code: def check_paired_arrays(X, Y):
      """Set X and Y appropriately and checks inputs for paired distances
  
      All paired distance metrics should use this function first to assert that
      the given parameters are correct and safe to use.
  
      Specifically, this function first ensures that both X and Y are arrays,
      then checks that they are at least two dimensional while ensuring that
      their elements are floats. Finally, the function checks that the size
      of the dimensions of the two arrays are equal.
  
      Parameters
      ----------
      X : {array-like, sparse matrix}, shape (n_samples_a, n_features)
  
      Y : {array-like, sparse matrix}, shape (n_samples_b, n_features)
  
      Returns
      -------
      safe_X : {array-like, sparse matrix}, shape (n_samples_a, n_features)
          An array equal to X, guaranteed to be a numpy array.
  
      safe_Y : {array-like, sparse matrix}, shape (n_samples_b, n_features)
          An array equal to Y if Y was not None, guaranteed to be a numpy array.
          If Y was None, safe_Y will be a pointer to X.
  
      """
      X, Y = check_pairwise_arrays(X, Y)
      if X.shape != Y.shape:
          raise ValueError(
              "X and Y should be of same shape. They were "
              "respectively %r and %r long." % (X.shape, Y.shape)
          )
      return 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 3 for calling a global function with example usage: check_paired_arrays(X, Y) and returns: X,  Y