add test_v7
This commit is contained in:
LDOUBLEV
parent
9d5d552b79
commit
f6167acc1f
|
|
@ -0,0 +1,48 @@
|
|||
===========================train_params===========================
|
||||
model_name:ocr_det
|
||||
python:python3.7
|
||||
gpu_list:0|0,1
|
||||
Global.auto_cast:null
|
||||
Global.epoch_num:2
|
||||
Global.save_model_dir:./output/
|
||||
Train.loader.batch_size_per_card:2
|
||||
Global.use_gpu:
|
||||
Global.pretrained_model:null
|
||||
train_model_name:latest
|
||||
train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
|
||||
null:null
|
||||
##
|
||||
trainer:norm_train|pact_train
|
||||
norm_train:tools/train.py -c configs/det/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained
|
||||
pact_train:deploy/slim/quantization/quant.py -c configs/det/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/det_mv3_db_v2.0_train/best_accuracy
|
||||
fpgm_train:null
|
||||
distill_train:null
|
||||
null:null
|
||||
null:null
|
||||
##
|
||||
===========================eval_params===========================
|
||||
eval:null
|
||||
null:null
|
||||
##
|
||||
===========================infer_params===========================
|
||||
Global.save_inference_dir:./output/
|
||||
Global.pretrained_model:
|
||||
norm_export:tools/export_model.py -c configs/det/det_mv3_db.yml -o
|
||||
quant_export:deploy/slim/quantization/export_model.py -c configs/det/det_mv3_db.yml -o
|
||||
fpgm_export:deploy/slim/prune/export_prune_model.py
|
||||
distill_export:null
|
||||
null:null
|
||||
null:null
|
||||
##
|
||||
inference:tools/infer/predict_det.py
|
||||
--use_gpu:True|False
|
||||
--enable_mkldnn:True|False
|
||||
--cpu_threads:1|6
|
||||
--rec_batch_num:1
|
||||
--use_tensorrt:True|False
|
||||
--precision:fp32|fp16|int8
|
||||
--det_model_dir:./inference/ch_ppocr_mobile_v2.0_det_infer/
|
||||
--image_dir:./inference/ch_det_data_50/all-sum-510/
|
||||
--save_log_path:null
|
||||
--benchmark:True
|
||||
null:null
|
||||
|
|
@ -0,0 +1,77 @@
|
|||
#!/bin/bash
|
||||
FILENAME=$1
|
||||
# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer', 'infer']
|
||||
MODE=$2
|
||||
|
||||
dataline=$(cat ${FILENAME})
|
||||
|
||||
# parser params
|
||||
IFS=$'\n'
|
||||
lines=(${dataline})
|
||||
function func_parser_key(){
|
||||
strs=$1
|
||||
IFS=":"
|
||||
array=(${strs})
|
||||
tmp=${array[0]}
|
||||
echo ${tmp}
|
||||
}
|
||||
function func_parser_value(){
|
||||
strs=$1
|
||||
IFS=":"
|
||||
array=(${strs})
|
||||
tmp=${array[1]}
|
||||
echo ${tmp}
|
||||
}
|
||||
IFS=$'\n'
|
||||
# The training params
|
||||
model_name=$(func_parser_value "${lines[0]}")
|
||||
train_model_list=$(func_parser_value "${lines[0]}")
|
||||
|
||||
trainer_list=$(func_parser_value "${lines[10]}")
|
||||
|
||||
|
||||
# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer']
|
||||
MODE=$2
|
||||
# prepare pretrained weights and dataset
|
||||
wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams
|
||||
wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar
|
||||
cd pretrain_models && tar xf det_mv3_db_v2.0_train.tar && cd ../
|
||||
|
||||
if [ ${MODE} = "lite_train_infer" ];then
|
||||
# pretrain lite train data
|
||||
rm -rf ./train_data/icdar2015
|
||||
wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_lite.tar
|
||||
cd ./train_data/ && tar xf icdar2015_lite.tar
|
||||
ln -s ./icdar2015_lite ./icdar2015
|
||||
cd ../
|
||||
epoch=10
|
||||
eval_batch_step=10
|
||||
elif [ ${MODE} = "whole_train_infer" ];then
|
||||
rm -rf ./train_data/icdar2015
|
||||
wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015.tar
|
||||
cd ./train_data/ && tar xf icdar2015.tar && cd ../
|
||||
epoch=500
|
||||
eval_batch_step=200
|
||||
elif [ ${MODE} = "whole_infer" ];then
|
||||
rm -rf ./train_data/icdar2015
|
||||
wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_infer.tar
|
||||
cd ./train_data/ && tar xf icdar2015_infer.tar
|
||||
ln -s ./icdar2015_infer ./icdar2015
|
||||
cd ../
|
||||
epoch=10
|
||||
eval_batch_step=10
|
||||
else
|
||||
rm -rf ./train_data/icdar2015
|
||||
wget -nc -P ./train_data https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar
|
||||
if [ ${model_name} = "ocr_det" ]; then
|
||||
eval_model_name="ch_ppocr_mobile_v2.0_det_infer"
|
||||
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar
|
||||
cd ./inference && tar xf ${eval_model_name}.tar && cd ../
|
||||
else
|
||||
eval_model_name="ch_ppocr_mobile_v2.0_rec_train"
|
||||
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar
|
||||
cd ./inference && tar xf ${eval_model_name}.tar && cd ../
|
||||
fi
|
||||
fi
|
||||
|
||||
|
||||
|
|
@ -0,0 +1,282 @@
|
|||
#!/bin/bash
|
||||
FILENAME=$1
|
||||
# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer', 'infer']
|
||||
MODE=$2
|
||||
|
||||
dataline=$(cat ${FILENAME})
|
||||
|
||||
# parser params
|
||||
IFS=$'\n'
|
||||
lines=(${dataline})
|
||||
|
||||
function func_parser_key(){
|
||||
strs=$1
|
||||
IFS=":"
|
||||
array=(${strs})
|
||||
tmp=${array[0]}
|
||||
echo ${tmp}
|
||||
}
|
||||
function func_parser_value(){
|
||||
strs=$1
|
||||
IFS=":"
|
||||
array=(${strs})
|
||||
tmp=${array[1]}
|
||||
echo ${tmp}
|
||||
}
|
||||
function func_set_params(){
|
||||
key=$1
|
||||
value=$2
|
||||
if [ ${key} = "null" ];then
|
||||
echo " "
|
||||
elif [[ ${value} = "null" ]] || [[ ${value} = " " ]] || [ ${#value} -le 0 ];then
|
||||
echo " "
|
||||
else
|
||||
echo "${key}=${value}"
|
||||
fi
|
||||
}
|
||||
function status_check(){
|
||||
last_status=$1 # the exit code
|
||||
run_command=$2
|
||||
run_log=$3
|
||||
if [ $last_status -eq 0 ]; then
|
||||
echo -e "\033[33m Run successfully with command - ${run_command}! \033[0m" | tee -a ${run_log}
|
||||
else
|
||||
echo -e "\033[33m Run failed with command - ${run_command}! \033[0m" | tee -a ${run_log}
|
||||
fi
|
||||
}
|
||||
|
||||
IFS=$'\n'
|
||||
# The training params
|
||||
model_name=$(func_parser_value "${lines[1]}")
|
||||
python=$(func_parser_value "${lines[2]}")
|
||||
gpu_list=$(func_parser_value "${lines[3]}")
|
||||
autocast_list=$(func_parser_value "${lines[4]}")
|
||||
autocast_key=$(func_parser_key "${lines[4]}")
|
||||
epoch_key=$(func_parser_key "${lines[5]}")
|
||||
epoch_num=$(func_parser_value "${lines[5]}")
|
||||
save_model_key=$(func_parser_key "${lines[6]}")
|
||||
train_batch_key=$(func_parser_key "${lines[7]}")
|
||||
train_batch_value=$(func_parser_value "${lines[7]}")
|
||||
