code: def unique_rows(in_array, dtype="f4"):
      """Find the unique rows in an array.
  
      Parameters
      ----------
      in_array: ndarray
          The array for which the unique rows should be found
  
      dtype: str, optional
          This determines the intermediate representation used for the
          values. Should at least preserve the values of the input array.
  
      Returns
      -------
      u_return: ndarray
         Array with the unique rows of the original array.
  
      """
      # Sort input array
      order = np.lexsort(in_array.T)
  
      # Apply sort and compare neighbors
      x = in_array[order]
      diff_x = np.ones(len(x), dtype=bool)
      diff_x[1:] = (x[1:] != x[:-1]).any(-1)
  
      # Reverse sort and return unique rows
      un_order = order.argsort()
      diff_in_array = diff_x[un_order]
      return in_array[diff_in_array]
  
imports: from collections import defaultdict, OrderedDict
  from functools import wraps
  from itertools import combinations, groupby
  from warnings import warn
  import numpy
  from nibabel.affines import apply_affine
  from scipy.spatial.distance import cdist
  from dipy.core.geometry import dist_to_corner
  from dipy.tracking import metrics
  from dipy.tracking.vox2track import _streamlines_in_mask
  from dipy.tracking._utils import _mapping_to_voxel, _to_voxel_coordinates
label_desc: Use image node_id 14 for calling a global function with example usage: unique_rows(in_array, dtype) and returns: in_array