code: def loss(self, y, p):
      # Avoid division by zero
      p = np.clip(p, 1e-15, 1 - 1e-15)
      return -y * np.log(p) - (1 - y) * np.log(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 2 for calling the CrossEntropy obj's underlying member method code with example usage: obj.loss(y, p) and returns: unknown