train_use_gpu_key=$(func_parser_key "${lines[8]}")
|
||||
pretrain_model_key=$(func_parser_key "${lines[9]}")
|
||||
pretrain_model_value=$(func_parser_value "${lines[9]}")
|
||||
train_model_name=$(func_parser_value "${lines[10]}")
|
||||
train_infer_img_dir=$(func_parser_value "${lines[11]}")
|
||||
train_param_key1=$(func_parser_key "${lines[12]}")
|
||||
train_param_value1=$(func_parser_value "${lines[12]}")
|
||||
|
||||
trainer_list=$(func_parser_value "${lines[14]}")
|
||||
trainer_norm=$(func_parser_key "${lines[15]}")
|
||||
norm_trainer=$(func_parser_value "${lines[15]}")
|
||||
pact_key=$(func_parser_key "${lines[16]}")
|
||||
pact_trainer=$(func_parser_value "${lines[16]}")
|
||||
fpgm_key=$(func_parser_key "${lines[17]}")
|
||||
fpgm_trainer=$(func_parser_value "${lines[17]}")
|
||||
distill_key=$(func_parser_key "${lines[18]}")
|
||||
distill_trainer=$(func_parser_value "${lines[18]}")
|
||||
trainer_key1=$(func_parser_key "${lines[19]}")
|
||||
trainer_value1=$(func_parser_value "${lines[19]}")
|
||||
trainer_key1=$(func_parser_key "${lines[20]}")
|
||||
trainer_value2=$(func_parser_value "${lines[20]}")
|
||||
|
||||
eval_py=$(func_parser_value "${lines[23]}")
|
||||
eval_key1=$(func_parser_key "${lines[24]}")
|
||||
eval_value1=$(func_parser_value "${lines[24]}")
|
||||
|
||||
save_infer_key=$(func_parser_key "${lines[27]}")
|
||||
export_weight=$(func_parser_key "${lines[28]}")
|
||||
norm_export=$(func_parser_value "${lines[29]}")
|
||||
pact_export=$(func_parser_value "${lines[30]}")
|
||||
fpgm_export=$(func_parser_value "${lines[31]}")
|
||||
distill_export=$(func_parser_value "${lines[32]}")
|
||||
export_key1=$(func_parser_key "${lines[33]}")
|
||||
export_value1=$(func_parser_value "${lines[33]}")
|
||||
export_key2=$(func_parser_key "${lines[34]}")
|
||||
export_value2=$(func_parser_value "${lines[34]}")
|
||||
|
||||
inference_py=$(func_parser_value "${lines[36]}")
|
||||
use_gpu_key=$(func_parser_key "${lines[37]}")
|
||||
use_gpu_list=$(func_parser_value "${lines[37]}")
|
||||
use_mkldnn_key=$(func_parser_key "${lines[38]}")
|
||||
use_mkldnn_list=$(func_parser_value "${lines[38]}")
|
||||
cpu_threads_key=$(func_parser_key "${lines[39]}")
|
||||
cpu_threads_list=$(func_parser_value "${lines[39]}")
|
||||
batch_size_key=$(func_parser_key "${lines[40]}")
|
||||
batch_size_list=$(func_parser_value "${lines[40]}")
|
||||
use_trt_key=$(func_parser_key "${lines[41]}")
|
||||
use_trt_list=$(func_parser_value "${lines[41]}")
|
||||
precision_key=$(func_parser_key "${lines[42]}")
|
||||
precision_list=$(func_parser_value "${lines[42]}")
|
||||
infer_model_key=$(func_parser_key "${lines[43]}")
|
||||
infer_model=$(func_parser_value "${lines[43]}")
|
||||
image_dir_key=$(func_parser_key "${lines[44]}")
|
||||
infer_img_dir=$(func_parser_value "${lines[44]}")
|
||||
save_log_key=$(func_parser_key "${lines[45]}")
|
||||
benchmark_key=$(func_parser_key "${lines[46]}")
|
||||
benchmark_value=$(func_parser_value "${lines[46]}")
|
||||
infer_key2=$(func_parser_key "${lines[47]}")
|
||||
infer_value2=$(func_parser_value "${lines[47]}")
|
||||
|
||||
LOG_PATH="./tests/output"
|
||||
mkdir -p ${LOG_PATH}
|
||||
