在numpy中，.sum(axis=n)解释：
如果，b是一个shap(5, 6, 7, 8)的numpy array，
然后，c = b.sum(axis=2)
那么，c的shape将是(5, 6, 8) ，因为“7”就是axis=2，被清除了。
而且，c[x, y, z] = sum( b[x, y, : , z])
If you do .sum(axis=n), for example, then dimension n is collapsed and deleted, with all values in the new matrix equal to the sum of the corresponding collapsed values. For example, if b has shape (5,6,7,8), and you do c, then axis 2 (dimension with size 7) is collapsed, and the result has shape
= b.sum(axis=2)(5,6,8). Furthermore, c[x,y,z] is equal to the sum of all elements c[x,y,:,z].
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