code: def normalize_fvec(x_train):
      """normalize feature vectors"""
      feature_mean = np.mean(x_train, axis=0)
      feature_std = np.std(x_train, axis=0)
      x_train = (x_train - feature_mean) / feature_std
      return x_train
  
imports: import os
  import ssl
  import tarfile
  import urllib.request
  from my_logistic_regression import MyLogisticRegression
  import numpy
  import requests
  from sklearn import preprocessing
  import sklearn.datasets
  from sklearn.linear_model import LogisticRegression
  import torch
  from torchvision import datasets, transforms
label_desc: Use image node_id 1 for calling a global function with example usage: normalize_fvec(x_train) and returns: x_train