Argument convention in PyTorch
I am new to PyTorch and while going through the examples, I noticed that sometimes functions have a different convention when accepting arguments. For example transforms.Compose receives a list as its argument:
pytorch
Best way to save a trained model in PyTorch?
I was looking for alternative ways to save a trained model in PyTorch. So far, I have found two alternatives. torch.save() to save a model and torch.load() to load a model. model.state_dict() to save a trained model and model.load_state_dict() to load the saved model. I have come across to this discussion where approach 2 is … Read more
What does model.train() do in PyTorch?
Does it call forward() in nn.Module? I thought when we call the model, forward method is being used.
Why do we need to specify train()?
Why do we need to call zero_grad() in PyTorch?
Why does zero_grad() need to be called during training?
What does model.eval() do in pytorch?
When should I use .eval()? I understand it is supposed to allow me to “evaluate my model”. How do I turn it back off for training?
How does Pytorch’s “Fold” and “Unfold” work?
I’ve gone through the official doc. I’m having a hard time understanding what this function is used for and how it works. Can someone explain this in layman’s terms?
What’s the difference between reshape and view in pytorch?
In numpy, we use ndarray.reshape() for reshaping an array.