[dy2static-tipc] add txt config for dy2static test

test_tipc/configs/MobileNetV1/MobileNetV1_train_dy2static_python.txt

+=========================== base_train ===========================
+model_name:MobileNetV2
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:to_static_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/MobileNetV2/MobileNetV2.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Global.eval_during_train=False -o Global.save_interval=2 -o Global.print_batch_step=1
+pact_train:null
+fpgm_train:null
+distill_train:null
+to_static_train:-o Global.to_static=True
+null:null
+##
+=========================== amp_train ===========================
+model_name:MobileNetV1
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:to_static_train
+amp_train:tools/train.py -c ppcls/configs/ImageNet/MobileNetV1/MobileNetV1.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=128 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Global.eval_during_train=False -o Global.save_interval=2 -o Global.print_batch_step=1
+pact_train:null
+fpgm_train:null
+distill_train:null
+to_static_train:-o Global.to_static=True
+null:null
+##

test_tipc/configs/MobileNetV2/MobileNetV2_train_dy2static_python.txt

+=========================== base_train ===========================
+model_name:MobileNetV2
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:to_static_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/MobileNetV2/MobileNetV2.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Global.eval_during_train=False -o Global.save_interval=2 -o Global.print_batch_step=1
+pact_train:null
+fpgm_train:null
+distill_train:null
+to_static_train:-o Global.to_static=True
+null:null
+##
+=========================== amp_train ===========================
+model_name:MobileNetV2
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:to_static_train
+amp_train:tools/train.py -c ppcls/configs/ImageNet/MobileNetV2/MobileNetV2.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=128 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Global.eval_during_train=False -o Global.save_interval=2 -o Global.print_batch_step=1
+pact_train:null
+fpgm_train:null
+distill_train:null
+to_static_train:-o Global.to_static=True
+null:null
+##

test_tipc/configs/MobileNetV3/MobileNetV3_large_x1_0_train_dy2static_python.txt

+=========================== base_train ===========================
+model_name:MobileNetV3_large_x1_0
+python:python3.7
+gpu_list:0
+-o Global.device:cpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:to_static_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Global.eval_during_train=False -o Global.save_interval=2 -o Global.print_batch_step=1 -o Global.print_batch_step=1 -o Global.print_batch_step=1 -o Global.print_batch_step=1 -o Global.print_batch_step=1 -o Global.print_batch_step=1 -o Global.print_batch_step=1 -o Global.print_batch_step=1
+pact_train:null
+fpgm_train:null
+distill_train:null
+to_static_train:-o Global.to_static=True
+null:null
+##
+=========================== amp_train ===========================
+model_name:MobileNetV3_large_x1_0
+python:python3.7
+gpu_list:0|0,1
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:amp_train
+amp_train:tools/train.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o AMP.scale_loss=128 -o AMP.use_dynamic_loss_scaling=True -o AMP.level=O2 -o Global.eval_during_train=False -o Global.save_interval=2
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##

test_tipc/test_train_dy2static_python.sh

 #!/bin/bash
 source test_tipc/common_func.sh
 
+IFS=$'\n'
+BASE_CONFIG_FILE=$1
 # always use the lite_train_lite_infer mode to speed. Modify the config file.
 MODE=lite_train_lite_infer
 BASEDIR=$(dirname "$0")
 
-FILENAME=$1
-sed -i 's/gpu_list.*$/gpu_list:0/g' $FILENAME
-sed -i '23,$d' $FILENAME
-#sed -i 's/-o Global.device:.*$/-o Global.device:cpu/g' $FILENAME
-sed -i '16s/$/ -o Global.print_batch_step=1/' ${FILENAME}
-
-
 # get the log path.
-IFS=$'\n'
-dataline=$(cat ${FILENAME})
+dataline=$(cat ${BASE_CONFIG_FILE})
 lines=(${dataline})
 model_name=$(func_parser_value "${lines[1]}")
 LOG_PATH="./test_tipc/output/${model_name}/${MODE}"
@@ -25,35 +19,54 @@ status_log="${LOG_PATH}/results_python.log"
 # make cudnn algorithm deterministic, such as conv.
 export FLAGS_cudnn_deterministic=True
 
