class_docstr: An abstract class for models that implement a model with first
  order and second information, namely gradient and hessian norm
  information
  
  Attributes
  ----------
  n_calls_hessian_norm : `int` (read-only)
      Number of times ``hessian_norm`` has been called so far
  
  dtype : `{'float64', 'float32'}`, default='float64'
      Type of the data arrays used.
  
  Notes
  -----
  This class should be not used by end-users, it is intended for
  development only.
code: def __init__(self):
      ModelFirstOrder.__init__(self)
      setattr(self, N_CALLS_HESSIAN_NORM, 0)
  
file_path: tick/tick/base_model/model_second_order.py
imports: from abc import abstractmethod
  import numpy
  from .None import ModelFirstOrder
  from .model import PASS_OVER_DATA, HESSIAN_NORM, N_CALLS_HESSIAN_NORM
label_desc: Use image node_id 1 to create a new ModelSecondOrder object from inherited base classes: ModelFirstOrder with example: obj = ModelSecondOrder()