code: def time_features_from_frequency_str(offset) -> List[TimeFeature]:
      """
      Returns a list of time features that will be appropriate for the given frequency string.
      Parameters
      ----------
      freq_str
          Frequency string of the form [multiple][granularity] such as "12H", "5min", "1D" etc.
      """
  
      features_by_offsets = (
          (
              Timedelta(seconds=60),
              [
                  SecondOfMinute,
                  MinuteOfHour,
                  HourOfDay,
                  DayOfWeek,
                  DayOfMonth,
                  DayOfYear,
              ],
          ),  # 6 for second - minutes
          (
              Timedelta(minutes=60),
              [
                  MinuteOfHour,
                  HourOfDay,
                  DayOfWeek,
                  DayOfMonth,
                  DayOfYear,
              ],
          ),  # 5 for minutes - hour
          (
              Timedelta(hours=24),
              [HourOfDay, DayOfWeek, DayOfMonth, DayOfYear],
          ),  # 4 for hour - day
          (
              Timedelta(days=7),
              [DayOfWeek, DayOfMonth, DayOfYear],
          ),  # 3 for day - week
          (
              Timedelta(days=30),
              [DayOfMonth, WeekOfYear],
          ),  # 2 for week - month
          (Timedelta(days=365), [MonthOfYear]),  # 1 for month - year
      )
  
      for offset_type, feature_classes in features_by_offsets:
          if offset < offset_type:
              return [cls() for cls in feature_classes]
      return []
  
imports: from typing import List
  import numpy
  import pandas
  from pandas import Timedelta
  from pandas.tseries.frequencies import to_offset
  from bigdl.chronos.data.utils.roll import _roll_timeseries_ndarray
label_desc: Use image node_id 1 for calling a global function with example usage: time_features_from_frequency_str(offset) and returns: list, unknown