===========================train_params=========================== model_name:PPHGNet_tiny python:python3.7 gpu_list:0|0,1 -o Global.device:gpu -o Global.auto_cast:null -o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120 -o Global.output_dir:./output/ -o DataLoader.Train.sampler.batch_size:8 -o Global.pretrained_model:null train_model_name:latest train_infer_img_dir:./dataset/ILSVRC2012/val null:null ## trainer:norm_train norm_train:tools/train.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False pact_train:null fpgm_train:null distill_train:null null:null null:null ## ===========================eval_params=========================== eval:tools/eval.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml null:null ## ===========================infer_params========================== -o Global.save_inference_dir:./inference -o Global.pretrained_model: norm_export:tools/export_model.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.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/legendary_models/PPHGNet_tiny_pretrained.pdparams infer_model:../inference/ infer_export:True infer_quant:Fasle inference:python/predict_cls.py -c configs/inference_cls.yaml -o PreProcess.transform_ops.0.ResizeImage.resize_short=232 -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.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 ===========================infer_benchmark_params========================== random_infer_input:[{float32,[3,224,224]}]