flopscope.

flopscope.numpy.dsplit

fnp.dsplit(ary, indices_or_sections)[flopscope source][numpy source]

Split array into multiple sub-arrays along the 3rd axis (depth).

Adapted from NumPy docs np.dsplit

Areacore
Typefree
NumPy Refnp.dsplit
Cost
0
Flopscope Context

Split array into multiple sub-arrays depth-wise. Cost: numel(output).

Please refer to the split documentation. dsplit is equivalent to split with axis=2, the array is always split along the third axis provided the array dimension is greater than or equal to 3.

See also

Examples

>>> import flopscope.numpy as fnp
>>> x = flops.arange(16.0).reshape(2, 2, 4)
>>> x
array([[[ 0.,   1.,   2.,   3.],
        [ 4.,   5.,   6.,   7.]],
       [[ 8.,   9.,  10.,  11.],
        [12.,  13.,  14.,  15.]]])
>>> flops.dsplit(x, 2)
[array([[[ 0.,  1.],
        [ 4.,  5.]],
       [[ 8.,  9.],
        [12., 13.]]]), array([[[ 2.,  3.],
        [ 6.,  7.]],
       [[10., 11.],
        [14., 15.]]])]
>>> flops.dsplit(x, flops.array([3, 6]))
[array([[[ 0.,   1.,   2.],
        [ 4.,   5.,   6.]],
       [[ 8.,   9.,  10.],
        [12.,  13.,  14.]]]),
 array([[[ 3.],
        [ 7.]],
       [[11.],
        [15.]]]),
array([], shape=(2, 2, 0), dtype=float64)]