-# start dygraph train
-dygraph_output=$LOG_PATH/python_train_infer_dygraph_output.txt
-dygraph_loss=$LOG_PATH/dygraph_loss.txt
-sed -i '15ctrainer:norm_train' ${FILENAME}
-cmd="bash test_tipc/test_train_inference_python.sh ${FILENAME} $MODE >$dygraph_output 2>&1"
-echo $cmd
-eval $cmd
-
-# start dy2static train
-dy2static_output=$LOG_PATH/python_train_infer_dy2static_output.txt
-dy2static_loss=$LOG_PATH/dy2static_loss.txt
-sed -i '15ctrainer:to_static_train' ${FILENAME}
-cmd="bash test_tipc/test_train_inference_python.sh ${FILENAME} $MODE >$dy2static_output 2>&1"
-echo $cmd
-eval $cmd
-
-# analysis and compare the losses. 
-dyout=`cat $dy2static_output | python test_tipc/extract_loss.py -v 'Iter:' -e 'loss: {%f},'`
-stout=`cat $dygraph_output   | python test_tipc/extract_loss.py -v 'Iter:' -e 'loss: {%f},'  `
-echo $dyout > $dygraph_loss
-echo $stout > $dy2static_loss
-diff_log=$LOG_PATH/diff_log.txt
-diff_cmd="diff -w $dygraph_loss $dy2static_loss | tee $diff_log"
-eval $diff_cmd
-last_status=$?
-if [ "$dyout" = "" ]; then
-    status_check 2 $diff_cmd $status_log $model_name $diff_log
-fi
-if [ "$stout" = "" ]; then
-    status_check 2 $diff_cmd $status_log $model_name $diff_log
-fi
-status_check $last_status $diff_cmd $status_log $model_name $diff_log
+# read the base config and parse and run the sub commands
+config_line_numbers=`cat ${BASE_CONFIG_FILE} | grep -n "============" | cut -d':' -f1`
+for cln in $config_line_numbers
+do
+    # change IFS to prevent \n is parsed as delimiter.
+    IFS=""
+    config_lines=$(cat ${BASE_CONFIG_FILE} | sed -n "${cln},\$p" | head -n 22)
+    config_name=`echo ${config_lines} | grep '=====' | cut -d' ' -f2`
+    FILENAME=$LOG_PATH/dy2static_$config_name.txt
+    echo "[Start dy2static]" "${config_name} : ${FILENAME}"
+    echo ${config_lines} > $FILENAME
+    sed -i 's/gpu_list.*$/gpu_list:0/g' $FILENAME
+    sed -i '16s/$/ -o Global.print_batch_step=1/' ${FILENAME}
+
+    IFS=$'\n'
+
+
+    # start dygraph train
+    dygraph_output=$LOG_PATH/${config_name}_python_train_infer_dygraph_output.txt
+    dygraph_loss=$LOG_PATH/${config_name}_dygraph_loss.txt
+    sed -i '15ctrainer:norm_train' ${FILENAME}
+    cmd="bash test_tipc/test_train_inference_python.sh ${FILENAME} $MODE >$dygraph_output 2>&1"
+    echo $cmd
+    eval $cmd
+
+    # start dy2static train
+    dy2static_output=$LOG_PATH/${config_name}_python_train_infer_dy2static_output.txt
+    dy2static_loss=$LOG_PATH/${config_name}_dy2static_loss.txt
+    sed -i '15ctrainer:to_static_train' ${FILENAME}
+    cmd="bash test_tipc/test_train_inference_python.sh ${FILENAME} $MODE >$dy2static_output 2>&1"
+    echo $cmd
+    eval $cmd
+
+    # analysis and compare the losses. 
+    dyout=`cat $dy2static_output | python test_tipc/extract_loss.py -v 'Iter:' -e 'loss: {%f},'`
+    stout=`cat $dygraph_output   | python test_tipc/extract_loss.py -v 'Iter:' -e 'loss: {%f},'  `
+    echo $dyout > $dygraph_loss
+    echo $stout > $dy2static_loss
+    diff_log=$LOG_PATH/${config_name}_diff_log.txt
+    diff_cmd="diff -w $dygraph_loss $dy2static_loss > $diff_log"
+    eval $diff_cmd
+    last_status=$?
+    cat $diff_log
+    if [ "$dyout" = "" ]; then
+        status_check 2 $diff_cmd $status_log $model_name $diff_log
+    fi
+    if [ "$stout" = "" ]; then
+        status_check 2 $diff_cmd $status_log $model_name $diff_log
+    fi
+    status_check $last_status $diff_cmd $status_log $model_name $diff_log
+done