code: def get_scaler(scaler_name):
      if scaler_name is None:
          return None
      if scaler_name == "standard":
          return preprocessing.StandardScaler()
      if scaler_name == "minmax":
          return preprocessing.MinMaxScaler()
      if scaler_name == "robust":
          return preprocessing.RobustScaler()
      if scaler_name == "normal":
          return preprocessing.Normalizer()
      raise ValueError("Invalid scaler")
  
imports: import copy
  from collections import defaultdict
  from dataclasses import dataclass
  from functools import partial
  from typing import List, Optional
  import numpy
  from sklearn import ensemble, impute, linear_model
  from sklearn import metrics
  from sklearn import naive_bayes, neighbors, pipeline, preprocessing, svm, tree
  from xgboost import XGBClassifier, XGBRegressor
label_desc: Use image node_id 3 for calling a global function with example usage: get_scaler(scaler_name) and returns: None, preprocessing, preprocessing, preprocessing, preprocessing