i use the pretrained vgg16_bn downloaded from torchvision for images classification.First, extracting the feature from the first full connection layers. Then, some of  4096-d features are trained for liblinear. After the SVM training, rest of the features are tested.
The same operation is implemented on the caffe and matconvnet. Comparing the three results, I find the model’s performance from torchvision is the worst.I want to know wether other people face the same problem, or my method is wrong. And i have one more question is that how can i use the pretrained model from other deep learning platform on the pytorch. Thank you in advance.