code: def _preprocess_for_cut(x):
      """
      handles preprocessing for cut where we convert passed
      input to array, strip the index information and store it
      separately
      """
      x_is_series = isinstance(x, Series)
      series_index = None
      name = None
  
      if x_is_series:
          series_index = x.index
          name = x.name
  
      # Check that the passed array is a Pandas or Numpy object
      # We don't want to strip away a Pandas data-type here (e.g. datetimetz)
      ndim = getattr(x, "ndim", None)
      if ndim is None:
          x = np.asarray(x)
      if x.ndim != 1:
          raise ValueError("Input array must be 1 dimensional")
  
      return x_is_series, series_index, name, x
  
file_path: catboost/contrib/python/pandas/py2/pandas/core/reshape/tile.py
imports: from functools import partial
  import numpy
  from pandas._libs.lib import infer_dtype
  from pandas.core.dtypes.common import _NS_DTYPE, ensure_int64, is_categorical_dtype, is_datetime64_dtype, is_datetime64tz_dtype, is_datetime_or_timedelta_dtype, is_integer, is_scalar, is_timedelta64_dtype
  from pandas.core.dtypes.missing import isna
  from pandas import Categorical, Index, Interval, IntervalIndex, Series, Timedelta, Timestamp, to_datetime, to_timedelta
  import pandas.core.algorithms
  import pandas.core.nanops
label_desc: Use image node_id 9 for calling a global function with example usage: _preprocess_for_cut(x) and returns: x_is_series,  series_index,  name,  x