class_docstr: Class for extracting floats from a string.
  
  For example:
  
  >>> text_parts, floats = _FloatExtractor()("Text 1.0 Text")
  >>> text_parts
  ["Text ", " Text"]
  >>> floats
  np.array([1.0])
class_docstr_tok: ["Class","for","extracting","floats","from","a","string",".","For","example",":",">",">",">","text_parts",",","floats","=","_FloatExtractor","(",")","(","``","Text","1.0","Text","''",")",">",">",">","text_parts","[","``","Text","``",",","``","Text","''","]",">",">",">","floats","np.array","(","[","1.0","]",")"]
docstr: Extracts floats from a string.
  
  >>> text_parts, floats = _FloatExtractor()("Text 1.0 Text")
  >>> text_parts
  ["Text ", " Text"]
  >>> floats
  np.array([1.0])
  
  Args:
    string: the string to extract floats from.
  
  Returns:
    A (string, array) pair, where `string` has each float replaced by "..."
    and `array` is a `float32` `numpy.array` containing the extracted floats.
docstr_tok: ["Extracts","floats","from","a","string",".",">",">",">","text_parts",",","floats","=","_FloatExtractor","(",")","(","``","Text","1.0","Text","''",")",">",">",">","text_parts","[","``","Text","``",",","``","Text","''","]",">",">",">","floats","np.array","(","[","1.0","]",")","Args",":","string",":","the","string","to","extract","floats","from",".","Returns",":","A","(","string",",","array",")","pair",",","where","`","string","`","has","each","float","replaced","by","``","...","''","and","`","array","`","is","a","`","float32","`","`","numpy.array","`","containing","the","extracted","floats","."]
code: def __call__(self, string):
      """Extracts floats from a string.
  
      >>> text_parts, floats = _FloatExtractor()("Text 1.0 Text")
      >>> text_parts
      ["Text ", " Text"]
      >>> floats
      np.array([1.0])
  
      Args:
        string: the string to extract floats from.
  
      Returns:
        A (string, array) pair, where `string` has each float replaced by "..."
        and `array` is a `float32` `numpy.array` containing the extracted floats.
      """
      texts = []
      floats = []
      for i, part in enumerate(self._FLOAT_RE.split(string)):
          if i % 2 == 0:
              texts.append(part)
          else:
              floats.append(float(part))
  
      return texts, np.array(floats)
  
file_path: tensorflow/tensorflow/tools/docs/tf_doctest_lib.py
imports: import doctest
  import re
  import textwrap
  import numpy
label_desc: Use image node_id 1 for calling the _FloatExtractor obj's underlying member method code with example usage: obj.__call__(string) and returns: texts,  np