From 900aad441721b5be4ee995894f5eee7b270fe685 Mon Sep 17 00:00:00 2001
From: memg <xumengmeng16@huawei-partners.com>
Date: Fri, 3 Mar 2023 09:27:53 +0000
Subject: [PATCH 1/5] update
 TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/README.md.

Signed-off-by: memg <xumengmeng16@huawei-partners.com>
---
 .../recommendation/DeepCTR_Series_for_TensorFlow/README.md      | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/README.md b/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/README.md
index 6f08d2511..92c51f0c1 100644
--- a/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/README.md
+++ b/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/README.md
@@ -211,4 +211,4 @@ python3 gen_kaggle_criteo_tfrecords.py
 
 #### 训练过程<a name="section1589455252218"></a>
 
-通过“模型训练”中的训练指令启动单卡或者多卡训练。单卡和多卡通过运行不同脚本，支持单卡，8卡网络训练。模型存储路径为${cur_path}/output/$ASCEND_DEVICE_ID，包括训练的log以及checkpoints文件。以8卡训练为例，loss信息在文件${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log中。
\ No newline at end of file
+通过“模型训练”中的训练指令启动单卡或者多卡训练。单卡和多卡通过运行不同脚本，支持单卡网络训练。模型存储路径为${cur_path}/output/$ASCEND_DEVICE_ID，包括训练的log以及checkpoints文件。loss信息在文件${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log中。
\ No newline at end of file
-- 
Gitee


From 09a790c17b603832c81d9ed2077a7cb319ef8ca4 Mon Sep 17 00:00:00 2001
From: memg <xumengmeng16@huawei-partners.com>
Date: Fri, 3 Mar 2023 09:28:11 +0000
Subject: [PATCH 2/5] =?UTF-8?q?=E5=88=A0=E9=99=A4=E6=96=87=E4=BB=B6=20Tens?=
 =?UTF-8?q?orFlow/built-in/recommendation/DeepCTR=5FSeries=5Ffor=5FTensorF?=
 =?UTF-8?q?low/test/train=5FID4032=5FDCNMix=5Fperformance=5F8p=5FRT2.sh?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../train_ID4032_DCNMix_performance_8p_RT2.sh | 153 ------------------
 1 file changed, 153 deletions(-)
 delete mode 100644 TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/test/train_ID4032_DCNMix_performance_8p_RT2.sh

