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- backbone: "yolox_nano" #option for backbone
- data_aug: True
- # path for local
- device_target: "Ascend"
- # /home/work/user-job-dir/outputs/model/
- outputs_dir: "./"
- # ======================================================
- # Train option
- save_graphs: False
- lr_scheduler: "yolox_warm_cos_lr"
- max_epoch: 285
- total_epoch: 300
- data_dir: "/home/work/user-job-dir/inputs/data/"
- # last no data aug related
- yolox_no_aug_ckpt: ""
- need_profiler: 0
- pretrained: ''
- resume_yolox: ''
- # data aug
- flip_prob: 0.5
- hsv_prob: 1.0
- # ========================================================\
- # dataset related
- per_batch_size: 8
-
- # network configuration
- depth_wise: False
- max_gt: 120
- num_classes: 80
- input_size: [416, 416]
- fpn_strides: [8, 16, 32]
- use_l1: False
- use_syc_bn: True
- updates: 0.0
-
- # dynamic_k
- n_candidate_k: 10
-
- # optimizer and lr related
- lr: 0.04 # 0.04 for yolox-nano
- min_lr_ratio: 0.001
- warmup_epochs: 5
- weight_decay: 0.0005
- momentum: 0.9
- no_aug_epochs: 15
- # logging related
- log_interval: 30
- ckpt_interval: -1
- is_save_on_master: 1
- ckpt_max_num: 60
- opt: "Momentum"
-
- # distributed related
- is_distributed: 1
- rank: 0
- group_size: 1
- bind_cpu: True
- device_num: 8
-
- # modelart
- is_modelArts: 0
- enable_modelarts: False
-
- need_modelarts_dataset_unzip: False
- modelarts_dataset_unzip_name: "coco2017"
-
- data_url: ""
- train_url: ""
- checkpoint_url: ""
- data_path: "/home/work/user-job-dir/inputs/data/"
- output_path: "./"
- load_path: "/cache/checkpoint_path"
- ckpt_path: './'
-
- # Eval option
- log_path: "val/outputs/"
- val_ckpt: "0-2755_64.ckpt"
- conf_thre: 0.001
- nms_thre: 0.65
- eval_interval: 10
- run_eval: False
- # modelarts
- is_modelart: False
- result_path: ''
-
- # export option
- file_format: 'MINDIR'
- export_bs: 1
-
-
- multi_scale: 5
- resize_rate: 10
- multi_scale_list: [[512, 512],
- [544, 544],
- [576, 576],
- [608, 608],
- [640, 640],
- [672, 672],
- [704, 704],
- [736, 736],
- [768, 768],
- [800, 800]
- ]
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