code: def dfp(inv_H, delta_w, delta_grad, epsilon=1e-7):
      """
      DFP is a method very similar to BFGS. It's rank 2 formula update.
      It can suffer from round-off error and inaccurate line searches.
      """
      inv_H_dot_grad = dot(inv_H, delta_grad)
  
      x = safe_division(
          outer(delta_w, delta_w), dot(delta_grad, delta_w), epsilon
      )
      y = safe_division(
          tf.matmul(outer(inv_H_dot_grad, delta_grad), inv_H),
          dot(delta_grad, inv_H_dot_grad),
          epsilon,
      )
  
      return inv_H - y + x
  
file_path: neupy/neupy/algorithms/gd/quasi_newton.py
imports: import tensorflow
  from neupy.core.config import Configurable
  from neupy.core.properties import ChoiceProperty, NumberProperty, WithdrawProperty, IntProperty
  from neupy.utils.tf_utils import setup_parameter_updates
  from neupy.algorithms.minsearch.wolfe import line_search
  from neupy.utils import asfloat, dot, outer, as_tuple, function_name_scope, make_single_vector
  from .base import BaseOptimizer
label_desc: Use image node_id 4 for calling a global function with example usage: dfp(inv_H, delta_w, delta_grad, epsilon) and returns: unknown