3 is not a file"
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exit 1
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fi
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rank_file_name=${2##*/}
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IFS='_' read -ra array <<<"${rank_file_name}"
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device_id_list=${array[2]}
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first_device=${device_id_list:0:1}
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#last_device=${device_list:${#device_list}-1:1}
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device_num=${#device_id_list}
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ulimit -u unlimited
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export DEVICE_NUM=${device_num}
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export RANK_SIZE=${device_num}
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export RANK_TABLE_FILE=$PATH1
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export SERVER_ID=0
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rank_start=$((DEVICE_NUM * SERVER_ID))
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rm -rf ./train
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mkdir ./train
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for((i=0; i<${device_num}; i++))
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do
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export DEVICE_ID=$((first_device+i))
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export RANK_ID=$((rank_start + i))
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mkdir ./train/device$i
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cp ../*.py ./train/device$i
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cp *.sh ./train/device$i
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cp -r ../src ./train/device$i
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cd ./train/device$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 [ $# == 3 ]
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then
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python train.py --device_target=$1 --dataset_path=$PATH2 &> train.log &
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fi
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if [ $# == 4 ]
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then
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python train.py --device_traget=$1 --dataset_path=$PATH2 --pre_trained=$PATH3 &> train.log &
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fi
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cd ../.. || exit
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done
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}
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run_gpu(){
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if [ $# -gt 3 ] || [ $# -lt 2 ]
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then
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echo "Usage: bash run_train.sh [GPU] [DEVICE_ID_LIST] [DATASET_PATH] [PRETRAINED_CKPT_PATH](optional)\n "
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exit 1
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fi
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PATH1=$(get_real_path $3)
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if [ $# == 4 ]
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then
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PATH2=$(get_real_path $4)
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fi
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if [ ! -d $PATH1 ]
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then
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echo "error: DATASET_PATH=$PATH1 is not a directory"
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exit 1
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fi
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if [ $# == 4 ] && [ ! -f $PATH2 ]
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then
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echo "error: PRETRAINED_CKPT_PATH=$PATH2 is not a file"
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exit 1
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fi
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device_num=$(get_gpu_device_num $2)
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ulimit -u unlimited
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export DEVICE_NUM=${device_num}
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export RANK_SIZE=${device_num}
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export CUDA_VISIBLE_DEVICES=$2
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rm -rf ./train
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mkdir ./train
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cp ../*.py ./train
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cp *.sh ./train
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cp -r ../src ./train
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cd ./train || exit
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echo "start training"
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env > env.log
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if [ $# == 3 ]
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then
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mpirun --allow-run-as-root -n ${RANK_SIZE} \
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python train.py --device_target=$1 --dataset_path=$PATH1 &> train.log &
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fi
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if [ $# == 4 ]
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then
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mpirun --allow-run-as-root -n ${RANK_SIZE} \
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python train.py --device_traget=$1 --dataset_path=$PATH1 --pre_trained=$PATH2 &> train.log &
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fi
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cd ..
