code: def scale_by_instance(
      x: np.ndarray, eps: float = 1e-12
  ) -> np.ndarray:
      xmean = x.mean(axis=(1, 2, 3)).reshape(-1, 1, 1, 1)
      xstd = x.std(axis=(1, 2, 3)).reshape(-1, 1, 1, 1)
      x_scaled = (x - xmean) / (xstd + eps)
      return x_scaled
  
imports: import argparse
  import numpy
  import os
  from pathlib import Path
  import tensorflow
  from tensorflow.keras.callbacks import Callback, ModelCheckpoint
  from tensorflow.keras.initializers import RandomNormal
  from tensorflow.keras.layers import Activation, Add, BatchNormalization, Conv2D, Dense, Input, ZeroPadding2D
  from tensorflow.keras.models import Model
  from tensorflow.keras.optimizers import SGD
  from tensorflow.keras.preprocessing.image import ImageDataGenerator
  from tensorflow.keras.regularizers import l2
  from typing import Callable, Tuple, Union
label_desc: Use image node_id 8 for calling a global function with example usage: scale_by_instance(x, eps) and returns: x_scaled