===========================train_params===========================
model_name:MetaBIN_ResNet50
python:python3.7
gpu_list:0
-o Global.device:gpu
-o Global.auto_cast:null
-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=348
-o Global.output_dir:./output/
-o DataLoader.Train.sampler.batch_size:16
-o Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./dataset/ILSVRC2012/val
null:null
##
trainer:amp_train
amp_train:tools/train.py -c ppcls/configs/reid/MetaBIN_ResNet50_cross_domain.yaml -o Global.seed=1234 -o DataLoader.Train.loader.num_workers=1 -o DataLoader.Train.loader.use_shared_memory=False -o Global.eval_during_train=False -o Global.save_interval=2 -o DataLoader.Train.sampler.num_instances=2 -o DataLoader.Metalearning.Train.sampler.batch_size=16 -o DataLoader.Metalearning.Train.sampler.num_instances=2
pact_train:null
fpgm_train:null
distill_train:null
null:null
null:null
##
===========================eval_params===========================
eval:tools/eval.py -c ppcls/configs/reid/MetaBIN_ResNet50_cross_domain.yaml
null:null
##
===========================infer_params==========================
-o Global.save_inference_dir:./inference
-o Global.pretrained_model:
norm_export:tools/export_model.py -c ppcls/configs/reid/MetaBIN_ResNet50_cross_domain.yaml
quant_export:null
fpgm_export:null
distill_export:null
kl_quant:null
export2:null
pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/metric_learning/metabin/metabin_resnet50_pretrained.pdparams
infer_model:../inference/
infer_export:True
infer_quant:Fasle
inference:python/predict_rec.py -c ./configs/inference_rec.yaml
-o Global.use_gpu:True|False
-o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1
-o Global.batch_size:1
-o Global.use_tensorrt:False
-o Global.use_fp16:False
-o Global.rec_inference_model_dir:../inference
-o Global.infer_imgs:../dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
-o Global.save_log_path:null
-o Global.benchmark:False
null:null
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,256,128]}]