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}
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if [ $1 = "Ascend" ] ; then
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run_ascend "$@"
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elif [ $1 = "GPU" ] ; then
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run_gpu "$@"
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else
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echo "Unsupported device target: $1"
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fi;
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@ -1,96 +0,0 @@
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#!/usr/bin/env 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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run_ascend()
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{
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if [ $2 -lt 1 ] && [ $2 -gt 8 ]
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then
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echo "error: DEVICE_NUM=$2 is not in (1-9)"
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exit 1
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fi
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if [ ! -d $5 ] && [ ! -f $5 ]
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then
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echo "error: DATASET_PATH=$5 is not a directory or file"
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exit 1
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fi
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BASEPATH=$(cd "`dirname $0`" || exit; pwd)
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export PYTHONPATH=${BASEPATH}:$PYTHONPATH
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if [ -d "../train" ];
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then
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rm -rf ../train
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fi
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mkdir ../train
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cd ../train || exit
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python ${BASEPATH}/../src/launch.py \
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--nproc_per_node=$2 \
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--visible_devices=$4 \
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--server_id=$3 \
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--training_script=${BASEPATH}/../train.py \
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--dataset_path=$5 \
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--pre_trained=$6 \
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--device_target=$1 &> train.log & # dataset train folder
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}
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run_gpu()
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{
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if [ $2 -lt 1 ] && [ $2 -gt 8 ]
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then
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echo "error: DEVICE_NUM=$2 is not in (1-8)"
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exit 1
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fi
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if [ ! -d $4 ]
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then
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echo "error: DATASET_PATH=$4 is not a directory"
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exit 1
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fi
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BASEPATH=$(cd "`dirname $0`" || exit; pwd)
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export PYTHONPATH=${BASEPATH}:$PYTHONPATH
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if [ -d "../train" ];
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then
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rm -rf ../train
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fi
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mkdir ../train
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cd ../train || exit
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export CUDA_VISIBLE_DEVICES="$3"
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mpirun -n $2 --allow-run-as-root \
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python ${BASEPATH}/../train.py \
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--dataset_path=$4 \
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--device_target=$1 \
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--pre_trained=$5 &> ../train.log & # dataset train folder
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}
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if [ $# -gt 6 ] || [ $# -lt 5 ]
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then
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echo "Usage:\n \
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Ascend: sh run_train_quant.sh Ascend [DEVICE_NUM] [SERVER_IP(x.x.x.x)] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH] [CKPT_PATH]\n \
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GPU: sh run_train_quant.sh GPU [DEVICE_NUM] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH] [CKPT_PATH]\n \
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"
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exit 1
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fi
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if [ $1 = "Ascend" ] ; then
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run_ascend "$@"
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elif [ $1 = "GPU" ] ; then
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run_gpu "$@"
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else
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echo "Unsupported device target."
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fi;
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@ -1,4 +1,43 @@
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# Contents
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# ResNet-50_quant Example
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## Description
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This is an example of training ResNet-50_quant with ImageNet2012 dataset in MindSpore.
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## Requirements
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- Install [MindSpore](https://www.mindspore.cn/install/en).
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- Download the dataset ImageNet2012
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> Unzip the ImageNet2012 dataset to any path you want and the folder structure should include train and eval dataset as follows:
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> ```
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> .
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> ├── ilsvrc # train dataset
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> └── ilsvrc_eval # infer dataset: images should be classified into 1000 directories firstly, just like train images
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> ```
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## Example structure
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```shell
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resnet50_quant/
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├── eval.py
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├── models
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│ └── resnet_quant.py
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├── Readme.md
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├── scripts
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│ ├── run_infer.sh
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│ └── run_train.sh
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├── src
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│ ├── config.py
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│ ├── crossentropy.py
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│ ├── dataset.py
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│ ├── launch.py
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│ └── lr_generator.py
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└── train.py
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||||
```
|
||||
|
||||
- [resnet50 Description](#resnet50-description)
|
||||
- [Model Architecture](#model-architecture)
|
||||
|
|
@ -88,21 +127,17 @@ For FP16 operators, if the input data type is FP32, the backend of MindSpore wil
|
|||
|
||||
### Usage
|
||||
|
||||
|
||||
You can start training using python or shell scripts. The usage of shell scripts as follows:
|
||||
|
||||
- Ascend: sh run_train.sh Ascend [DEVICE_NUM] [SERVER_IP(x.x.x.x)] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH][CKPT_PATH]
|
||||
- Ascend: sh run_train.sh Ascend [RANK_TABLE_FILE] [DATASET_PATH] [PRETRAINED_CKPT_PATH]\(optional)
|
||||
### Launch
|
||||
|
||||
```
|
||||
# training example
|
||||
shell:
|
||||
Ascend: sh run_train.sh Ascend 8 10.222.223.224 0,1,2,3,4,5,6,7 ~/resnet/train/ Resnet50-90_5004.ckpt
|
||||
# training example
|
||||
Ascend: bash run_train.sh Ascend ~/hccl_4p_0123_x.x.x.x.json ~/imagenet/train/
|
||||
```
|
||||
|
||||
### Result
|
||||
|
||||
Training result will be stored in the example path. Checkpoints will be stored at `. /checkpoint` by default, and training log will be redirected to `./train/train.log` like followings.
