segmentation fault段错误(核心已转储)

[XuYi-fei]

CUDA_VISIBLE_DEVICES=0 python trainval_net.py                    --dataset pascal_voc --net vgg16                    --bs 4 --nw 4                    --lr 0.01 --lr_decay_step 10 --cuda
Called with args:
Namespace(batch_size=4, checkepoch=1, checkpoint=0, checkpoint_interval=10000, checksession=1, class_agnostic=False, cuda=True, dataset='pascal_voc', disp_interval=100, large_scale=False, lr=0.01, lr_decay_gamma=0.1, lr_decay_step=10, mGPUs=False, max_epochs=20, net='vgg16', num_workers=4, optimizer='sgd', resume=False, save_dir='models', session=1, start_epoch=1, use_tfboard=False)
/home/xuyifei/桌面/Git/Git/rcnn-pytorch1.0_new/faster-rcnn.pytorch/lib/model/utils/config.py:374: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
 yaml_cfg = edict(yaml.load(f))
Using config:
{'ANCHOR_RATIOS': [0.5, 1, 2],
'ANCHOR_SCALES': [8, 16, 32],
'CROP_RESIZE_WITH_MAX_POOL': False,
'CUDA': False,
'DATA_DIR': '/home/xuyifei/桌面/Git/Git/rcnn-pytorch1.0_new/faster-rcnn.pytorch/data',
'DEDUP_BOXES': 0.0625,
'EPS': 1e-14,
'EXP_DIR': 'vgg16',
'FEAT_STRIDE': [16],
'GPU_ID': 0,
'MATLAB': 'matlab',
'MAX_NUM_GT_BOXES': 20,
'MOBILENET': {'DEPTH_MULTIPLIER': 1.0,
              'FIXED_LAYERS': 5,
              'REGU_DEPTH': False,
              'WEIGHT_DECAY': 4e-05},
'PIXEL_MEANS': array([[[102.9801, 115.9465, 122.7717]]]),
'POOLING_MODE': 'align',
'POOLING_SIZE': 7,
'RESNET': {'FIXED_BLOCKS': 1, 'MAX_POOL': False},
'RNG_SEED': 3,
'ROOT_DIR': '/home/xuyifei/桌面/Git/Git/rcnn-pytorch1.0_new/faster-rcnn.pytorch',
'TEST': {'BBOX_REG': True,
         'HAS_RPN': True,
         'MAX_SIZE': 1000,
         'MODE': 'nms',
         'NMS': 0.3,
         'PROPOSAL_METHOD': 'gt',
         'RPN_MIN_SIZE': 16,
         'RPN_NMS_THRESH': 0.7,
         'RPN_POST_NMS_TOP_N': 300,
         'RPN_PRE_NMS_TOP_N': 6000,
         'RPN_TOP_N': 5000,
         'SCALES': [600],
         'SVM': False},
'TRAIN': {'ASPECT_GROUPING': False,
          'BATCH_SIZE': 256,
          'BBOX_INSIDE_WEIGHTS': [1.0, 1.0, 1.0, 1.0],
          'BBOX_NORMALIZE_MEANS': [0.0, 0.0, 0.0, 0.0],
          'BBOX_NORMALIZE_STDS': [0.1, 0.1, 0.2, 0.2],
          'BBOX_NORMALIZE_TARGETS': True,
          'BBOX_NORMALIZE_TARGETS_PRECOMPUTED': True,
          'BBOX_REG': True,
          'BBOX_THRESH': 0.5,
          'BG_THRESH_HI': 0.5,
          'BG_THRESH_LO': 0.0,
          'BIAS_DECAY': False,
          'BN_TRAIN': False,
          'DISPLAY': 10,
          'DOUBLE_BIAS': True,
          'FG_FRACTION': 0.25,
          'FG_THRESH': 0.5,
          'GAMMA': 0.1,
          'HAS_RPN': True,
          'IMS_PER_BATCH': 1,
          'LEARNING_RATE': 0.01,
          'MAX_SIZE': 1000,
          'MOMENTUM': 0.9,
          'PROPOSAL_METHOD': 'gt',
          'RPN_BATCHSIZE': 256,
          'RPN_BBOX_INSIDE_WEIGHTS': [1.0, 1.0, 1.0, 1.0],
          'RPN_CLOBBER_POSITIVES': False,
