code: def exp_sigmoid(
      input: np.ndarray,
      exponent: float = 10.0,
      max_value: float = 2.0,
      threshold: float = 1e-7,
  ) -> np.ndarray:
      """Exponential Sigmoid pointwise nonlinearity (Numpy version).
      Implements the equation:
      ``max_value`` * sigmoid(``input``) ** (log(``exponent``)) + ``threshold``
  
      The output has a range of [``threshold``, ``max_value``].
      ``exponent`` controls the slope of the output.
  
      Args:
          input (np.ndarray): Input array
          exponent (float, optional): Exponent. Controls the slope of the output
          max_value (float, optional): Maximum value of the output
          threshold (float, optional): Minimum value of the output
  
      Returns:
          np.ndarray: Exponential Sigmoid output. Shape: same as input
  
      """
      return (
          max_value
          * (1 / (1 + np.exp(-input, dtype=input.dtype)))
          ** np.log(exponent, dtype=input.dtype)
          + threshold
      )
  
imports: import numpy
label_desc: Use image node_id 4 for calling a global function with example usage: exp_sigmoid(input, exponent, max_value, threshold) and returns: unknown