code: def _apply_on_cols(self) -> List[Callable]:
      input_col = self.input_col
  
      return [
          f.mean(f.col(input_col)).alias(
              StandardScalarScalerConfig.mean_token
          ),
          f.stddev_pop(f.col(input_col)).alias(
              StandardScalarScalerConfig.std_token
          ),
      ]
  
imports: from abc import ABC, abstractmethod
  from typing import Callable, Dict, List, Optional, Union
  from synapse.ml.cyber.utils.spark_utils import ExplainBuilder, HasSetInputCol, HasSetOutputCol
  from pyspark.ml import Estimator, Transformer
  from pyspark.ml.param.shared import HasInputCol, HasOutputCol, Param, Params
  from pyspark.sql import DataFrame, functions, types
label_desc: Use image node_id 2 for calling the StandardScalarScaler obj's underlying member method code with example usage: obj._apply_on_cols() and returns: list