status_log="${LOG_PATH}/results.log"
|
||||
|
||||
|
||||
function func_inference(){
|
||||
IFS='|'
|
||||
_python=$1
|
||||
_script=$2
|
||||
_model_dir=$3
|
||||
_log_path=$4
|
||||
_img_dir=$5
|
||||
_flag_quant=$6
|
||||
# inference
|
||||
for use_gpu in ${use_gpu_list[*]}; do
|
||||
if [ ${use_gpu} = "False" ] && [ ${_flag_quant} = "True" ]; then
|
||||
continue
|
||||
fi
|
||||
if [ ${use_gpu} = "False" ]; then
|
||||
for use_mkldnn in ${use_mkldnn_list[*]}; do
|
||||
for threads in ${cpu_threads_list[*]}; do
|
||||
for batch_size in ${batch_size_list[*]}; do
|
||||
_save_log_path="${_log_path}/infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_batchsize_${batch_size}.log"
|
||||
#${image_dir_key}=${_img_dir} ${save_log_key}=${_save_log_path} --benchmark=True
|
||||
set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}")
|
||||
set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}")
|
||||
command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_mkldnn_key}=${use_mkldnn} ${cpu_threads_key}=${threads} ${infer_model_key}=${_model_dir} ${batch_size_key}=${batch_size} ${set_infer_data} ${set_benchmark} > ${_save_log_path} 2>&1 "
|
||||
eval $command
|
||||
status_check $? "${command}" "${status_log}"
|
||||
done
|
||||
done
|
||||
done
|
||||
else
|
||||
for use_trt in ${use_trt_list[*]}; do
|
||||
for precision in ${precision_list[*]}; do
|
||||
if [ ${use_trt} = "False" ] && [ ${precision} != "fp32" ]; then
|
||||
continue
|
||||
fi
|
||||
if [ ${use_trt} = "False" ] && [ ${_flag_quant} = "True" ]; then
|
||||
continue
|
||||
fi
|
||||
if [ ${precision} != "int8" ] && [ ${_flag_quant} = "True" ]; then
|
||||
continue
|
||||
fi
|
||||
for batch_size in ${batch_size_list[*]}; do
|
||||
_save_log_path="${_log_path}/infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
|
||||
set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}")
|
||||
set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}")
|
||||
command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_trt_key}=${use_trt} ${precision_key}=${precision} ${infer_model_key}=${_model_dir} ${batch_size_key}=${batch_size} ${set_infer_data} ${set_benchmark} > ${_save_log_path} 2>&1 "
|
||||
eval $command
|
||||
status_check $? "${command}" "${status_log}"
|
||||
done
|
||||
done
|
||||
done
|
||||
fi
|
||||
done
|
||||
}
|
||||
|
||||
if [ ${MODE} != "infer" ]; then
|
||||
|
||||
IFS="|"
|
||||
for gpu in ${gpu_list[*]}; do
|
||||
use_gpu=True
|
||||
if [ ${gpu} = "-1" ];then
|
||||
use_gpu=False
|
||||
env=""
|
||||
elif [ ${#gpu} -le 1 ];then
|
||||
env="export CUDA_VISIBLE_DEVICES=${gpu}"
|
||||
eval ${env}
|
||||
elif [ ${#gpu} -le 15 ];then
|
||||
IFS=","
|
||||
array=(${gpu})
|
||||
env="export CUDA_VISIBLE_DEVICES=${array[0]}"
|
||||
IFS="|"
|
||||
else
|
||||
IFS=";"
|
||||
array=(${gpu})
|
||||
ips=${array[0]}
|
||||
gpu=${array[1]}
|
||||
IFS="|"
|
||||
env=" "
|
||||
fi
|
||||
for autocast in ${autocast_list[*]}; do
|
||||
for trainer in ${trainer_list[*]}; do
|
||||
flag_quant=False
|
||||
if [ ${trainer} = ${pact_key} ]; then
|
||||
run_train=${pact_trainer}
|
||||
run_export=${pact_export}
|
||||
flag_quant=True
|
||||
elif [ ${trainer} = "${fpgm_key}" ]; then
|
