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You must flatten this to provide it on the fully connected layer. So that you explain to PyTorch to reshape the tensor you acquired to possess distinct variety of columns and explain to it to decide the number of rows by by itself.
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I really feel a good example (popular circumstance early on in pytorch ahead of the flatten layer was official added was this widespread code):
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If there is any problem that you don't know the quantity of rows you wish but are sure of the quantity of columns, then you can specify this which has a -1. (
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Here the thing is PyTorch would make a tensor by changing an underlying block of contiguous memory into a matrix-like item by incorporating a form my site and stride attribute:
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