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from ..datasource import tensor as astensor
from .split import split
[docs]def dsplit(a, indices_or_sections):
"""
Split tensor into multiple sub-tensors along the 3rd axis (depth).
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 tensor dimension is greater than or equal to 3.
See Also
--------
split : Split a tensor into multiple sub-arrays of equal size.
Examples
--------
>>> import mars.tensor as mt
>>> x = mt.arange(16.0).reshape(2, 2, 4)
>>> x.execute()
array([[[ 0., 1., 2., 3.],
[ 4., 5., 6., 7.]],
[[ 8., 9., 10., 11.],
[ 12., 13., 14., 15.]]])
>>> mt.dsplit(x, 2).execute()
[array([[[ 0., 1.],
[ 4., 5.]],
[[ 8., 9.],
[ 12., 13.]]]),
array([[[ 2., 3.],
[ 6., 7.]],
[[ 10., 11.],
[ 14., 15.]]])]
>>> mt.dsplit(x, mt.array([3, 6])).execute()
[array([[[ 0., 1., 2.],
[ 4., 5., 6.]],
[[ 8., 9., 10.],
[ 12., 13., 14.]]]),
array([[[ 3.],
[ 7.]],
[[ 11.],
[ 15.]]]),
array([], dtype=float64)]
"""
ary = a
a = astensor(a)
if a.ndim < 3:
raise ValueError("dsplit only works on tensors of 3 or more dimensions")
return split(ary, indices_or_sections, 2)