===========================train_params===========================
model_name:slanet
python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1
Global.use_gpu:True
Global.auto_cast:fp32
Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=50
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128
Global.pretrained_model:./pretrain_models/en_ppstructure_mobile_v2.0_SLANet_train/best_accuracy
train_model_name:latest
train_infer_img_dir:./ppstructure/docs/table/table.jpg
null:null
##
trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/slanet/SLANet.yml -o
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 test_tipc/configs/slanet/SLANet.yml -o
quant_export:
fpgm_export: 
distill_export:null
export1:null
export2:null
##
infer_model:./inference/en_ppstructure_mobile_v2.0_SLANet_train
infer_export:null
infer_quant:False
inference:ppstructure/table/predict_table.py --det_model_dir=./inference/en_ppocr_mobile_v2.0_table_det_infer --rec_model_dir=./inference/en_ppocr_mobile_v2.0_table_rec_infer  --rec_char_dict_path=./ppocr/utils/dict/table_dict.txt --table_char_dict_path=./ppocr/utils/dict/table_structure_dict.txt --image_dir=./ppstructure/docs/table/table.jpg --det_limit_side_len=736 --det_limit_type=min --output ./output/table
--use_gpu:False
--enable_mkldnn:False
--cpu_threads:6
--rec_batch_num:1
--use_tensorrt:False
--precision:fp32
--table_model_dir:
--image_dir:./ppstructure/docs/table/table.jpg
null:null
--benchmark:False
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,488,488]}]