          'RPN_FG_FRACTION': 0.5,
          'RPN_MIN_SIZE': 8,
          'RPN_NEGATIVE_OVERLAP': 0.3,
          'RPN_NMS_THRESH': 0.7,
          'RPN_POSITIVE_OVERLAP': 0.7,
          'RPN_POSITIVE_WEIGHT': -1.0,
          'RPN_POST_NMS_TOP_N': 2000,
          'RPN_PRE_NMS_TOP_N': 12000,
          'SCALES': [600],
          'SNAPSHOT_ITERS': 5000,
          'SNAPSHOT_KEPT': 3,
          'SNAPSHOT_PREFIX': 'res101_faster_rcnn',
          'STEPSIZE': [30000],
          'SUMMARY_INTERVAL': 180,
          'TRIM_HEIGHT': 600,
          'TRIM_WIDTH': 600,
          'TRUNCATED': False,
          'USE_ALL_GT': True,
          'USE_FLIPPED': True,
          'USE_GT': False,
          'WEIGHT_DECAY': 0.0005},
'USE_GPU_NMS': True}
Loaded dataset `voc_2007_trainval` for training
Set proposal method: gt
Appending horizontally-flipped training examples...
voc_2007_trainval gt roidb loaded from /home/xuyifei/桌面/Git/Git/rcnn-pytorch1.0_new/faster-rcnn.pytorch/data/cache/voc_2007_trainval_gt_roidb.pkl
done
Preparing training data...
done
before filtering, there are 10022 images...
after filtering, there are 10022 images...
10022 roidb entries
Loading pretrained weights from data/pretrained_model/vgg16_caffe.pth
THCudaCheck FAIL file=/home/xuyifei/桌面/Git/Git/rcnn-pytorch1.0_new/faster-rcnn.pytorch/lib/model/csrc/cuda/ROIAlign_cuda.cu line=297 error=98 : unrecognized error code
Traceback (most recent call last):
 File "trainval_net.py", line 321, in <module>
   rois_label = fasterRCNN(im_data, im_info, gt_boxes, num_boxes)
 File "/home/xuyifei/anaconda3/envs/pytorch_2/lib/python3.7/site-packages/torch/nn/modules/module.py", line 489, in __call__
   result = self.forward(*input, **kwargs)
 File "/home/xuyifei/桌面/Git/Git/rcnn-pytorch1.0_new/faster-rcnn.pytorch/lib/model/faster_rcnn/faster_rcnn.py", line 77, in forward
   pooled_feat = self.RCNN_roi_align(base_feat, rois.view(-1, 5))
 File "/home/xuyifei/anaconda3/envs/pytorch_2/lib/python3.7/site-packages/torch/nn/modules/module.py", line 489, in __call__
   result = self.forward(*input, **kwargs)
 File "/home/xuyifei/桌面/Git/Git/rcnn-pytorch1.0_new/faster-rcnn.pytorch/lib/model/roi_layers/roi_align.py", line 58, in forward
   input, rois, self.output_size, self.spatial_scale, self.sampling_ratio
 File "/home/xuyifei/桌面/Git/Git/rcnn-pytorch1.0_new/faster-rcnn.pytorch/lib/model/roi_layers/roi_align.py", line 20, in forward
   output = _C.roi_align_forward(input, roi, spatial_scale, output_size[0], output_size[1], sampling_ratio)
RuntimeError: cuda runtime error (98) : unrecognized error code at /home/xuyifei/桌面/Git/Git/rcnn-pytorch1.0_new/faster-rcnn.pytorch/lib/model/csrc/cuda/ROIAlign_cuda.cu:297
段错误 (核心已转储)

ubuntu 18.04 python 3.7 gcc 7.5 cuda 10.0 Geforce RTX 2060

Could somebody help me?

[zhangshen12356]

did you solve it?

[wwcc1107]

Install cudatoolKit that matches your PyTorch version