diff --git a/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/test/train_ID4032_DCNMix_performance_8p_RT2.sh b/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/test/train_ID4032_DCNMix_performance_8p_RT2.sh
deleted file mode 100644
index b0430aec6..000000000
--- a/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/test/train_ID4032_DCNMix_performance_8p_RT2.sh
+++ /dev/null
@@ -1,153 +0,0 @@
-#!/bin/bash
-
-#当前路径,不需要修改
-cur_path=`pwd`
-#集合通信参数,不需要修改
-export RANK_SIZE=8
-export RANK_TABLE_FILE=${cur_path}/rank_8p.json
-export JOB_ID=10087
-RANK_ID_START=0
-
-#使能RT2.0
-export ENABLE_RUNTIME_V2=1
-# 数据集路径,保持为空,不需要修改
-data_path=""
-#基础参数，需要模型审视修改
-#网络名称，同目录名称
-Network="DCNMix_ID4032_for_TensorFlow"
-#训练epoch
-train_epochs=1
-#训练batch_size
-batch_size=10240
-#训练step
-train_steps=100
-#学习率
-learning_rate=
-
-#维测参数，precision_mode需要模型审视修改
-precision_mode="allow_fp32_to_fp16"
-#维持参数，以下不需要修改
-over_dump=False
-data_dump_flag=False
-data_dump_step="10"
-profiling=False
-
-# 帮助信息，不需要修改
-if [[ $1 == --help || $1 == -h ]];then
-    echo"usage:./train_performance_1P.sh <args>"
-    echo " "
-    echo "parameter explain:
-    --precision_mode         precision mode(allow_fp32_to_fp16/force_fp16/must_keep_origin_dtype/allow_mix_precision)
-    --over_dump		           if or not over detection, default is False
-    --data_dump_flag		     data dump flag, default is False
-    --data_dump_step		     data dump step, default is 10
-    --profiling		           if or not profiling for performance debug, default is False
-	--data_path		           source data of training
-    -h/--help		             show help message
-    "
-    exit 1
-fi
-
-#参数校验，不需要修改
-for para in $*
-do
-    if [[ $para == --precision_mode* ]];then
-        precision_mode=`echo ${para#*=}`
-    elif [[ $para == --over_dump* ]];then
-        over_dump=`echo ${para#*=}`
-        over_dump_path=${cur_path}/output/overflow_dump
-        mkdir -p ${over_dump_path}
-    elif [[ $para == --data_dump_flag* ]];then
-        data_dump_flag=`echo ${para#*=}`
-        data_dump_path=${cur_path}/output/data_dump
-        mkdir -p ${data_dump_path}
-    elif [[ $para == --data_dump_step* ]];then
-        data_dump_step=`echo ${para#*=}`
-    elif [[ $para == --profiling* ]];then
-        profiling=`echo ${para#*=}`
-        profiling_dump_path=${cur_path}/output/profiling
-        mkdir -p ${profiling_dump_path}
-    elif [[ $para == --data_path* ]];then
-        data_path=`echo ${para#*=}`
-    fi
-done
-
-#校验是否传入data_path,不需要修改
-if [[ $data_path == "" ]];then
-    echo "[Error] para \"data_path\" must be confing"
-    exit 1
-fi
-
-#训练开始时间，不需要修改
-start_time=$(date +%s)
-
-#进入训练脚本目录，需要模型审视修改
-cd $cur_path/../examples
-
-for((RANK_ID=$RANK_ID_START;RANK_ID<$((RANK_SIZE+RANK_ID_START));RANK_ID++));
-do
-    #设置环境变量，不需要修改
-    echo "Device ID: $RANK_ID"
-    export RANK_ID=$RANK_ID
-    export ASCEND_DEVICE_ID=$RANK_ID
-
-    #创建DeviceID输出目录，不需要修改
-    if [ -d ${cur_path}/output/${ASCEND_DEVICE_ID} ];then
-        rm -rf ${cur_path}/output/${ASCEND_DEVICE_ID}
-        mkdir -p ${cur_path}/output/$ASCEND_DEVICE_ID/ckpt
-    else
-        mkdir -p ${cur_path}/output/$ASCEND_DEVICE_ID/ckpt
-    fi
-    
-    #执行训练脚本，以下传参不需要修改，其他需要模型审视修改
-    #--data_dir, --model_dir, --precision_mode, --over_dump, --over_dump_path，--data_dump_flag，--data_dump_step，--data_dump_path，--profiling，--profiling_dump_path
-    nohup python3 run_dcnmix.py \
-        --data_path=${data_path} \
-        --train_batch_size=${batch_size} \
-        --eval_batch_size=${batch_size} \
-        --num_epochs=${train_epochs} \
-        --max_steps=${train_steps} \
-        --output_dir=${cur_path}/output/$ASCEND_DEVICE_ID/ckpt > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
-done 
-wait
-
-#训练结束时间，不需要修改
-end_time=$(date +%s)
-e2e_time=$(( $end_time - $start_time ))
-
-
-#结果打印，不需要修改
-echo "------------------ Final result ------------------"
-# #输出性能FPS，需要模型审视修改
-fps=`grep "examples\/sec" $cur_path/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log | awk '{print $2}'|tail -n +5 |awk '{sum+=$1} END {print sum/NR}'`
-FPS=`awk 'BEGIN{printf "%.2f\n", '${fps}'}'`
-# #打印，不需要修改
-echo "Final Performance item/sec : $FPS"
-
-echo "E2E Training Duration sec : $e2e_time"
-
-#性能看护结果汇总
-#训练用例信息，不需要修改
-BatchSize=${batch_size}
-DeviceType=`uname -m`
-CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'RT2'_'perf'
-
-##获取性能数据，不需要修改
-#吞吐量
-TrainingTime=`awk 'BEGIN{printf "%.6f\n",'${BatchSize}'/'${FPS}'}'`
-
-ActualFPS=${FPS}
-grep ":loss =" $cur_path/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log| awk '{print $3}' | sed 's/,//g' > $cur_path/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt
-#最后一个迭代loss值，不需要修改
-ActualLoss=`awk 'END {print}' $cur_path/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt`
-
-#关键信息打印到${CaseName}.log中，不需要修改
-echo "Network = ${Network}" > $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "RankSize = ${RANK_SIZE}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "BatchSize = ${BatchSize}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "DeviceType = ${DeviceType}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "CaseName = ${CaseName}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "ActualFPS = ${ActualFPS}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "TrainingTime = ${TrainingTime}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "ActualLoss = ${ActualLoss}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-- 
Gitee


