From f12e7c7f275b8c6351e56ec2bb36eed279b2f98d Mon Sep 17 00:00:00 2001
From: limingxing517 <limingxing517@163.com>
Date: Wed, 19 Apr 2023 10:17:47 +0800
Subject: [PATCH 1/3] update

---
 .../MiniGo_ID0629_for_TensorFlow/dual_net.py  |   2 +-
 .../test/.train_full_1p.sh.swp                | Bin 0 -> 16384 bytes
 .../test/train_full_1p.sh                     |  17 ++++++++++---
 .../test/train_full_8p.sh                     |  24 +++++++++++++-----
 .../test/train_performance_1p.sh              |   8 +++++-
 5 files changed, 39 insertions(+), 12 deletions(-)
 create mode 100644 TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/.train_full_1p.sh.swp

diff --git a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/dual_net.py b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/dual_net.py
index 8f2e173a1..d89f77a1b 100644
--- a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/dual_net.py
+++ b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/dual_net.py
@@ -683,7 +683,7 @@ def _get_nontpu_estimator():
     session_config = tf.ConfigProto(allow_soft_placement=True)
     custom_op = session_config.graph_options.rewrite_options.custom_optimizers.add()
     custom_op.name = 'NpuOptimizer'
-    custom_op.parameter_map["precision_mode"].s = tf.compat.as_bytes("allow_mix_precision")
+    custom_op.parameter_map["precision_mode"].s = tf.compat.as_bytes("must_keep_origin_dtype")
     #session_config = npu_config_proto(config_proto=tf.ConfigProto())
     session_config.gpu_options.allow_growth = True
 
diff --git a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/.train_full_1p.sh.swp b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/.train_full_1p.sh.swp
new file mode 100644
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diff --git a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_1p.sh b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_1p.sh
index a6f75350e..566d9265c 100644
--- a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_1p.sh
+++ b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_1p.sh
@@ -38,6 +38,8 @@ for para in $*
 do
    if [[ $para  == --data_path* ]];then
       data_path=`echo ${para#*=}`
+   elif [[ $para == --precision_mode* ]];then
+      precision_mode=`echo ${para#*=}`
    elif [[ $para == --dynamic_input* ]];then
       dynamic_input=`echo ${para#*=}`  	
    fi
@@ -48,6 +50,11 @@ if [[ $data_path  == "" ]];then
     exit 1
 fi
 
+if [[ $precision_mode == "must_keep_origin_dtype" ]];then
+   sed -i "s|allow_mix_precision|must_keep_origin_dtype|g" $cur_path/../dual_net.py
+fi
+
+
 ##############执行训练##########
 cd $cur_path
 
@@ -65,7 +72,7 @@ wait
 
 start=$(date +%s)
 #(Step3)训练
-python3 train.py --training_data_path=$data_path --steps_to_train=$train_steps --train_batch_size=$batch_size --work_dir=$cur_path/estimator_working_dir --export_path=$cur_path/outputs/models/000001-first_generation --dynamic_input=${dynamic_input}> $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
+python3 train.py --training_data_path=$data_path --steps_to_train=$train_steps --train_batch_size=$batch_size --work_dir=$cur_path/estimator_working_dir --export_path=$cur_path/outputs/models/000001-first_generation --dynamic_input=${dynamic_input}  > $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log 2>&1 &
 wait
 end=$(date +%s)
 e2etime=$(( $end - $start ))
@@ -79,7 +86,11 @@ BatchSize=${batch_size}
 #设备类型，自动获取
 DeviceType=`uname -m`
 #用例名称，自动获取
-CaseName=${Network}_bs${BatchSize}_${RankSize}'p'_'acc'
+if [[ $precision_mode == "must_keep_origin_dtype" ]];then
+    CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'fp32'_'acc'
+else
+    CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'acc'
+fi
 
 #获取性能
 TrainingTime=`grep "tensorflow:global_step/sec" $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log|awk 'END {print $2}'`
@@ -101,4 +112,4 @@ echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${Cas
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainAccuracy = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "E2ETrainingTime = ${e2etime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "DynamicInput = ${dynamic_input}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
diff --git a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_8p.sh b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_8p.sh
index 8cd78e2f2..b8ad2e3b0 100644
--- a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_8p.sh
+++ b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_full_8p.sh
@@ -38,10 +38,12 @@ for para in $*
 do
    if [[ $para  == --data_path* ]];then
       data_path=`echo ${para#*=}`
-    elif [[ $para == --bind_core* ]]; then
-        bind_core=`echo ${para#*=}`
-        name_bind="_bindcore"
-	elif [[ $para == --dynamic_input* ]];then
+   elif [[ $para == --precision_mode* ]];then
+      precision_mode=`echo ${para#*=}`
+   elif [[ $para == --bind_core* ]]; then
+      bind_core=`echo ${para#*=}`
+      name_bind="_bindcore"
+   elif [[ $para == --dynamic_input* ]];then
       dynamic_input=`echo ${para#*=}` 
    fi
 done
@@ -51,6 +53,11 @@ if [[ $data_path  == "" ]];then
     exit 1
 fi
 
