code: def gradient(self, y, p):
      # Avoid division by zero
      p = np.clip(p, 1e-15, 1 - 1e-15)
      return -(y / p) + (1 - y) / (1 - p)
  
file_path: ML-From-Scratch/mlfromscratch/deep_learning/loss_functions.py
imports: from __future__ import division
  import numpy
  from mlfromscratch.utils import accuracy_score
  from mlfromscratch.deep_learning.activation_functions import Sigmoid
label_desc: Use image node_id 4 for calling the CrossEntropy obj's underlying member method code with example usage: obj.gradient(y, p) and returns: unknown