我想提取VGG16模型中最後一層的激活。爲此,我在模型上使用了一個裝飾器,如下所示。使用pregrained vgg16模型的CUDNN錯誤
當我將一個cuda張量傳遞給模型時,我得到一個CUDNN_STATUS_INTERNAL_ERROR和下面的回溯。
任何人都知道我錯了哪裏?
回溯:
File "/media/data1/iftachg/frame_glimpses/parse_files_to_vgg.py", line 80, in get_activation
return model(image)
File "/media/data1/iftachg/miniconda2/lib/python2.7/site-packages/torch/nn/modules/module.py", line 206, in __call__
result = self.forward(*input, **kwargs)
File "/media/data1/iftachg/frame_glimpses/partial_vgg.py", line 24, in forward
x = self.vgg16.features(x)
File "/media/data1/iftachg/miniconda2/lib/python2.7/site-packages/torch/nn/modules/module.py", line 206, in __call__
result = self.forward(*input, **kwargs)
File "/media/data1/iftachg/miniconda2/lib/python2.7/site-packages/torch/nn/modules/container.py", line 64, in forward
input = module(input)
File "/media/data1/iftachg/miniconda2/lib/python2.7/site-packages/torch/nn/modules/module.py", line 206, in __call__
result = self.forward(*input, **kwargs)
File "/media/data1/iftachg/miniconda2/lib/python2.7/site-packages/torch/nn/modules/conv.py", line 237, in forward
self.padding, self.dilation, self.groups)
File "/media/data1/iftachg/miniconda2/lib/python2.7/site-packages/torch/nn/functional.py", line 39, in conv2d
return f(input, weight, bias)
RuntimeError: CUDNN_STATUS_INTERNAL_ERROR
類:
class partial_vgg(nn.Module):
def __init__(self):
super(partial_vgg, self).__init__()
self.vgg16 = models.vgg16(pretrained=True).cuda()
for param in self.vgg16.parameters():
param.requires_grad = False
def forward(self, x):
x = self.vgg16.features(x)
x = x.view(x.size(0), -1)
for l in list(self.vgg16.classifier.children())[:-3]:
x = l(x)
return x
不知道你的錯誤,但我認爲可能有一個更簡單的方法來做你想做的事情。看看我的答案,它解釋瞭如何使用預訓練模型並從中創建新模型/僅提取它的一部分以構建新模型:https://stackoverflow.com/questions/44146655/how-to-convert -pretrained-FC-層到CONV層合pytorch/44410334#44410334 – mexmex