2017-08-22 8 views
1

Sur ubuntu14.04, j'utilise pytorch avec le problème cudnn.This est arrivé:RuntimeError: CUDNN_STATUS_INTERNAL_ERROR

Traceback (most recent call last): 
    File "main.py", line 58, in <module> 
    test_detect(test_loader, nod_net, get_pbb, bbox_result_path,config1,n_gpu=config_submit['n_gpu']) 
    File "/home/ubuntu/nndl/DSB2017/test_detect.py", line 52, in test_detect 
    output = net(input,inputcoord) 
    File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/torch/nn/modules/module.py", line 252, in __call__ 
    result = self.forward(*input, **kwargs) 
    File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/torch/nn/parallel/data_parallel.py", line 58, in forward 
    return self.module(*inputs[0], **kwargs[0]) 
    File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/torch/nn/modules/module.py", line 252, in __call__ 
    result = self.forward(*input, **kwargs) 
    File "/home/ubuntu/nndl/DSB2017/net_detector.py", line 102, in forward 
    out = self.preBlock(x)#16 
    File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/torch/nn/modules/module.py", line 252, in __call__ 
    result = self.forward(*input, **kwargs) 
    File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/torch/nn/modules/container.py", line 67, in forward 
    input = module(input) 
    File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/torch/nn/modules/module.py", line 252, in __call__ 
    result = self.forward(*input, **kwargs) 
    File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/torch/nn/modules/conv.py", line 351, in forward 
    self.padding, self.dilation, self.groups) 
    File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/torch/nn/functional.py", line 119, in conv3d 
    return f(input, weight, bias) 
RuntimeError: CUDNN_STATUS_INTERNAL_ERROR 

J'ai google pendant des heures severial un matin vraiment confused.What rendu cela?

+0

Le GPU est GTX1080Ti.CUDA8.0, cuDNN5.1 –

Répondre

2

Je viens de rencontrer ce problème sur Ubuntu16.04 et l'ai résolu. Ma solution a été

sudo rm -rf ~/.NV

puis redémarrez.