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- ===========================train_params===========================
- model_name:en_server_pgnetA
- python:python3.7
- gpu_list:0|0,1
- Global.use_gpu:True|True
- Global.auto_cast:null
- Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=500
- Global.save_model_dir:./output/
- Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=14
- Global.pretrained_model:null
- train_model_name:latest
- train_infer_img_dir:./train_data/total_text/test/rgb/
- null:null
- ##
- trainer:norm_train
- norm_train:tools/train.py -c configs/e2e/e2e_r50_vd_pg.yml -o Global.pretrained_model=./pretrain_models/en_server_pgnetA/best_accuracy
- pact_train:null
- fpgm_train:null
- distill_train:null
- null:null
- null:null
- ##
- ===========================eval_params===========================
- eval:null
- null:null
- ##
- ===========================infer_params===========================
- Global.save_inference_dir:./output/
- Global.checkpoints:
- norm_export:tools/export_model.py -c configs/e2e/e2e_r50_vd_pg.yml -o
- quant_export:null
- fpgm_export:null
- distill_export:null
- export1:null
- export2:null
- inference_dir:null
- train_model:./inference/en_server_pgnetA/best_accuracy
- infer_export:tools/export_model.py -c configs/e2e/e2e_r50_vd_pg.yml -o
- infer_quant:False
- inference:tools/infer/predict_e2e.py
- --use_gpu:True|False
- --enable_mkldnn:False
- --cpu_threads:6
- --rec_batch_num:1
- --use_tensorrt:False
- --precision:fp32
- --e2e_model_dir:
- --image_dir:./inference/ch_det_data_50/all-sum-510/
- null:null
- --benchmark:True
- null:null
- ===========================infer_benchmark_params==========================
- random_infer_input:[{float32,[3,640,640]}];[{float32,[3,960,960]}]
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