class_docstr: FuzzingHelper makes handling FuzzedDataProvider easier with TensorFlow Python fuzzing.
class_docstr_tok: ["FuzzingHelper","makes","handling","FuzzedDataProvider","easier","with","TensorFlow","Python","fuzzing","."]
docstr: Consume a float with given constraints.
  
  Args:
    min_float: Minimum allowed float.
    max_float: Maximum allowed float.
  
  Returns:
    Consumed float based on input bytes and constraints.
docstr_tok: ["Consume","a","float","with","given","constraints",".","Args",":","min_float",":","Minimum","allowed","float",".","max_float",":","Maximum","allowed","float",".","Returns",":","Consumed","float","based","on","input","bytes","and","constraints","."]
code: def get_float(self, min_float=_MIN_FLOAT, max_float=_MAX_FLOAT):
      """Consume a float with given constraints.
  
      Args:
        min_float: Minimum allowed float.
        max_float: Maximum allowed float.
  
      Returns:
        Consumed float based on input bytes and constraints.
      """
      return self.fdp.ConsumeFloatInRange(min_float, max_float)
  
file_path: tensorflow/tensorflow/security/fuzzing/python_fuzzing.py
imports: import atheris
  import tensorflow
label_desc: Use image node_id 4 for calling the FuzzingHelper obj's underlying member method code with example usage: obj.get_float(min_float, max_float) and returns: self