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7.3. Padding and Stride — Dive into Deep Learning 1.0.3 documentation
d2l.ai
lose pixels on the perimeter of our image since kernels generally have width and height greater than outputs that are considerably smaller than our input. give the input and output the same height and width. preserve the dimensionality while padding with the same number of rows on top and bottom, an
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lose pixels on the perimeter of our image
since kernels generally have width and height greater than
outputs that are considerably smaller than our input.
give the input and output the same height and width.
preserve the dimensionality while padding with the same number of rows on top and bottom, and the same number of columns on left and right.
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d2l.ai
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