code: def _partial_fit_binary(estimator, X, y):
      """Partially fit a single binary estimator."""
      estimator.partial_fit(X, y, np.array((0, 1)))
      return estimator
  
imports: import array
  import numpy
  import warnings
  import scipy.sparse
  import itertools
  from .base import BaseEstimator, ClassifierMixin, clone, is_classifier
  from .base import MetaEstimatorMixin, is_regressor
  from .preprocessing import LabelBinarizer
  from .metrics.pairwise import euclidean_distances
  from .utils import check_random_state
  from .utils.validation import _num_samples
  from .utils.validation import check_is_fitted
  from .utils.validation import check_X_y
  from .utils.multiclass import _check_partial_fit_first_call, check_classification_targets, _ovr_decision_function
  from .utils.metaestimators import _safe_split
  from .externals.joblib import Parallel
  from .externals.joblib import delayed
  from .externals.six.moves import zip
label_desc: Use image node_id 2 for calling a global function with example usage: _partial_fit_binary(estimator, X, y) and returns: estimator