code: def attach(logger_module: Union[str, ModuleType]) -> None:
      """
      Attach the usage logger.
  
      Parameters
      ----------
      logger_module : the module or module name contains the usage logger.
          The module needs to provide `get_logger` function as an entry point of the plug-in
          returning the usage logger.
  
      See Also
      --------
      usage_logger : the reference implementation of the usage logger.
      """
  
      modules = [config, namespace]
      classes = [
          DataFrame,
          Series,
          Index,
          MultiIndex,
          CategoricalIndex,
          DatetimeIndex,
          DataFrameGroupBy,
          SeriesGroupBy,
          DatetimeMethods,
          StringMethods,
          Expanding,
          ExpandingGroupby,
          Rolling,
          RollingGroupby,
          ExponentialMoving,
          ExponentialMovingGroupby,
          CachedSparkFrameMethods,
          SparkFrameMethods,
          SparkIndexOpsMethods,
          PandasOnSparkFrameMethods,
      ]
  
      try:
          from pyspark.pandas import mlflow
  
          modules.append(mlflow)
          classes.append(mlflow.PythonModelWrapper)
      except ImportError:
          pass
  
      sql_formatter._CAPTURE_SCOPES = 4
      modules.append(sql_formatter)
  
      missings = [
          (pd, MissingPandasLikeGeneralFunctions),
          (pd.DataFrame, MissingPandasLikeDataFrame),
          (pd.Series, MissingPandasLikeSeries),
          (pd.Index, MissingPandasLikeIndex),
          (pd.MultiIndex, MissingPandasLikeMultiIndex),
          (pd.DatetimeIndex, MissingPandasLikeDatetimeIndex),
          (
              pd.core.groupby.DataFrameGroupBy,
              MissingPandasLikeDataFrameGroupBy,
          ),
          (
              pd.core.groupby.SeriesGroupBy,
              MissingPandasLikeSeriesGroupBy,
          ),
          (pd.core.window.Expanding, MissingPandasLikeExpanding),
          (pd.core.window.Rolling, MissingPandasLikeRolling),
          (
              pd.core.window.ExpandingGroupby,
              MissingPandasLikeExpandingGroupby,
          ),
          (
              pd.core.window.RollingGroupby,
              MissingPandasLikeRollingGroupby,
          ),
          (
              pd.core.window.ExponentialMovingWindow,
              MissingPandasLikeExponentialMoving,
          ),
          (
              pd.core.window.ExponentialMovingWindowGroupby,  # type: ignore[attr-defined]
              MissingPandasLikeExponentialMovingGroupby,
          ),
      ]
  
      _attach(logger_module, modules, classes, missings)
  
imports: from types import ModuleType
  from typing import Union
  import pandas
  from pyspark.pandas import config, namespace, sql_formatter
  from pyspark.pandas.accessors import PandasOnSparkFrameMethods
  from pyspark.pandas.frame import DataFrame
  from pyspark.pandas.datetimes import DatetimeMethods
  from pyspark.pandas.groupby import DataFrameGroupBy, SeriesGroupBy
  from pyspark.pandas.indexes.base import Index
  from pyspark.pandas.indexes.category import CategoricalIndex
  from pyspark.pandas.indexes.datetimes import DatetimeIndex
  from pyspark.pandas.indexes.multi import MultiIndex
  from pyspark.pandas.missing.frame import MissingPandasLikeDataFrame
  from pyspark.pandas.missing.general_functions import MissingPandasLikeGeneralFunctions
  from pyspark.pandas.missing.groupby import MissingPandasLikeDataFrameGroupBy, MissingPandasLikeSeriesGroupBy
  from pyspark.pandas.missing.indexes import MissingPandasLikeDatetimeIndex, MissingPandasLikeIndex, MissingPandasLikeMultiIndex
  from pyspark.pandas.missing.series import MissingPandasLikeSeries
  from pyspark.pandas.missing.window import MissingPandasLikeExpanding, MissingPandasLikeRolling, MissingPandasLikeExpandingGroupby, MissingPandasLikeRollingGroupby, MissingPandasLikeExponentialMoving, MissingPandasLikeExponentialMovingGroupby
  from pyspark.pandas.series import Series
  from pyspark.pandas.spark.accessors import CachedSparkFrameMethods, SparkFrameMethods, SparkIndexOpsMethods
  from pyspark.pandas.strings import StringMethods
  from pyspark.pandas.window import Expanding, ExpandingGroupby, Rolling, RollingGroupby, ExponentialMoving, ExponentialMovingGroupby
  from pyspark.instrumentation_utils import _attach
label_desc: Use image node_id 1 for calling a global function with example usage: attach(logger_module) without return types