train_infer_python.txt

===========================train_params===========================
model_name:nafnet
python:python3.7
gpu_list:0
##
auto_cast:null
total_iters:lite_train_lite_infer=10
output_dir:./output/
snapshot_config.interval:lite_train_lite_infer=10
pretrained_model:null
train_model_name:nafnet*/*checkpoint.pdparams
train_infer_img_dir:null
null:null
##
trainer:norm_train
norm_train:tools/main.py -c configs/nafnet_denoising.yaml --seed 100  -o log_config.interval=1
pact_train:null
fpgm_train:null
distill_train:null
null:null
null:null
##
===========================eval_params===========================
eval:null
null:null
##
===========================infer_params===========================
--output_dir:./output/
load:null
norm_export:tools/export_model.py -c configs/nafnet_denoising.yaml  --inputs_size=1,3,256,256 --model_name inference --load
quant_export:null
fpgm_export:null
distill_export:null
export1:null
export2:null
inference_dir:inference
train_model:./inference/nafnet/nafnetmodel_generator
infer_export:null
infer_quant:False
inference:tools/inference.py --model_type nafnet --seed 100 -c configs/nafnet_denoising.yaml --output_path test_tipc/output/
--device:gpu
null:null
null:null
null:null
null:null
null:null
--model_path:
null:null
null:null
--benchmark:True
null:null