code: def paired_euclidean_distances(X, Y):
      """
      Computes the paired euclidean distances between X and Y
  
      Read more in the :ref:`User Guide <metrics>`.
  
      Parameters
      ----------
      X : array-like, shape (n_samples, n_features)
  
      Y : array-like, shape (n_samples, n_features)
  
      Returns
      -------
      distances : ndarray (n_samples, )
      """
      X, Y = check_paired_arrays(X, Y)
      return row_norms(X - Y)
  
imports: import itertools
  import numpy
  from scipy.spatial import distance
  from scipy.sparse import csr_matrix
  from scipy.sparse import issparse
  from ..utils import check_array
  from ..utils import gen_even_slices
  from ..utils import gen_batches
  from ..utils.fixes import partial
  from ..utils.extmath import row_norms, safe_sparse_dot
  from ..preprocessing import normalize
  from ..externals.joblib import Parallel
  from ..externals.joblib import delayed
  from ..externals.joblib import cpu_count
  from .pairwise_fast import _chi2_kernel_fast, _sparse_manhattan
label_desc: Use image node_id 9 for calling a global function with example usage: paired_euclidean_distances(X, Y) and returns: row_norms