commit
cd53b915d5
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@ -101,7 +101,7 @@ def main():
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quanter = QAT(config=quant_config)
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quanter = QAT(config=quant_config)
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quanter.quantize(model)
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quanter.quantize(model)
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init_model(config, model, logger)
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init_model(config, model)
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model.eval()
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model.eval()
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# build metric
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# build metric
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@ -17,7 +17,7 @@ distill_train:null
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eval:tools/eval.py -c configs/det/det_mv3_db.yml -o
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eval:tools/eval.py -c configs/det/det_mv3_db.yml -o
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Global.save_inference_dir:./output/
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Global.save_inference_dir:./output/
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Global.checkpoints:
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Global.pretrained_model:
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norm_export:tools/export_model.py -c configs/det/det_mv3_db.yml -o
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norm_export:tools/export_model.py -c configs/det/det_mv3_db.yml -o
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quant_export:deploy/slim/quantization/export_model.py -c configs/det/det_mv3_db.yml -o
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quant_export:deploy/slim/quantization/export_model.py -c configs/det/det_mv3_db.yml -o
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fpgm_export:deploy/slim/prune/export_prune_model.py
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fpgm_export:deploy/slim/prune/export_prune_model.py
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@ -101,7 +101,7 @@ function func_inference(){
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for use_mkldnn in ${use_mkldnn_list[*]}; do
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for use_mkldnn in ${use_mkldnn_list[*]}; do
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for threads in ${cpu_threads_list[*]}; do
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for threads in ${cpu_threads_list[*]}; do
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for batch_size in ${batch_size_list[*]}; do
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for batch_size in ${batch_size_list[*]}; do
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_save_log_path="${_log_path}/infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_batchsize_${batch_size}"
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_save_log_path="${_log_path}/infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_batchsize_${batch_size}.log"
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command="${_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} ${image_dir_key}=${_img_dir} ${save_log_key}=${_save_log_path} --benchmark=True"
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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} ${image_dir_key}=${_img_dir} ${save_log_key}=${_save_log_path} --benchmark=True"
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eval $command
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eval $command
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status_check $? "${command}" "${status_log}"
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status_check $? "${command}" "${status_log}"
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@ -115,7 +115,7 @@ function func_inference(){
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continue
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continue
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fi
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fi
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for batch_size in ${batch_size_list[*]}; do
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for batch_size in ${batch_size_list[*]}; do
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_save_log_path="${_log_path}/infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}"
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_save_log_path="${_log_path}/infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
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command="${_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} ${image_dir_key}=${_img_dir} ${save_log_key}=${_save_log_path} --benchmark=True"
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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} ${image_dir_key}=${_img_dir} ${save_log_key}=${_save_log_path} --benchmark=True"
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eval $command
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eval $command
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status_check $? "${command}" "${status_log}"
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status_check $? "${command}" "${status_log}"
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@ -136,6 +136,7 @@ for gpu in ${gpu_list[*]}; do
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env=""
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env=""
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elif [ ${#gpu} -le 1 ];then
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elif [ ${#gpu} -le 1 ];then
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env="export CUDA_VISIBLE_DEVICES=${gpu}"
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env="export CUDA_VISIBLE_DEVICES=${gpu}"
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eval ${env}
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elif [ ${#gpu} -le 15 ];then
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elif [ ${#gpu} -le 15 ];then
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IFS=","
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IFS=","
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array=(${gpu})
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array=(${gpu})
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@ -215,7 +216,7 @@ for gpu in ${gpu_list[*]}; do
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status_check $? "${export_cmd}" "${status_log}"
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status_check $? "${export_cmd}" "${status_log}"
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#run inference
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#run inference
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echo $env
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eval $env
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save_infer_path="${save_log}"
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save_infer_path="${save_log}"
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func_inference "${python}" "${inference_py}" "${save_infer_path}" "${LOG_PATH}" "${infer_img_dir}"
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func_inference "${python}" "${inference_py}" "${save_infer_path}" "${LOG_PATH}" "${infer_img_dir}"
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done
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done
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Reference in New Issue