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 list with given constraints.
  
  Args:
    min_length: The minimum length of the list.
    max_length: The maximum length of the list.
  
  Returns:
    Consumed integer list based on input bytes and constraints.
docstr_tok: ["Consume","a","float","list","with","given","constraints",".","Args",":","min_length",":","The","minimum","length","of","the","list",".","max_length",":","The","maximum","length","of","the","list",".","Returns",":","Consumed","integer","list","based","on","input","bytes","and","constraints","."]
code: def get_float_list(
      self, min_length=_MIN_LENGTH, max_length=_MAX_LENGTH
  ):
      """Consume a float list with given constraints.
  
      Args:
        min_length: The minimum length of the list.
        max_length: The maximum length of the list.
  
      Returns:
        Consumed integer list based on input bytes and constraints.
      """
      length = self.get_int(min_length, max_length)
      return self.fdp.ConsumeFloatListInRange(
          length, _MIN_FLOAT, _MAX_FLOAT
      )
  
file_path: tensorflow/tensorflow/security/fuzzing/python_fuzzing.py
imports: import atheris
  import tensorflow
label_desc: Use image node_id 6 for calling the FuzzingHelper obj's underlying member method code with example usage: obj.get_float_list(min_length, max_length) and returns: self