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I come to feel a very good example (prevalent scenario early on in pytorch before the flatten layer was official additional was this frequent code):

@MaxB Compared with reshape, The brand new tensor returned by "view" shares the underlying knowledge with the first tensor, so it is known as a view in to the aged tensor in its place of creating a fresh just one.

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A different intriguing detail 1 could notice with the strides tuples top article would be that the price of the component during the 0th position is equal to the worth of the ingredient during the 1st place of the shape learn this here now tuple.

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Ways to restructure the output tensor of a cnn layer to be used by a linear layer in an easy pytorch design three

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