code: def _set_inputs(self, inputs):
      super()._set_inputs(inputs)
      if isinstance(self.y, ENTITY_TYPE):
          self.y = self._inputs[0]
      if isinstance(self.classes, ENTITY_TYPE):
          self.classes = self._inputs[-1]
  
imports: from typing import Union
  import numpy
  import scipy.sparse
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.preprocessing import label_binarize
  from sklearn.utils.sparsefuncs import min_max_axis
  from ...None import execute, fetch
  from ...None import opcodes
  from ...None import tensor
  from ...core import ENTITY_TYPE, OutputType, recursive_tile
  from ...core.context import get_context, Context
  from ...lib.sparse import SparseNDArray
  from ...serialization.serializables import AnyField, BoolField, Int32Field, StringField
  from ...tensor.core import TensorOrder
  from ...typing import TileableType
  from ..operands import LearnOperand, LearnOperandMixin
  from ..utils import column_or_1d
  from ..utils._encode import _unique, _encode
  from ..utils.multiclass import unique_labels, type_of_target
  from ..utils.validation import _num_samples, check_is_fitted, check_array
label_desc: Use image node_id 2 for calling the LabelBinarize obj's underlying member method code with example usage: obj._set_inputs(inputs) without return types