code: def __init__(
      self,
      y_true=None,
      y_pred=None,
      normalize=None,
      sample_weight=None,
      type_true=None,
      **kw,
  ):
      super().__init__(
          _y_true=y_true,
          _y_pred=y_pred,
          _normalize=normalize,
          _sample_weight=sample_weight,
          _type_true=type_true,
          **kw,
      )
      self.output_types = [OutputType.tensor]
  
imports: import warnings
  import numpy
  from sklearn.exceptions import UndefinedMetricWarning
  from ...None import execute, fetch
  from ...None import opcodes
  from ...None import tensor
  from ...core import ENTITY_TYPE, recursive_tile
  from ...core.context import get_context
  from ...serialization.serializables import AnyField, BoolField, KeyField
  from ...tensor.core import TensorOrder
  from ..operands import LearnOperand, LearnOperandMixin, OutputType
  from ..preprocessing import LabelBinarizer, LabelEncoder
  from ..utils import check_array, check_consistent_length, column_or_1d
  from ..utils.multiclass import unique_labels
  from ..utils.sparsefuncs import count_nonzero
  from ._check_targets import _check_targets
label_desc: Use image node_id 1 to create a new AccuracyScore object from inherited base classes: LearnOperand, LearnOperandMixin with example: obj = AccuracyScore(y_true, y_pred, normalize, sample_weight, type_true)