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PaddleOCR
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support use_gpu as device

This commit is contained in:
LDOUBLEV 2021-07-14 13:54:42 +00:00
parent 2be96bfc9a
commit 425e343b05
2 changed files with 21 additions and 15 deletions
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2
tests/ocr_det_params.txt
View File

@ -2,11 +2,11 @@
model_name:ocr_det
python:python3.7
gpu_list:0|0,1
Global.use_gpu:True|False
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/

34
tests/test.sh
View File

@ -50,14 +50,15 @@ IFS=$'\n'
model_name=$(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 "${lines[8]}")
train_use_gpu_key=$(func_parser_key "${lines[4]}")
train_use_gpu_value=$(func_parser_value "${lines[4]}")
autocast_list=$(func_parser_value "${lines[5]}")
autocast_key=$(func_parser_key "${lines[5]}")
epoch_key=$(func_parser_key "${lines[6]}")
epoch_num=$(func_parser_value "${lines[6]}")
save_model_key=$(func_parser_key "${lines[7]}")
train_batch_key=$(func_parser_key "${lines[8]}")
train_batch_value=$(func_parser_value "${lines[8]}")
pretrain_model_key=$(func_parser_key "${lines[9]}")
pretrain_model_value=$(func_parser_value "${lines[9]}")
train_model_name=$(func_parser_value "${lines[10]}")
@ -132,7 +133,7 @@ function func_inference(){
_flag_quant=$6
# inference
for use_gpu in ${use_gpu_list[*]}; do
if [ ${use_gpu} = "False" ]; then
if [ ${use_gpu} = "False" ] || [ ${use_gpu} = "cpu" ]; then
for use_mkldnn in ${use_mkldnn_list[*]}; do
if [ ${use_mkldnn} = "False" ] && [ ${_flag_quant} = "True" ]; then
continue
@ -149,7 +150,7 @@ function func_inference(){
done
done
done
else
elif [ ${use_gpu} = "True" ] || [ ${use_gpu} = "gpu" ]; then
for use_trt in ${use_trt_list[*]}; do
for precision in ${precision_list[*]}; do
if [ ${use_trt} = "False" ] && [ ${precision} != "fp32" ]; then
@ -171,6 +172,8 @@ function func_inference(){
done
done
done
else
echo "Currently does not support hardware other than CPU and GPU"
fi
done
}
@ -178,10 +181,12 @@ function func_inference(){
if [ ${MODE} != "infer" ]; then
IFS="|"
export Count=0
USE_GPU_KEY=(${train_use_gpu_value})
for gpu in ${gpu_list[*]}; do
use_gpu=True
use_gpu=${USE_GPU_KEY[Count]}
Count=$(($Count + 1))
if [ ${gpu} = "-1" ];then
use_gpu=False
env=""
elif [ ${#gpu} -le 1 ];then
env="export CUDA_VISIBLE_DEVICES=${gpu}"
@ -232,10 +237,11 @@ for gpu in ${gpu_list[*]}; do
set_pretrain=$(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}")
set_use_gpu=$(func_set_params "${train_use_gpu_key}" "${use_gpu}")
save_log="${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} ${set_train_params1} "
cmd="${python} ${run_train} ${set_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
@ -247,7 +253,7 @@ for gpu in ${gpu_list[*]}; do
# run eval
if [ ${eval_py} != "null" ]; then
eval_cmd="${python} ${eval_py} ${save_model_key}=${save_log} ${pretrain_model_key}=${save_log}/${train_model_name}"
eval_cmd="${python} ${eval_py} ${save_model_key}=${save_log} ${pretrain_model_key}=${save_log}/${train_model_name} ${set_use_gpu}"
eval $eval_cmd
status_check $? "${eval_cmd}" "${status_log}"
fi