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Fine-tune pretrained Convolutional Neural Networks with PyTorch

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When I am trying to run examples/cifar10.py with Inception-Resnet-v2, i am getting the following error: RuntimeError: Calculated padded input size per channel: (1 x 1). Kernel size: (3 x 3)....

hello, i finetune the pre-trained inception_v4 model with 3 classes,by model=make_model('inception_v4',3,pretrained=True) , and saved the trained-model as 'model.pth' by torch.save(model.state_dict(),'model.pth') but when i restored the model by model = make_model('inception_v4',3,pretrained=False)...

What does your network “output ” include? “output = model(data) ” Is “output.data () ” a logical value? I want to get the classification probability, how do I get it?...

Hi, I found this annoying feature/bug as one may like to: ``` def forward(self, x): x = self.features(x) if self.pool is not None: x = self.pool(x) if self.dropout is not...