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add pretrain to Global

This commit is contained in:
LDOUBLEV 2021-06-09 13:02:34 +08:00
parent 4b56069d84
commit 3cdc9e5383
1 changed files with 9 additions and 3 deletions
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12
test/test.sh
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@ -8,6 +8,8 @@ FILENAME=$1
MODE=$2 MODE=$2
# prepare pretrained weights and dataset # 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://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 if [ ${MODE} = "lite_train_infer" ];then
# pretrain lite train data # pretrain lite train data
@ -107,28 +109,32 @@ for train_model in ${train_model_list[*]}; do
env="CUDA_VISIBLE_DEVICES=${array[0]}" env="CUDA_VISIBLE_DEVICES=${array[0]}"
IFS="|" IFS="|"
fi fi
IFS="|"
for auto_cast in ${auto_cast_list[*]}; do for auto_cast in ${auto_cast_list[*]}; do
for slim_trainer in ${slim_trainer_list[*]}; do for slim_trainer in ${slim_trainer_list[*]}; do
if [ ${slim_trainer} = "norm" ]; then if [ ${slim_trainer} = "norm" ]; then
trainer="tools/train.py" trainer="tools/train.py"
export_model="tools/export_model.py" export_model="tools/export_model.py"
pretrain="./pretrain_models/MobileNetV3_large_x0_5_pretrained"
elif [ ${slim_trainer} = "quant" ]; then elif [ ${slim_trainer} = "quant" ]; then
trainer="deploy/slim/quantization/quant.py" trainer="deploy/slim/quantization/quant.py"
export_model="deploy/slim/quantization/export_model.py" export_model="deploy/slim/quantization/export_model.py"
pretrain="./pretrain_models/det_mv3_db_v2.0_train/best_accuracy"
elif [ ${slim_trainer} = "prune" ]; then elif [ ${slim_trainer} = "prune" ]; then
trainer="deploy/slim/prune/sensitivity_anal.py" trainer="deploy/slim/prune/sensitivity_anal.py"
export_model="deploy/slim/prune/export_prune_model.py" export_model="deploy/slim/prune/export_prune_model.py"
pretrain="./pretrain_models/det_mv3_db_v2.0_train/best_accuracy"
elif [ ${slim_trainer} = "distill" ]; then elif [ ${slim_trainer} = "distill" ]; then
trainer="deploy/slim/distill/train_dml.py" trainer="deploy/slim/distill/train_dml.py"
export_model="deploy/slim/distill/export_distill_model.py" export_model="deploy/slim/distill/export_distill_model.py"
pretrain=""
else else
trainer="tools/train.py" trainer="tools/train.py"
export_model="tools/export_model.py" export_model="tools/export_model.py"
pretrain="./pretrain_models/MobileNetV3_large_x0_5_pretrained"
fi fi
save_log="${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}" save_log="${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}"
command="${env} ${python} ${launch} ${trainer} -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu} Train.loader.batch_size_per_card=2" command="${env} ${python} ${launch} ${trainer} -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain} Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu} Train.loader.batch_size_per_card=2"
${env} ${python} ${launch} ${trainer} -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu} Train.loader.batch_size_per_card=2 ${env} ${python} ${launch} ${trainer} -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.pretrained_model=${pretrain} Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu} Train.loader.batch_size_per_card=2
status_check $? "${trainer}" "${command}" "${save_log}/train.log" status_check $? "${trainer}" "${command}" "${save_log}/train.log"
command="${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}" command="${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}"