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 signed integer list with given constraints.
  
  Args:
    min_length: The minimum length of the list.
    max_length: The maximum length of the list.
    min_int: Minimum allowed integer.
    max_int: Maximum allowed integer.
  
  Returns:
    Consumed integer list based on input bytes and constraints.
docstr_tok: ["Consume","a","signed","integer","list","with","given","constraints",".","Args",":","min_length",":","The","minimum","length","of","the","list",".","max_length",":","The","maximum","length","of","the","list",".","min_int",":","Minimum","allowed","integer",".","max_int",":","Maximum","allowed","integer",".","Returns",":","Consumed","integer","list","based","on","input","bytes","and","constraints","."]
code: def get_int_list(
      self,
      min_length=_MIN_LENGTH,
      max_length=_MAX_LENGTH,
      min_int=_MIN_INT,
      max_int=_MAX_INT,
  ):
      """Consume a signed integer list with given constraints.
  
      Args:
        min_length: The minimum length of the list.
        max_length: The maximum length of the list.
        min_int: Minimum allowed integer.
        max_int: Maximum allowed integer.
  
      Returns:
        Consumed integer list based on input bytes and constraints.
      """
      length = self.get_int(min_length, max_length)
      return self.fdp.ConsumeIntListInRange(length, min_int, max_int)
  
file_path: tensorflow/tensorflow/security/fuzzing/python_fuzzing.py
imports: import atheris
  import tensorflow
label_desc: Use image node_id 5 for calling the FuzzingHelper obj's underlying member method code with example usage: obj.get_int_list(min_length, max_length, min_int, max_int) and returns: self