code: def unique_labels(*ys):
      """Extract an ordered array of unique labels
  
      We don't allow:
          - mix of multilabel and multiclass (single label) targets
          - mix of label indicator matrix and anything else,
            because there are no explicit labels)
          - mix of label indicator matrices of different sizes
          - mix of string and integer labels
  
      At the moment, we also don't allow "multiclass-multioutput" input type.
  
      Parameters
      ----------
      *ys : array-likes
  
      Returns
      -------
      out : numpy array of shape [n_unique_labels]
          An ordered array of unique labels.
  
      Examples
      --------
      >>> from sklearn.utils.multiclass import unique_labels
      >>> unique_labels([3, 5, 5, 5, 7, 7])
      array([3, 5, 7])
      >>> unique_labels([1, 2, 3, 4], [2, 2, 3, 4])
      array([1, 2, 3, 4])
      >>> unique_labels([1, 2, 10], [5, 11])
      array([ 1,  2,  5, 10, 11])
      """
      if not ys:
          raise ValueError("No argument has been passed.")
      # Check that we don't mix label format
  
      ys_types = set(type_of_target(x) for x in ys)
      if ys_types == {"binary", "multiclass"}:
          ys_types = {"multiclass"}
  
      if len(ys_types) > 1:
          raise ValueError(
              "Mix type of y not allowed, got types %s" % ys_types
          )
  
      label_type = ys_types.pop()
  
      # Get the unique set of labels
      _unique_labels = _FN_UNIQUE_LABELS.get(label_type, None)
      if not _unique_labels:
          raise ValueError("Unknown label type: %s" % repr(ys))
  
      ys_labels = set(
          chain.from_iterable(_unique_labels(y) for y in ys)
      )
  
      # Check that we don't mix string type with number type
      if len(set(isinstance(label, str) for label in ys_labels)) > 1:
          raise ValueError(
              "Mix of label input types (string and number)"
          )
  
      return np.array(sorted(ys_labels))
  
imports: from collections.abc import Sequence
  from itertools import chain
  from scipy.sparse import issparse
  from scipy.sparse.base import spmatrix
  from scipy.sparse import dok_matrix
  from scipy.sparse import lil_matrix
  import scipy.sparse
  import numpy
  import pandas
label_desc: Use image node_id 5 for calling a global function with example usage: unique_labels() and returns: np