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 fit(self, *args):
      ModelFirstOrder.fit(self, *args)
      self._set(N_CALLS_HESSIAN_NORM, 0)
      return self
  
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 2 for calling the ModelSecondOrder obj's underlying member method code with example usage: obj.fit() and returns: self