code: def safe_float(
      text: Any,
      replace_dict: Optional[Dict[str, List[str]]] = None,
      logger: Optional[logging.Logger] = None,
  ) -> Union[float, int, str]:
      """
      Convert string to a float.
  
      It first tries to convert to an integer and then to a float if that fails.
      If neither is possible, the originals string value is returned.
  
      Parameters
      ----------
      text : Any
          The text to convert.
  
      replace_dict : Optional[Dict[str, List[str]]], default=None
          Mapping from text to replacement text values. This is
          mainly used for collapsing multiple labels into a
          single class. Replacing happens before conversion to
          floats. Anything not in the mapping will be kept the
          same.
  
      logger : Optional[logging.Logger], default=None
          The Logger instance to use to log messages. Used instead of
          creating a new Logger instance by default.
  
      Returns
      -------
      Union[float, int, str]
          The text value converted to int or float, if possible. Otherwise
          it's a string.
      """
      # convert to str to be "Safe"!
      text = str(text)
  
      # get a logger unless we are passed one
      if not logger:
          logger = logging.getLogger(__name__)
  
      if replace_dict is not None:
          if text in replace_dict:
              text = replace_dict[text]
          else:
              logger.warning(
                  "Encountered value that was not in replacement "
                  f"dictionary (e.g., class_map): {text}"
              )
      try:
          return int(text)
      except ValueError:
          try:
              return float(text)
          except ValueError:
              return text
          except TypeError:
              return 0.0
      except TypeError:
          return 0
  
imports: import csv
  import json
  import logging
  import re
  import sys
  from io import StringIO
  from itertools import chain
  from numbers import Number
  from pathlib import Path
  from typing import IO, Any, Dict, List, Optional, Tuple, Union
  import numpy
  import pandas
  from bs4 import UnicodeDammit
  from sklearn.feature_extraction import FeatureHasher
  from skll.data import FeatureSet
  from skll.data.dict_vectorizer import DictVectorizer
  from skll.types import ClassMap, FeatGenerator, FeatureDictList, IdType, LabelType, PathOrStr
label_desc: Use image node_id 1 for calling a global function with example usage: safe_float(text, replace_dict, logger) and returns: int, int, float, text, int