code: def get_metrics(
      reset: bool = False,
      include_custom: bool = True,
      raise_errors: bool = True,
  ) -> pd.DataFrame:
      """
      Returns table of available metrics used in the experiment.
  
  
      Example
      -------
      >>> from pycaret.datasets import get_data
      >>> boston = get_data('boston')
      >>> from pycaret.regression import *
      >>> exp_name = setup(data = boston,  target = 'medv')
      >>> all_metrics = get_metrics()
  
  
      reset: bool, default = False
          When True, will reset all changes made using the ``add_metric``
          and ``remove_metric`` function.
  
  
      include_custom: bool, default = True
          Whether to include user added (custom) metrics or not.
  
  
      raise_errors: bool, default = True
          If False, will suppress all exceptions, ignoring models that
          couldn't be created.
  
  
      Returns:
          pandas.DataFrame
  
      """
  
      return _CURRENT_EXPERIMENT.get_metrics(
          reset=reset,
          include_custom=include_custom,
          raise_errors=raise_errors,
      )
  
imports: import logging
  import os
  from typing import Any, BinaryIO, Callable, Dict, List, Optional, Union
  import pandas
  from joblib.memory import Memory
  from pycaret.internal.parallel.parallel_backend import ParallelBackend
  from pycaret.loggers.base_logger import BaseLogger
  from pycaret.regression.oop import RegressionExperiment
  from pycaret.utils.constants import DATAFRAME_LIKE, SEQUENCE_LIKE, TARGET_LIKE
  from pycaret.utils.generic import check_if_global_is_not_none
label_desc: Use image node_id 21 for calling a global function with example usage: get_metrics(reset, include_custom, raise_errors) and returns: _CURRENT_EXPERIMENT