code: def convert_ag_metric_to_xgbm(ag_metric_name, problem_type):
      return _ag_to_xgbm_metric_dict.get(problem_type, dict()).get(
          ag_metric_name, None
      )
  
file_path: autogluon/tabular/src/autogluon/tabular/models/xgboost/xgboost_utils.py
imports: from collections import OrderedDict
  import numpy
  from scipy.sparse import csr_matrix, hstack
  from sklearn.base import BaseEstimator, TransformerMixin
  from autogluon.core.constants import BINARY, MULTICLASS, REGRESSION, SOFTCLASS
  from ..tabular_nn.utils.categorical_encoders import OneHotMergeRaresHandleUnknownEncoder
label_desc: Use image node_id 1 for calling a global function with example usage: convert_ag_metric_to_xgbm(ag_metric_name, problem_type) and returns: _ag_to_xgbm_metric_dict