|
||||
Training result will be stored in the example path. Checkpoints will be stored at `./train/device$i/` by default, and training log will be redirected to `./train/device$i/train.log` like followings.
|
||||
|
||||
```
|
||||
epoch: 1 step: 5004, loss is 4.8995576
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
#!/usr/bin/env bash
|
||||
#!/bin/bash
|
||||
# Copyright 2020 Huawei Technologies Co., Ltd
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
|
|
@ -14,49 +14,259 @@
|
|||
# limitations under the License.
|
||||
# ============================================================================
|
||||
|
||||
run_ascend()
|
||||
{
|
||||
if [ $2 -lt 1 ] && [ $2 -gt 8 ]
|
||||
then
|
||||
echo "error: DEVICE_NUM=$2 is not in (1-8)"
|
||||
exit 1
|
||||
get_real_path(){
|
||||
if [ "${1:0:1}" == "/" ]; then
|
||||
echo "$1"
|
||||
else
|
||||
echo "$(realpath -m $PWD/$1)"
|
||||
fi
|
||||
|
||||
if [ ! -d $5 ] && [ ! -f $5 ]
|
||||
then
|
||||
echo "error: DATASET_PATH=$5 is not a directory or file"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
BASEPATH=$(cd "`dirname $0`" || exit; pwd)
|
||||
export PYTHONPATH=${BASEPATH}:$PYTHONPATH
|
||||
if [ -d "../train" ];
|
||||
then
|
||||
rm -rf ../train
|
||||
fi
|
||||
mkdir ../train
|
||||
cd ../train || exit
|
||||
python ${BASEPATH}/../src/launch.py \
|
||||
--nproc_per_node=$2 \
|
||||
--visible_devices=$4 \
|
||||
--server_id=$3 \
|
||||
--training_script=${BASEPATH}/../train.py \
|
||||
--dataset_path=$5 \
|
||||
--pre_trained=$6 \
|
||||
--device_target=$1 &> train.log & # dataset train folder
|
||||
}
|
||||
|
||||
if [ $# -gt 6 ] || [ $# -lt 4 ]
|
||||
then
|
||||
echo "Usage:\n \
|
||||
Ascend: sh run_train.sh Ascend [DEVICE_NUM] [SERVER_IP(x.x.x.x)] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH] [CKPT_PATH]\n \
|
||||
"
