code: def __call__(self, x):
      # mean across the axis
      u = np.mean(x, axis=self.axis, keepdims=True)
      # standard deviation
      s = np.mean((x - u) ** 2, axis=self.axis, keepdims=True)
      # rescaled values
      x = (x - u) * objax.functional.rsqrt(s + self.epsilon)
      x = x * self.g.value + self.b.value
      return x
  
imports: import json
  import os
  import sys
  import jax.numpy
  import numpy
  import objax
  from objax.variable import TrainVar
label_desc: Use image node_id 2 for calling the Norm obj's underlying member method code with example usage: obj.__call__(x) and returns: x