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x=rand(10)
and then to reshape x to a (5,2) array, write either
reshape(x, (5, -1))
or
reshape(x, (-1, 2))
instead of
reshape(x, (5,2))
It's convenient since one of the dimensions to reshape is always implicitly defined by the other, and numpy lets you use -1 to signal the dimension whose value should be inferred from the others.
Any interest in having julia's reshape have the same functionality? I could implement it.