code: def get_feature_name(model: LudwigModel, target: str) -> str:
      t = target.lower()
      for c in model.training_set_metadata.keys():
          if c.lower() == t:
              return c
      raise ValueError(
          f"Unable to find target column {t} in {model.training_set_metadata.keys()}"
      )
  
file_path: ludwig/ludwig/explain/util.py
imports: from copy import deepcopy
  import pandas
  import torch
  from ludwig.api import LudwigModel
  from ludwig.constants import COLUMN, INPUT_FEATURES, PREPROCESSING, SPLIT
  from ludwig.data.split import get_splitter
  from ludwig.features.base_feature import BaseFeature
label_desc: Use image node_id 4 for calling a global function with example usage: get_feature_name(model, target) and returns: c