From 95ab3057a219293dcbfabb5cbc3d5e1908766760 Mon Sep 17 00:00:00 2001
From: memg <xumengmeng16@huawei-partners.com>
Date: Fri, 3 Mar 2023 09:28:21 +0000
Subject: [PATCH 3/5] =?UTF-8?q?=E5=88=A0=E9=99=A4=E6=96=87=E4=BB=B6=20Tens?=
 =?UTF-8?q?orFlow/built-in/recommendation/DeepCTR=5FSeries=5Ffor=5FTensorF?=
 =?UTF-8?q?low/test/train=5FID4032=5FDCNMix=5Fperformance=5F8p.sh?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../train_ID4032_DCNMix_performance_8p.sh     | 150 ------------------
 1 file changed, 150 deletions(-)
 delete mode 100644 TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/test/train_ID4032_DCNMix_performance_8p.sh

diff --git a/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/test/train_ID4032_DCNMix_performance_8p.sh b/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/test/train_ID4032_DCNMix_performance_8p.sh
deleted file mode 100644
index a19701a8b..000000000
--- a/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/test/train_ID4032_DCNMix_performance_8p.sh
+++ /dev/null
@@ -1,150 +0,0 @@
-#!/bin/bash
-
-#当前路径,不需要修改
-cur_path=`pwd`
-#集合通信参数,不需要修改
-export RANK_SIZE=8
-export RANK_TABLE_FILE=${cur_path}/rank_8p.json
-export JOB_ID=10087
-RANK_ID_START=0
-# 数据集路径,保持为空,不需要修改
-data_path=""
-#基础参数，需要模型审视修改
-#网络名称，同目录名称
-Network="DCNMix_ID4032_for_TensorFlow"
-#训练epoch
-train_epochs=1
-#训练batch_size
-batch_size=10240
-#训练step
-train_steps=100
-#学习率
-learning_rate=
-
-#维测参数，precision_mode需要模型审视修改
-precision_mode="allow_fp32_to_fp16"
-#维持参数，以下不需要修改
-over_dump=False
-data_dump_flag=False
-data_dump_step="10"
-profiling=False
-
-# 帮助信息，不需要修改
-if [[ $1 == --help || $1 == -h ]];then
-    echo"usage:./train_performance_1P.sh <args>"
-    echo " "
-    echo "parameter explain:
-    --precision_mode         precision mode(allow_fp32_to_fp16/force_fp16/must_keep_origin_dtype/allow_mix_precision)
-    --over_dump		           if or not over detection, default is False
-    --data_dump_flag		     data dump flag, default is False
-    --data_dump_step		     data dump step, default is 10
-    --profiling		           if or not profiling for performance debug, default is False
-	--data_path		           source data of training
-    -h/--help		             show help message
-    "
-    exit 1
-fi
-
-#参数校验，不需要修改
-for para in $*
-do
-    if [[ $para == --precision_mode* ]];then
-        precision_mode=`echo ${para#*=}`
-    elif [[ $para == --over_dump* ]];then
-        over_dump=`echo ${para#*=}`
-        over_dump_path=${cur_path}/output/overflow_dump
-        mkdir -p ${over_dump_path}
-    elif [[ $para == --data_dump_flag* ]];then
-        data_dump_flag=`echo ${para#*=}`
-        data_dump_path=${cur_path}/output/data_dump
-        mkdir -p ${data_dump_path}
-    elif [[ $para == --data_dump_step* ]];then
-        data_dump_step=`echo ${para#*=}`
-    elif [[ $para == --profiling* ]];then
-        profiling=`echo ${para#*=}`
-        profiling_dump_path=${cur_path}/output/profiling
-        mkdir -p ${profiling_dump_path}
-    elif [[ $para == --data_path* ]];then
-        data_path=`echo ${para#*=}`
-    fi
-done
-
-#校验是否传入data_path,不需要修改
-if [[ $data_path == "" ]];then
-    echo "[Error] para \"data_path\" must be confing"
-    exit 1
-fi
-
-#训练开始时间，不需要修改
-start_time=$(date +%s)
-
-#进入训练脚本目录，需要模型审视修改
-cd $cur_path/../examples
-
-for((RANK_ID=$RANK_ID_START;RANK_ID<$((RANK_SIZE+RANK_ID_START));RANK_ID++));
-do
-    #设置环境变量，不需要修改
-    echo "Device ID: $RANK_ID"
-    export RANK_ID=$RANK_ID
-    export ASCEND_DEVICE_ID=$RANK_ID
-
-    #创建DeviceID输出目录，不需要修改
-    if [ -d ${cur_path}/output/${ASCEND_DEVICE_ID} ];then
-        rm -rf ${cur_path}/output/${ASCEND_DEVICE_ID}
-        mkdir -p ${cur_path}/output/$ASCEND_DEVICE_ID/ckpt
-    else
-        mkdir -p ${cur_path}/output/$ASCEND_DEVICE_ID/ckpt
-    fi
-    
-    #执行训练脚本，以下传参不需要修改，其他需要模型审视修改
-    #--data_dir, --model_dir, --precision_mode, --over_dump, --over_dump_path，--data_dump_flag，--data_dump_step，--data_dump_path，--profiling，--profiling_dump_path
-    nohup python3 run_dcnmix.py \
-        --data_path=${data_path} \
-        --train_batch_size=${batch_size} \
-        --eval_batch_size=${batch_size} \
-        --num_epochs=${train_epochs} \
-        --max_steps=${train_steps} \
-        --output_dir=${cur_path}/output/$ASCEND_DEVICE_ID/ckpt > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
-done 
-wait
-
-#训练结束时间，不需要修改
-end_time=$(date +%s)
-e2e_time=$(( $end_time - $start_time ))
-
-
-#结果打印，不需要修改
-echo "------------------ Final result ------------------"
-# #输出性能FPS，需要模型审视修改
-fps=`grep "examples\/sec" $cur_path/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log | awk '{print $2}'|tail -n +5 |awk '{sum+=$1} END {print sum/NR}'`
-FPS=`awk 'BEGIN{printf "%.2f\n", '${fps}'}'`
-# #打印，不需要修改
-echo "Final Performance item/sec : $FPS"
-
-echo "E2E Training Duration sec : $e2e_time"
-
-#性能看护结果汇总
-#训练用例信息，不需要修改
-BatchSize=${batch_size}
-DeviceType=`uname -m`
-CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'perf'
-
-##获取性能数据，不需要修改
-#吞吐量
-TrainingTime=`awk 'BEGIN{printf "%.6f\n",'${BatchSize}'/'${FPS}'}'`
-
-ActualFPS=${FPS}
-grep ":loss =" $cur_path/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log| awk '{print $3}' | sed 's/,//g' > $cur_path/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt
-#最后一个迭代loss值，不需要修改
-ActualLoss=`awk 'END {print}' $cur_path/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt`
-
-#关键信息打印到${CaseName}.log中，不需要修改
-echo "Network = ${Network}" > $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "RankSize = ${RANK_SIZE}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "BatchSize = ${BatchSize}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "DeviceType = ${DeviceType}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "CaseName = ${CaseName}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "ActualFPS = ${ActualFPS}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "TrainingTime = ${TrainingTime}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "ActualLoss = ${ActualLoss}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-- 
Gitee