|
||||
exit 1
|
||||
fi
|
||||
# check_and_get_Ascend_device(){
|
||||
|
||||
# #device_list=(${1//,/ })
|
||||
# IFS=',' read -ra device_list <<<"$1"
|
||||
# last_device_id=0
|
||||
# first_device_id=8
|
||||
# device_used=(0 0 0 0 0 0 0 0)
|
||||
|
||||
# for var in "${device_list[@]}"
|
||||
# do
|
||||
|
||||
# if [ $((var)) -lt 0 ] || [ $((var)) -ge 8 ]
|
||||
# then
|
||||
# echo "error: device id=${var} is incorrect, device id must be in range [0,8), please check your device id list!"
|
||||
# exit 1
|
||||
# fi
|
||||
|
||||
# if [ ${device_used[$((var))]} -eq 0 ]
|
||||
# then
|
||||
# device_used[ $((var)) ]=1
|
||||
# else
|
||||
# echo "error: device id is duplicate, please check your device id list!"
|
||||
# exit 1
|
||||
# fi
|
||||
|
||||
# if [ ${last_device_id} \< $((var)) ]
|
||||
# then
|
||||
# last_device_id=$((var))
|
||||
# fi
|
||||
# if [ ${first_device_id} \> $((var)) ]
|
||||
# then
|
||||
# first_device_id=$((var))
|
||||
# fi
|
||||
# done
|
||||
|
||||
# device_num=`expr ${last_device_id} - ${first_device_id} + 1`
|
||||
# if [ ${device_num} != ${#device_list[*]} ]
|
||||
# then
|
||||
# echo "error: the Ascend chips used must be continuous, please check your device id list!"
|
||||
# exit 1
|
||||
# fi
|
||||
|
||||
# if [ ${first_device_id} -lt 4 ] && [ ${last_device_id} -ge 4 ]
|
||||
# then
|
||||
# if [ ${first_device_id} != 0 ] || [ ${last_device_id} != 7 ]
|
||||
# then
|
||||
# echo "error: device id list must be in the same group of [0,4) or [4,8) when using Ascend chips."
|
||||
# exit 1
|
||||
# fi
|
||||
# fi
|
||||
|
||||
# echo "${first_device_id},`expr ${last_device_id} + 1`"
|
||||
# }
|
||||
|
||||
# get_hccl_name(){
|
||||
|
||||
# server_ip=$(ifconfig -a | grep inet | grep -v 127.0.0.1 | grep -v inet6 | awk '{print $2}' | tr -d "addr:")
|
||||
# device_num=`expr $2 - $1`
|
||||
# device_id_list=""
|
||||
|
||||
# for(( i=$1 ; i < $2 ; i++ ))
|
||||
# do
|
||||
# device_id_list=${device_id_list}$i
|
||||
# done
|
||||
# hccl_name="hccl_${device_num}p_${device_id_list}_${server_ip}.json"
|
||||
|
||||
# echo ${hccl_name}
|
||||
# }
|
||||
|
||||
|
||||
run_ascend(){
|
||||
|
||||
if [ $# != 3 ] && [ $# != 4 ]
|
||||
then
|
||||
echo "Usage: bash run_train.sh [Ascend] [RANK_TABLE_FILE] [DATASET_PATH] [PRETRAINED_CKPT_PATH](optional)\n"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# first_last_device=$(check_and_get_Ascend_device $2)
|
||||
# #devices=(${first_last_device//,/ })
|
||||
# #IFS=',' read -ra devices <<<"${first_last_device}"
|
||||
# first_device=${first_last_device:0:1}
|
||||
# last_device=${first_last_device:2:1}
|
||||
# device_num=`expr $((last_device)) - $((first_device))`
|
||||
|
||||
|
||||
# #single ascend or multiple ascend
|
||||
# if [ ${device_num} -gt 1 ]
|
||||
# then
|
||||
# ori_path=$(dirname "$(readlink -f "$0")")
|
||||
# #generate hccl config file
|
||||
# cd ../../../../utils/hccl_tools/ || exit
|
||||
# device_num_arg="[${first_device},${last_device})"
|
||||
|
||||
# python hccl_tools.py --device_num=${device_num_arg}
|
||||
|
||||
# hccl_name=$(get_hccl_name ${first_device} ${last_device})
|
||||
|
||||
# if [ ! -e ${hccl_name} ]
|
||||
# then
|
||||
# echo "error: failed to generate the hccl config file!"
|
||||
# exit 1
|
||||
# fi
|
||||
|
||||
# mv ${hccl_name} ${ori_path}
|
||||
# cd ${ori_path} || exit
|
||||
|
||||
# PATH1=$(get_real_path ${hccl_name})
|
||||
|
||||
# if [ ! -f $PATH1 ]
|
||||
# then
|
||||
# echo "error: RANK_TABLE_FILE=$PATH1 is not a file"
|
||||
# exit 1
|
||||
# fi
|
