code: def _check_y(y, multi_output=False, y_numeric=False):
      """Isolated part of check_X_y dedicated to y validation"""
      # TODO: implement
      # if multi_output:
      #     y = check_array(
      #         y, accept_sparse="csr", force_all_finite=True, ensure_2d=False, dtype=None
      #     )
      # else:
      #     y = column_or_1d(y, warn=True)
      #     _assert_all_finite(y)
      #     _ensure_no_complex_data(y)
      # if y_numeric and y.dtype.kind == "O":
      #     y = y.astype(np.float64)
      return y
  
imports: import contextlib
  import datetime
  import functools
  import logging
  import warnings
  from collections.abc import Sequence
  from multiprocessing import cpu_count
  from numbers import Integral
  from timeit import default_timer
  import dask
  import dask.array
  import dask.dataframe
  import numpy
  import pandas
  import sklearn.utils.extmath
  import sklearn.utils.validation
  from dask import delayed
  from dask.array.utils import assert_eq
  from dask.dataframe.utils import assert_eq
  from ._utils import ConstantFunction
label_desc: Use image node_id 13 for calling a global function with example usage: _check_y(y, multi_output, y_numeric) and returns: y