From 34596471832b1581771470180bf91c81002eaa25 Mon Sep 17 00:00:00 2001
From: memg <xumengmeng16@huawei-partners.com>
Date: Fri, 3 Mar 2023 09:28:31 +0000
Subject: [PATCH 4/5] =?UTF-8?q?=E5=88=A0=E9=99=A4=E6=96=87=E4=BB=B6=20Tens?=
 =?UTF-8?q?orFlow/built-in/recommendation/DeepCTR=5FSeries=5Ffor=5FTensorF?=
 =?UTF-8?q?low/test/train=5FID4032=5FDCNMix=5Ffull=5F8p.sh?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../test/train_ID4032_DCNMix_full_8p.sh       | 153 ------------------
 1 file changed, 153 deletions(-)
 delete mode 100644 TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/test/train_ID4032_DCNMix_full_8p.sh

diff --git a/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/test/train_ID4032_DCNMix_full_8p.sh b/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/test/train_ID4032_DCNMix_full_8p.sh
deleted file mode 100644
index 60f518698..000000000
--- a/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/test/train_ID4032_DCNMix_full_8p.sh
+++ /dev/null
@@ -1,153 +0,0 @@
-#!/bin/bash
-
-#当前路径,不需要修改
-cur_path=`pwd`
-#集合通信参数,不需要修改
-export RANK_SIZE=8
-export RANK_TABLE_FILE=${cur_path}/rank_8p.json
-export JOB_ID=10087
-RANK_ID_START=0
-# 数据集路径,保持为空,不需要修改
-data_path=""
-#基础参数，需要模型审视修改
-#网络名称，同目录名称
-Network="DCNMix_ID4032_for_TensorFlow"
-#训练epoch
-train_epochs=4
-#训练batch_size
-batch_size=10240
-#训练step
-train_steps=
-#学习率
-learning_rate=
-
-#维测参数，precision_mode需要模型审视修改
-precision_mode="allow_fp32_to_fp16"
-#维持参数，以下不需要修改
-over_dump=False
-data_dump_flag=False
-data_dump_step="10"
-profiling=False
-
-# 帮助信息，不需要修改
-if [[ $1 == --help || $1 == -h ]];then
-    echo"usage:./train_performance_1P.sh <args>"
-    echo " "
-    echo "parameter explain:
-    --precision_mode         precision mode(allow_fp32_to_fp16/force_fp16/must_keep_origin_dtype/allow_mix_precision)
-    --over_dump		           if or not over detection, default is False
-    --data_dump_flag		     data dump flag, default is False
-    --data_dump_step		     data dump step, default is 10
-    --profiling		           if or not profiling for performance debug, default is False
-	--data_path		           source data of training
-    -h/--help		             show help message
-    "
-    exit 1
-fi
-
-#参数校验，不需要修改
-for para in $*
-do
-    if [[ $para == --precision_mode* ]];then
-        precision_mode=`echo ${para#*=}`
-    elif [[ $para == --over_dump* ]];then
-        over_dump=`echo ${para#*=}`
-        over_dump_path=${cur_path}/output/overflow_dump
-        mkdir -p ${over_dump_path}
-    elif [[ $para == --data_dump_flag* ]];then
-        data_dump_flag=`echo ${para#*=}`
-        data_dump_path=${cur_path}/output/data_dump
-        mkdir -p ${data_dump_path}
-    elif [[ $para == --data_dump_step* ]];then
-        data_dump_step=`echo ${para#*=}`
-    elif [[ $para == --profiling* ]];then
-        profiling=`echo ${para#*=}`
-        profiling_dump_path=${cur_path}/output/profiling
-        mkdir -p ${profiling_dump_path}
-    elif [[ $para == --data_path* ]];then
-        data_path=`echo ${para#*=}`
-    fi
-done
-
-#校验是否传入data_path,不需要修改
-if [[ $data_path == "" ]];then
-    echo "[Error] para \"data_path\" must be confing"
