Have you ever tried to plot a PyTorch tensor with matplotlib like: plt.plot(tensor) and then received the following error? AttributeError: 'Tensor' object has no attribute 'ndim' You can get around this easily by letting all PyTorch tensors know how to respond to ndim like this: torch.Tensor.ndim = property(lambda self: len(self.shape)) Basically, this uses the property decorator to create ndim as a property which reads its value as the length of self.
Recent advances in training deep neural networks have led to a whole bunch of impressive machine learning models which are able to tackle a very diverse range of tasks. When you are developing such a model, one of the notable downsides is that it is considered a “black-box” approach in the sense that your model learns from data you feed it, but you don't really know what is going on inside the model.
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