code: def _column_or_1d(y, warn=False):
      y = np.asarray(y)
  
      # TODO: Convert this kind of arrays to a table like in daal4py
      if not y.flags.aligned and not y.flags.writeable:
          y = np.array(y.tolist())
  
      shape = np.shape(y)
      if len(shape) == 1:
          return np.ravel(y)
      if len(shape) == 2 and shape[1] == 1:
          if warn:
              warnings.warn(
                  "A column-vector y was passed when a 1d array was"
                  " expected. Please change the shape of y to "
                  "(n_samples, ), for example using ravel().",
                  DataConversionWarning,
                  stacklevel=2,
              )
          return np.ravel(y)
  
      raise ValueError(
          "y should be a 1d array, "
          "got an array of shape {} instead.".format(shape)
      )
  
imports: import warnings
  from collections.abc import Sequence
  from numbers import Integral
  import numpy
  from scipy import sparse
  from sklearn.preprocessing import LabelEncoder
  from sklearn.utils.validation import check_array
  from daal4py.sklearn.utils.validation import _assert_all_finite
label_desc: Use image node_id 3 for calling a global function with example usage: _column_or_1d(y, warn) and returns: np, np