docstr: Convert ONNX _initializer to Zoo format
  :return: list of ndarray
docstr_tok: ["Convert","ONNX","_initializer","to","Zoo","format",":","return",":","list","of","ndarray"]
code: def to_zoo_format(self, trainable_values):
      """
      Convert ONNX _initializer to Zoo format
      :return: list of ndarray
      """
      return trainable_values
  
file_path: analytics-zoo/pyzoo/zoo/pipeline/api/onnx/mapper/batchnormalization.py
imports: from zoo.pipeline.api.onnx.mapper.operator_mapper import OperatorMapper
  from zoo.pipeline.api.onnx.onnx_helper import OnnxHelper
  import zoo.pipeline.api.keras.layers
  import zoo.pipeline.api.autograd
  import numpy
label_desc: Use image node_id 4 for calling the BatchNormalizationMapper obj's underlying member method code with example usage: obj.to_zoo_format(trainable_values) and returns: trainable_values