code: def is_multilabel(y):
      """Check if ``y`` is in a multilabel format.
  
      Parameters
      ----------
      y : numpy array of shape [n_samples]
          Target values.
  
      Returns
      -------
      out : bool,
          Return ``True``, if ``y`` is in a multilabel format, else ```False``.
  
      Examples
      --------
      >>> import numpy as np
      >>> from sklearn.utils.multiclass import is_multilabel
      >>> is_multilabel([0, 1, 0, 1])
      False
      >>> is_multilabel([[1], [0, 2], []])
      False
      >>> is_multilabel(np.array([[1, 0], [0, 0]]))
      True
      >>> is_multilabel(np.array([[1], [0], [0]]))
      False
      >>> is_multilabel(np.array([[1, 0, 0]]))
      True
      """
      if hasattr(y, "__array__"):
          y = np.asarray(y)
      if not (hasattr(y, "shape") and y.ndim == 2 and y.shape[1] > 1):
          return False
  
      if issparse(y):
          if isinstance(y, (dok_matrix, lil_matrix)):
              y = y.tocsr()
          return (
              len(y.data) == 0
              or np.unique(y.data).size == 1
              and (
                  y.dtype.kind in "biu"
                  or _is_integral_float(  # bool, int, uint
                      np.unique(y.data)
                  )
              )
          )
      else:
          labels = np.unique(y)
  
          return len(labels) < 3 and (
              y.dtype.kind in "biu"
              or _is_integral_float(labels)  # bool, int, uint
          )
  
imports: from __future__ import division
  from collections 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 numpy
  from ..externals.six import string_types
  from .validation import check_array
  from ..utils.fixes import bincount
  from ..utils.fixes import array_equal
label_desc: Use image node_id 5 for calling a global function with example usage: is_multilabel(y) and returns: False, unknown, unknown