||||
|
||||
# export RANK_TABLE_FILE=$PATH1
|
||||
# fi
|
||||
|
||||
|
||||
PATH1=$(get_real_path $2)
|
||||
PATH2=$(get_real_path $3)
|
||||
|
||||
if [ $# == 4 ]
|
||||
then
|
||||
PATH3=$(get_real_path $4)
|
||||
fi
|
||||
|
||||
if [ ! -f $PATH1 ]
|
||||
then
|
||||
echo "error: RANK_TABLE_FILE=$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 [ $# == 4 ] && [ ! -f $PATH3 ]
|
||||
then
|
||||
echo "error: PRETRAINED_CKPT_PATH=$PATH3 is not a file"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
rank_file_name=${2##*/}
|
||||
IFS='_' read -ra array <<<"${rank_file_name}"
|
||||
device_id_list=${array[2]}
|
||||
first_device=${device_id_list:0:1}
|
||||
device_num=${#device_id_list}
|
||||
|
||||
|
||||
ulimit -u unlimited
|
||||
export DEVICE_NUM=${device_num}
|
||||
export RANK_SIZE=${device_num}
|
||||
export RANK_TABLE_FILE=$PATH1
|
||||
|
||||
export SERVER_ID=0
|
||||
rank_start=$((DEVICE_NUM * SERVER_ID))
|
||||
|
||||
rm -rf ./train
|
||||
mkdir ./train
|
||||
for((i=0; i<${device_num}; i++))
|
||||
do
|
||||
export DEVICE_ID=$((first_device+i))
|
||||
export RANK_ID=$((rank_start + i))
|
||||
mkdir ./train/device$i
|
||||
cp ../*.py ./train/device$i
|
||||
cp *.sh ./train/device$i
|
||||
cp -r ../src ./train/device$i
|
||||
cp -r ../models ./train/device$i
|
||||
cd ./train/device$i || exit
|
||||
echo "start training for rank $RANK_ID, device $DEVICE_ID"
|
||||
env > env.log
|
||||
if [ $# == 3 ]
|
||||
then
|
||||
python train.py --device_target=$1 --run_distribute=True --device_num=$DEVICE_NUM --dataset_path=$PATH2 &> train.log &
|
||||
fi
|
||||
|
||||
if [ $# == 4 ]
|
||||
then
|
||||
python train.py --device_target=$1 --run_distribute=True --device_num=$DEVICE_NUM --dataset_path=$PATH2 --pre_trained=$PATH3 &> train.log &
|
||||
fi
|
||||
|
||||
cd ../.. || exit
|
||||
done
|
||||
}
|
||||
|
||||
# run_gpu(){
|
||||
|
||||
# if [ $# -gt 3 ] || [ $# -lt 2 ]
|
||||
# then
|
||||
# echo "Usage: sh run_train_distribute_quant.sh [GPU] [DATASET_PATH] [PRETRAINED_CKPT_PATH](optional)\n "
|
||||
# exit 1
|
||||
# fi
|
||||
|
||||
# PATH1=$(get_real_path $2)
|
||||
|
||||
# if [ $# == 3 ]
|
||||
# then
|
||||
# PATH2=$(get_real_path $3)
|
||||
# fi
|
||||
|
||||
# if [ ! -d $PATH1 ]
|
||||
# then
|
||||
# echo "error: DATASET_PATH=$PATH1 is not a directory"
|
||||
# exit 1
|
||||
# fi
|
||||
|
||||
# if [ $# == 3 ] && [ ! -f $PATH2 ]
|
||||
# then
|
||||
# echo "error: PRETRAINED_CKPT_PATH=$PATH2 is not a file"
|
||||
# exit 1
|
||||
# fi
|
||||
|
||||
# ulimit -u unlimited
|
||||
# export RANK_SIZE=2
|
||||
# #export CUDA_VISIBLE_DEVICES=1,2
|
||||
|
||||
# rm -rf ./train_parallel
|
||||
# mkdir ./train_parallel
|
||||
# cp ../*.py ./train_parallel
|
||||
# cp *.sh ./train_parallel
|
||||
# cp -r ../src ./train_parallel
|
||||
# cp -r ../models ./train_parallel
|
||||
# cd ./train_parallel || exit
|
||||
# echo "start training"
|
||||
# env > env.log
|
||||
# if [ $# == 2 ]
|
||||
# then
|
||||
# mpirun --allow-run-as-root -n $RANK_SIZE
|
||||
# python train.py --device_target=$1 --dataset_path=$PATH1 &> log &
|
||||
# fi
|
||||
|
||||
# if [ $# == 3 ]
|
||||
# then
|
||||
# mpirun --allow-run-as-root -n $RANK_SIZE
|
||||
# python train.py --device_traget=$1 --dataset_path=$PATH1 --pre_trained=$PATH2 &> log &
|
||||
# fi
|
||||
# cd ..
|
||||
# }
|
||||
|
||||
|
||||
if [ $1 = "Ascend" ] ; then
|
||||
run_ascend "$@"
|
||||
else
|
||||
echo "not support platform"
|
||||
fi;
|
||||
|
||||
echo "Unsupported device target: $1"
|
||||
fi;
|
||||
Loading…
Reference in New Issue