===========================train_params===========================
model_name:edvr
python:python3.7
gpu_list:0
##
auto_cast:null
total_iters:lite_train_lite_infer=100
output_dir:./output/
dataset.train.batch_size:lite_train_lite_infer=4
pretrained_model:null
train_model_name:edvr_m_wo_tsa*/*checkpoint.pdparams
train_infer_img_dir:./data/basicvsr_reds/test
null:null
##
trainer:norm_train
norm_train:tools/main.py -c configs/edvr_m_wo_tsa.yaml --seed 123 -o log_config.interval=5 snapshot_config.interval=25
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/edvr_m_wo_tsa.yaml  --inputs_size="1,5,3,180,320" --model_name inference --load
quant_export:null
fpgm_export:null
distill_export:null
export1:null
export2:null
inference_dir:inference
train_model:./inference/edvr/edvrmodel_generator
infer_export:null
infer_quant:False
inference:tools/inference.py --model_type edvr -c configs/edvr_m_wo_tsa.yaml --seed 123 -o dataset.test.num_frames=5 --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
===========================to_static_train_benchmark_params===========================
to_static_train:model.to_static=True
===========================train_benchmark_params==========================
batch_size:64
fp_items:fp32|fp16
total_iters:100
--profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
flags:FLAGS_cudnn_exhaustive_search=1