+if [[ $precision_mode == "must_keep_origin_dtype" ]];then
+   sed -i "s|allow_mix_precision|must_keep_origin_dtype|g" $cur_path/../dual_net.py
+fi
+
+
 ##############执行训练##########
 cd $cur_path
 
@@ -105,8 +112,11 @@ BatchSize=${batch_size}
 #设备类型，自动获取
 DeviceType=`uname -m`
 #用例名称，自动获取
-CaseName=${Network}_bs${BatchSize}_${RankSize}'p'_'acc'
-
+if [[ $precision_mode == "must_keep_origin_dtype" ]];then
+    CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'fp32'_'acc'
+else
+    CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'acc'
+fi
 #获取性能
 TrainingTime=`grep "tensorflow:global_step/sec" $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log|awk 'END {print $2}'`
 wait
@@ -127,4 +137,4 @@ echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${Cas
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainAccuracy = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "E2ETrainingTime = ${e2etime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "DynamicInput = ${dynamic_input}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
diff --git a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_1p.sh
index 2b9da3177..073205e5e 100644
--- a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_1p.sh
+++ b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_1p.sh
@@ -38,6 +38,8 @@ for para in $*
 do
    if [[ $para  == --data_path* ]];then
       data_path=`echo ${para#*=}`
+   elif [[ $para == --precision_mode* ]];then
+      precision_mode=`echo ${para#*=}`
    elif [[ $para == --dynamic_input* ]];then
       dynamic_input=`echo ${para#*=}`  	
    fi
@@ -48,6 +50,10 @@ if [[ $data_path  == "" ]];then
     exit 1
 fi
 
+if [[ $precision_mode == "must_keep_origin_dtype" ]];then
+   sed -i "s|allow_mix_precision|must_keep_origin_dtype|g" $cur_path/../dual_net.py
+fi
+
 ##############执行训练##########
 cd $cur_path
 
@@ -108,4 +114,4 @@ echo "ActualFPS = ${ActualFPS}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${Cas
 echo "ActualLoss = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "TrainAccuracy = ${ActualLoss}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "E2ETrainingTime = ${e2etime}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "DynamicInput = ${dynamic_input}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
\ No newline at end of file
+echo "DynamicInput = ${dynamic_input}" >> $cur_path/test/output/$ASCEND_DEVICE_ID/${CaseName}.log
-- 
Gitee


From 1f0f413c9db0d7adaa533ed961c3e8f0d8aadf0d Mon Sep 17 00:00:00 2001
From: limingxing517 <limingxing517@163.com>
Date: Wed, 19 Apr 2023 10:18:34 +0800
Subject: [PATCH 2/3] update

---
 .../test/.train_full_1p.sh.swp                  | Bin 16384 -> 0 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 delete mode 100644 TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/.train_full_1p.sh.swp

diff --git a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/.train_full_1p.sh.swp b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/.train_full_1p.sh.swp
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index 390faf4fd7fa56ebb9e0e01052578c815667576f..0000000000000000000000000000000000000000
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From 121b2041a403aee4a3574303638e4f17feaa4a8d Mon Sep 17 00:00:00 2001
From: limingxing517 <limingxing517@163.com>
Date: Wed, 19 Apr 2023 10:24:10 +0800
Subject: [PATCH 3/3] update

---
 .../MiniGo_ID0629_for_TensorFlow/dual_net.py               | 2 +-
 .../test/train_performance_1p.sh                           | 7 +++++--
 2 files changed, 6 insertions(+), 3 deletions(-)

diff --git a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/dual_net.py b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/dual_net.py
index d89f77a1b..8f2e173a1 100644
--- a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/dual_net.py
+++ b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/dual_net.py
@@ -683,7 +683,7 @@ def _get_nontpu_estimator():
     session_config = tf.ConfigProto(allow_soft_placement=True)
     custom_op = session_config.graph_options.rewrite_options.custom_optimizers.add()
     custom_op.name = 'NpuOptimizer'
-    custom_op.parameter_map["precision_mode"].s = tf.compat.as_bytes("must_keep_origin_dtype")
+    custom_op.parameter_map["precision_mode"].s = tf.compat.as_bytes("allow_mix_precision")
     #session_config = npu_config_proto(config_proto=tf.ConfigProto())
     session_config.gpu_options.allow_growth = True
 
diff --git a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_1p.sh b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_1p.sh
index 073205e5e..212394cd3 100644
--- a/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_1p.sh
+++ b/TensorFlow/built-in/cv/image_classification/MiniGo_ID0629_for_TensorFlow/test/train_performance_1p.sh
@@ -92,8 +92,11 @@ BatchSize=${batch_size}
 #设备类型，自动获取
 DeviceType=`uname -m`
 #用例名称，自动获取
-CaseName=${Network}_bs${BatchSize}_${RankSize}'p'_'perf'
-
+if [[ $precision_mode == "must_keep_origin_dtype" ]];then
+    CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'fp32'_'perf'
+else
+    CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'perf'
+fi
 #获取性能
 TrainingTime=`grep "tensorflow:global_step/sec" $cur_path/test/output/$ASCEND_DEVICE_ID/train_$ASCEND_DEVICE_ID.log|awk 'END {print $2}'`
 wait
-- 
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