-    exit 1
-fi
-
-#训练开始时间，不需要修改
-start_time=$(date +%s)
-
-#进入训练脚本目录，需要模型审视修改
-cd $cur_path/../examples
-
-for((RANK_ID=$RANK_ID_START;RANK_ID<$((RANK_SIZE+RANK_ID_START));RANK_ID++));
-do
-    #设置环境变量，不需要修改
-    echo "Device ID: $RANK_ID"
-    export RANK_ID=$RANK_ID
-    export ASCEND_DEVICE_ID=$RANK_ID
-
-    #创建DeviceID输出目录，不需要修改
-    if [ -d ${cur_path}/output/${ASCEND_DEVICE_ID} ];then
-        rm -rf ${cur_path}/output/${ASCEND_DEVICE_ID}
-        mkdir -p ${cur_path}/output/$ASCEND_DEVICE_ID/ckpt
-    else
-        mkdir -p ${cur_path}/output/$ASCEND_DEVICE_ID/ckpt
-    fi
-    
-    #执行训练脚本，以下传参不需要修改，其他需要模型审视修改
-    #--data_dir, --model_dir, --precision_mode, --over_dump, --over_dump_path，--data_dump_flag，--data_dump_step，--data_dump_path，--profiling，--profiling_dump_path
-    nohup python3 run_dcnmix.py \
-        --data_path=${data_path} \
-        --train_batch_size=${batch_size} \
-        --eval_batch_size=${batch_size} \
-        --num_epochs=${train_epochs} \
-        --output_dir=${cur_path}/output/$ASCEND_DEVICE_ID/ckpt > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
-done 
-wait
-
-#训练结束时间，不需要修改
-end_time=$(date +%s)
-e2e_time=$(( $end_time - $start_time ))
-
-
-#结果打印，不需要修改
-echo "------------------ Final result ------------------"
-# #输出性能FPS，需要模型审视修改
-fps=`grep "examples\/sec" $cur_path/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log | awk '{print $2}'|tail -n +5 |awk '{sum+=$1} END {print sum/NR}'`
-FPS=`awk 'BEGIN{printf "%.2f\n", '${fps}'}'`
-# #打印，不需要修改
-echo "Final Performance item/sec : $FPS"
-
-# #输出训练精度,需要模型审视修改
-train_accuracy=`grep "AUC = " $cur_path/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log | awk 'END {print $9}' | sed 's/,//g'`
-echo "Final Train Accuracy : ${train_accuracy}"
-echo "E2E Training Duration sec : $e2e_time"
-
-#性能看护结果汇总
-#训练用例信息，不需要修改
-BatchSize=${batch_size}
-DeviceType=`uname -m`
-CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'accu'
-
-##获取性能数据，不需要修改
-#吞吐量
-TrainingTime=`awk 'BEGIN{printf "%.6f\n",'${BatchSize}'/'${FPS}'}'`
-
-ActualFPS=${FPS}
-grep ":loss =" $cur_path/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log| awk '{print $3}' | sed 's/,//g' > $cur_path/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt
-#最后一个迭代loss值，不需要修改
-ActualLoss=`awk 'END {print}' $cur_path/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt`
-
-#关键信息打印到${CaseName}.log中，不需要修改
-echo "Network = ${Network}" > $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "RankSize = ${RANK_SIZE}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "BatchSize = ${BatchSize}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "DeviceType = ${DeviceType}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "CaseName = ${CaseName}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "ActualFPS = ${ActualFPS}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "TrainingTime = ${TrainingTime}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "ActualLoss = ${ActualLoss}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "E2ETrainingTime = ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
-- 
Gitee


