class_docstr: Not sure if I can avoid the state machine here
class_docstr_tok: ["Not","sure","if","I","can","avoid","the","state","machine","here"]
code: def __init__(self, index) -> None:
      self.index = index
      self.i8values = index.asi8
  
      # For get_unit_from_dtype we need the dtype to the underlying ndarray,
      #  which for tz-aware is not the same as index.dtype
      if isinstance(index, ABCIndex):
          # error: Item "ndarray[Any, Any]" of "Union[ExtensionArray,
          # ndarray[Any, Any]]" has no attribute "_ndarray"
          self._creso = get_unit_from_dtype(
              index._data._ndarray.dtype  # type: ignore[union-attr]
          )
      else:
          # otherwise we have DTA/TDA
          self._creso = get_unit_from_dtype(index._ndarray.dtype)
  
      # This moves the values, which are implicitly in UTC, to the
      # the timezone so they are in local time
      if hasattr(index, "tz"):
          if index.tz is not None:
              self.i8values = tz_convert_from_utc(
                  self.i8values, index.tz, reso=self._creso
              )
  
      if len(index) < 3:
          raise ValueError("Need at least 3 dates to infer frequency")
  
      self.is_monotonic = (
          self.index._is_monotonic_increasing
          or self.index._is_monotonic_decreasing
      )
  
imports: from __future__ import annotations
  import numpy
  from pandas._libs.algos import unique_deltas
  from pandas._libs.tslibs import Timestamp, get_unit_from_dtype, periods_per_day, tz_convert_from_utc
  from pandas._libs.tslibs.ccalendar import DAYS, MONTH_ALIASES, MONTH_NUMBERS, MONTHS, int_to_weekday
  from pandas._libs.tslibs.fields import build_field_sarray, month_position_check
  from pandas._libs.tslibs.offsets import DateOffset, Day, to_offset
  from pandas._libs.tslibs.parsing import get_rule_month
  from pandas._typing import npt
  from pandas.util._decorators import cache_readonly
  from pandas.core.dtypes.common import is_datetime64_dtype, is_numeric_dtype, is_period_dtype, is_timedelta64_dtype
  from pandas.core.dtypes.generic import ABCIndex, ABCSeries
  from pandas.core.algorithms import unique
label_desc: Use image node_id 1 to create a new _FrequencyInferer object  with example: obj = _FrequencyInferer(index)