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 with given constraints.
  
  Args:
    min_int: Minimum allowed integer.
    max_int: Maximum allowed integer.
  
  Returns:
    Consumed integer based on input bytes and constraints.
docstr_tok: ["Consume","a","signed","integer","with","given","constraints",".","Args",":","min_int",":","Minimum","allowed","integer",".","max_int",":","Maximum","allowed","integer",".","Returns",":","Consumed","integer","based","on","input","bytes","and","constraints","."]
code: def get_int(self, min_int=_MIN_INT, max_int=_MAX_INT):
      """Consume a signed integer with given constraints.
  
      Args:
        min_int: Minimum allowed integer.
        max_int: Maximum allowed integer.
  
      Returns:
        Consumed integer based on input bytes and constraints.
      """
      return self.fdp.ConsumeIntInRange(min_int, max_int)
  
file_path: tensorflow-upstream/tensorflow/security/fuzzing/python_fuzzing.py
imports: import atheris
  import tensorflow
label_desc: Use image node_id 3 for calling the FuzzingHelper obj's underlying member method code with example usage: obj.get_int(min_int, max_int) and returns: self