||||
run_train=${fpgm_trainer}
|
||||
run_export=${fpgm_export}
|
||||
elif [ ${trainer} = "${distill_key}" ]; then
|
||||
run_train=${distill_trainer}
|
||||
run_export=${distill_export}
|
||||
elif [ ${trainer} = ${trainer_key1} ]; then
|
||||
run_train=${trainer_value1}
|
||||
run_export=${export_value1}
|
||||
elif [[ ${trainer} = ${trainer_key2} ]]; then
|
||||
run_train=${trainer_value2}
|
||||
run_export=${export_value2}
|
||||
else
|
||||
run_train=${norm_trainer}
|
||||
run_export=${norm_export}
|
||||
fi
|
||||
|
||||
if [ ${run_train} = "null" ]; then
|
||||
continue
|
||||
fi
|
||||
|
||||
set_autocast=$(func_set_params "${autocast_key}" "${autocast}")
|
||||
set_autocast=$(func_set_params "${epoch_key}" "${epoch_num}")
|
||||
set_pretrain=$(func_set_params "${pretrain_model_key}" "${pretrain_model_value}")
|
||||
set_batchsize=$(func_set_params "${train_batch_key}" "${train_batch_value}")
|
||||
set_train_params1=$(func_set_params "${train_param_key1}" "${train_param_value1}")
|
||||
|
||||
save_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}"
|
||||
if [ ${#gpu} -le 2 ];then # train with cpu or single gpu
|
||||
cmd="${python} ${run_train} ${train_use_gpu_key}=${use_gpu} ${save_model_key}=${save_log} ${set_epoch} ${set_pretrain} ${set_autocast} ${set_batchsize} ${set_train_params1} "
|
||||
elif [ ${#gpu} -le 15 ];then # train with multi-gpu
|
||||
cmd="${python} -m paddle.distributed.launch --gpus=${gpu} ${run_train} ${save_model_key}=${save_log} ${set_epoch} ${set_pretrain} ${set_autocast} ${set_batchsize} ${set_train_params1}"
|
||||
else # train with multi-machine
|
||||
cmd="${python} -m paddle.distributed.launch --ips=${ips} --gpus=${gpu} ${run_train} ${save_model_key}=${save_log} ${set_pretrain} ${set_epoch} ${set_autocast} ${set_batchsize} ${set_train_params1}"
|
||||
fi
|
||||
# run train
|
||||
eval $cmd
|
||||
status_check $? "${cmd}" "${status_log}"
|
||||
|
||||
# run eval
|
||||
if [ ${eval_py} != "null" ]; then
|
||||
eval_cmd="${python} ${eval_py} ${save_model_key}=${save_log} ${pretrain_model_key}=${save_log}/${train_model_name}"
|
||||
eval $eval_cmd
|
||||
status_check $? "${eval_cmd}" "${status_log}"
|
||||
fi
|
||||
|
||||
if [ ${run_export} != "null" ]; then
|
||||
# run export model
|
||||
save_infer_path="${save_log}"
|
||||
export_cmd="${python} ${run_export} ${save_model_key}=${save_log} ${export_weight}=${save_log}/${train_model_name} ${save_infer_key}=${save_infer_path}"
|
||||
eval $export_cmd
|
||||
status_check $? "${export_cmd}" "${status_log}"
|
||||
|
||||
#run inference
|
||||
eval $env
|
||||
save_infer_path="${save_log}"
|
||||
func_inference "${python}" "${inference_py}" "${save_infer_path}" "${LOG_PATH}" "${train_infer_img_dir}" "${flag_quant}"
|
||||
eval "unset CUDA_VISIBLE_DEVICES"
|
||||
fi
|
||||
done
|
||||
done
|
||||
done
|
||||
|
||||
else
|
||||
GPUID=$3
|
||||
if [ ${#GPUID} -le 0 ];then
|
||||
env=" "
|
||||
else
|
||||
env="export CUDA_VISIBLE_DEVICES=${GPUID}"
|
||||
fi
|
||||
echo $env
|
||||
#run inference
|
||||
func_inference "${python}" "${inference_py}" "${infer_model}" "${LOG_PATH}" "${infer_img_dir}" "False"
|
||||
fi
|
||||
Loading…
Reference in New Issue