TODO: implement Images2Neibs.infer_shape() methods
Parameters: |
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Returns: | Reshapes the input as a 2D tensor where each row is an pooling example. Pseudo-code of the output: idx = 0
for i in xrange(list 1 dim)
for j in xrange(list 2 dim)
for k in <image column coordinates>
for l in <image row coordinates>
output[idx,:]
= flattened version of ten4[i,j,l:l+r,k:k+c]
idx += 1
(note: the op isn't necessarily implemented internally with these
for loops, they're just the easiest way to describe the output
pattern)
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Inverse of images2neib.
Parameters: |
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Returns: | Return a 4d tensor of shape original_shape. |