From df522d3ccc26e21e98429bab7d6947e87e531c23 Mon Sep 17 00:00:00 2001
From: memg <xumengmeng16@huawei-partners.com>
Date: Mon, 6 Mar 2023 06:29:29 +0000
Subject: [PATCH 5/5] update
 TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/README.md.

Signed-off-by: memg <xumengmeng16@huawei-partners.com>
---
 .../recommendation/DeepCTR_Series_for_TensorFlow/README.md      | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/README.md b/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/README.md
index 92c51f0c1..6f08d2511 100644
--- a/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/README.md
+++ b/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/README.md
@@ -211,4 +211,4 @@ python3 gen_kaggle_criteo_tfrecords.py
 
 #### 训练过程<a name="section1589455252218"></a>
 
-通过“模型训练”中的训练指令启动单卡或者多卡训练。单卡和多卡通过运行不同脚本，支持单卡网络训练。模型存储路径为${cur_path}/output/$ASCEND_DEVICE_ID，包括训练的log以及checkpoints文件。loss信息在文件${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log中。
\ No newline at end of file
+通过“模型训练”中的训练指令启动单卡或者多卡训练。单卡和多卡通过运行不同脚本，支持单卡，8卡网络训练。模型存储路径为${cur_path}/output/$ASCEND_DEVICE_ID，包括训练的log以及checkpoints文件。以8卡训练为例，loss信息在文件${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log中。
\ No newline at end of file
-- 
Gitee