You will need to flatten this to offer it towards the fully connected layer. So that you notify PyTorch to reshape the tensor you obtained to own specific range of columns and explain to it to decide the amount of rows by alone.
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@MaxB As opposed to reshape, the new tensor returned by "view" shares the underlying information with the first tensor, so it is known as a view in the old tensor as an alternative of making a new just one.
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Here the thing is PyTorch makes a tensor by changing an underlying block of contiguous memory into a matrix-like object by adding a condition and stride attribute: