parameters: (ary, indices_or_sections)
return_statement: return split(ary, indices_or_sections, 2)
docstring: Split array into multiple sub-arrays 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 array dimension is greater than or equal to 3.
  
      See Also
      --------
      split : Split an array into multiple sub-arrays of equal size.
  
      Examples
      --------
      >>> x = np.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.]]])
      >>> np.dsplit(x, 2)
      [array([[[  0.,   1.],
              [  4.,   5.]],
             [[  8.,   9.],
              [ 12.,  13.]]]),
       array([[[  2.,   3.],
              [  6.,   7.]],
             [[ 10.,  11.],
              [ 14.,  15.]]])]
      >>> np.dsplit(x, np.array([3, 6]))
      [array([[[  0.,   1.,   2.],
              [  4.,   5.,   6.]],
             [[  8.,   9.,  10.],
              [ 12.,  13.,  14.]]]),
       array([[[  3.],
              [  7.]],
             [[ 11.],
              [ 15.]]]),
       array([], dtype=float64)]
docstring_summary: Split array into multiple sub-arrays along the 3rd axis (depth).
docstring_tokens: Split array into multiple sub - arrays along the 3rd axis ( depth ) .
function: def dsplit(ary, indices_or_sections):
      """
      Split array into multiple sub-arrays 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 array dimension is greater than or equal to 3.
  
      See Also
      --------
      split : Split an array into multiple sub-arrays of equal size.
  
      Examples
      --------
      >>> x = np.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.]]])
      >>> np.dsplit(x, 2)
      [array([[[  0.,   1.],
              [  4.,   5.]],
             [[  8.,   9.],
              [ 12.,  13.]]]),
       array([[[  2.,   3.],
              [  6.,   7.]],
             [[ 10.,  11.],
              [ 14.,  15.]]])]
      >>> np.dsplit(x, np.array([3, 6]))
      [array([[[  0.,   1.,   2.],
              [  4.,   5.,   6.]],
             [[  8.,   9.,  10.],
              [ 12.,  13.,  14.]]]),
       array([[[  3.],
              [  7.]],
             [[ 11.],
              [ 15.]]]),
       array([], dtype=float64)]
  
      """
      if len(_nx.shape(ary)) < 3:
          raise ValueError('vsplit only works on arrays of 3 or more dimensions')
      return split(ary, indices_or_sections, 2)
function_tokens: def dsplit ( ary , indices_or_sections ) : if len ( _nx . shape ( ary ) ) < 3 : raise ValueError ( 'vsplit only works on arrays of 3 or more dimensions' ) return split ( ary , indices_or_sections , 2 )