commit
370f0fef99
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@ -26,7 +26,7 @@ null:null
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##
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===========================infer_params===========================
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Global.save_inference_dir:./output/
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Global.pretrained_model:
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Global.checkpoints:
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norm_export:null
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quant_export:deploy/slim/quantization/export_model.py -c configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml -o
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fpgm_export:
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@ -4,7 +4,7 @@ python:python3.7
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gpu_list:0|0,1
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Global.use_gpu:True|True
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Global.auto_cast:null
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Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=300
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Global.epoch_num:lite_train_lite_infer=20|whole_train_whole_infer=300
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Global.save_model_dir:./output/
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Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4
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Global.pretrained_model:null
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@ -26,7 +26,7 @@ null:null
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##
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===========================infer_params===========================
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Global.save_inference_dir:./output/
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Global.pretrained_model:
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Global.checkpoints:
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norm_export:null
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quant_export:deploy/slim/quantization/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
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fpgm_export:null
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@ -48,4 +48,4 @@ inference:tools/infer/predict_det.py
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--image_dir:./inference/ch_det_data_50/all-sum-510/
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null:null
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--benchmark:True
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null:null
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null:null
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@ -322,10 +322,6 @@ else
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save_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}_nodes_${nodes}"
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fi
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# load pretrain from norm training if current trainer is pact or fpgm trainer
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if ([ ${trainer} = ${pact_key} ] || [ ${trainer} = ${fpgm_key} ]) && [ ${nodes} -le 1 ]; then
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set_pretrain="${load_norm_train_model}"
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fi
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set_save_model=$(func_set_params "${save_model_key}" "${save_log}")
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if [ ${#gpu} -le 2 ];then # train with cpu or single gpu
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@ -341,10 +337,7 @@ else
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status_check $? "${cmd}" "${status_log}"
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set_eval_pretrain=$(func_set_params "${pretrain_model_key}" "${save_log}/${train_model_name}")
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# save norm trained models to set pretrain for pact training and fpgm training
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if [ ${trainer} = ${trainer_norm} ] && [ ${nodes} -le 1 ]; then
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load_norm_train_model=${set_eval_pretrain}
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fi
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# run eval
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if [ ${eval_py} != "null" ]; then
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set_eval_params1=$(func_set_params "${eval_key1}" "${eval_value1}")
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