Where is the GPU setup? Running shows that GPU = None, in fact, I have a gpu, cuda10 installation training is no problem

[QQ2737499951]

Excuse me? Where is the GPU setup?

Running shows that GPU = None, in fact, I have a gpu, cuda10 installation training is no problem. thank you.

请问一下，gpu在哪里设置？运行显示 gpu=None，实际我gpu是有的，cuda10都安装训练没问题。方便加QQ沟通一下吗？ QQ2737499951,谢谢

================ args= Namespace(cfg_file='CornerNet_Saccade', dist_backend='nccl', dist_url=None, distributed=False, gpu=None, initialize=False, rank=0, start_iter=0, workers=2, world_size=-1) train tart_iter 0 distributed False world_size -1 initialize False gpu None Process 0: 创建模型 building model... total parameters: 116969339 启动预取数据 start prefetching data...

[heilaw]

Can you include the complete error message?

[QQ2737499951]

Can you include the complete error message?

D:\pytorch\CornerNet-Lite>python train.py CornerNet ngpus_per_node= 1 准备读取参数 cfg_file= ./configs\CornerNet.json Process 0: 加载所有数据集 loading all datasets... Process 0: using 1 workers coco_dir = B:/COCO2017/data\coco self._split A train2017 self._data_dir B B:/COCO2017/data\coco\images\train2017 _anno_file C B:/COCO2017/data\coco\annotations\instances_train2017.json loading annotations into memory... Done (t=13.10s) creating index... index created! coco_dir = B:/COCO2017/data\coco self._split A val2017 self._data_dir B B:/COCO2017/data\coco\images\val2017 _anno_file C B:/COCO2017/data\coco\annotations\instances_val2017.json loading annotations into memory... Done (t=1.13s) creating index... index created! 系统配置 system config... {'batch_size': 1, 'cache_dir': './cache', 'chunk_sizes': [1], 'config_dir': './config', 'data_dir': 'B:/COCO2017/data', 'data_rng': <mtrand.RandomState object at 0x000001B2AA7ABCA8>, 'dataset': 'COCO', 'decay_rate': 10, 'display': 100, 'learning_rate': 0.00025, 'max_iter': 500000, 'nnet_rng': <mtrand.RandomState object at 0x000001B2AA7ABCF0>, 'opt_algo': 'adam', 'prefetch_size': 5, 'pretrain': None, 'result_dir': './results', 'sampling_function': 'cornernet', 'snapshot': 5000, 'snapshot_name': 'CornerNet', 'stepsize': 450000, 'test_split': 'testing', 'train_split': 'training', 'val_iter': 100, 'val_split': 'validation'} 数据库配置 db config... {'ae_threshold': 0.5, 'att_max_crops': 8, 'att_nms_ks': [3, 3, 3], 'att_ranges': [[96, 256], [32, 96], [0, 32]], 'att_ratios': [16, 8, 4], 'att_scales': [1, 1.5, 2], 'att_sizes': [[16, 16], [32, 32], [64, 64]], 'att_thresholds': [0.3, 0.3, 0.3, 0.3], 'border': 128, 'categories': 80, 'data_aug': True, 'gaussian_bump': True, 'gaussian_iou': 0.3, 'gaussian_radius': -1, 'init_sizes': [192, 255], 'input_size': [511, 511], 'lighting': True, 'max_per_image': 100, 'max_per_set': 40, 'max_scale': 32, 'merge_bbox': False, 'min_scale': 16, 'nms_algorithm': 'exp_soft_nms', 'nms_kernel': 3, 'nms_threshold': 0.5, 'num_dets': 1000, 'output_sizes': [[128, 128]], 'rand_center': True, 'rand_color': True, 'rand_crop': True, 'rand_scale_max': 1.4, 'rand_scale_min': 0.6, 'rand_scale_step': 0.1, 'rand_scales': array([0.6, 0.7, 0.8, 0.9, 1. , 1.1, 1.2, 1.3]), 'ref_dets': True, 'score_threshold': 0.05, 'test_flipped': True, 'test_scales': [1], 'top_k': 100, 'view_sizes': [], 'weight_exp': 8} len of db: 118287 分布式 distributed: False 正式train args= Namespace(cfg_file='CornerNet', dist_backend='nccl', dist_url=None, distributed=False, gpu=None, initialize=False, rank=0, start_iter=0, workers=1, world_size=-1) **train..... tart_iter 0 distributed False world_size -1 initialize False gpu None ** Process 0: 创建模型 building model... total parameters: 201035212 system_config= <core.config.SystemConfig object at 0x00000277868FB240> db= <core.dbs.coco.COCO object at 0x00000277868FB7B8> queue= <multiprocessing.queues.Queue object at 0x0000027843333710> sample_data= <function data_sampling_func at 0x00000277862A60D0> data_aug= True 启动预取数据 start prefetching data... 洗牌指数 shuffling indices... system_config= <core.config.SystemConfig object at 0x000001D6A507B240> db= <core.dbs.coco.COCO object at 0x000001D6A507B7B8> queue= <multiprocessing.queues.Queue object at 0x000001D6ACC60F28> sample_data= <function data_sampling_func at 0x000001D6A4A560D0> data_aug= False 启动预取数据 start prefetching data... 洗牌指数 shuffling indices... setting learning rate to: 0.00025 开始训练 training start... Process 0: 迭代 100: 训练损失 11.960190773010254 Process 0: 迭代 100: 验证损失 8.793777465820312 Process 0: 迭代 200: 训练损失 7.868043422698975 Process 0: 迭代 200: 验证损失 10.156821250915527 0%| | 149/500000 [03:04<172:18:18, 1.24s/it]

============= D:\pytorch\CornerNet-Lite\train.py 259 pprint.pprint(training_dbs[0].configs)

261 print("len of db: {}".format(len(training_dbs[0].db_inds))) 262 print("分布式 distributed: {}".format(args.distributed))

264 print("正式train args=",args) 265 train(training_dbs, validation_db, system_config, model, args)