How does the transpose work in three or more dimensions?

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For two-dimensaol array, according Guide to numpy

The two-styles of memory layout for arrays are connected through the transpose operation. Thus, if A is a (contiguous) C-style array, then the same block memory can be used to represent AT as a (contiguous) Fortran-style array. This kindof undorctondina non ho ucoful mhon trrina to orn mmonnina of Fortron

In three dimensional matrix

A = np.arange(6).reshape([1,2,3])

we can view A as a 1 by 1 block matrix, which means A has one entry, and that entry is a matrix with two rows and three columns.

So we can iteratively take the transpose according to the rules above.

My question is:

A= np.arange(6).reshape([1,2,3])
B = A.transpose(1,2,0)

In this case, how does it work. Is there a rule that can tell me how the elements of B are arranged

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