docstr: 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
      """
  
      # The format of weight in BigDL is : input * output, so we need to transpose the y here.
      # There's no exception if you don't transpose it
      # as the `set_weights` method doesn't check the shape and respect the total items only.
      return [np.transpose(trainable_values[0]), trainable_values[1]]
  
file_path: analytics-zoo/pyzoo/zoo/pipeline/api/onnx/mapper/gemm.py
imports: import numpy
  import zoo.pipeline.api.keras.layers
  from zoo.pipeline.api.onnx.mapper.operator_mapper import OperatorMapper
label_desc: Use image node_id 4 for calling the GemmMapper obj's underlying member method code with example usage: obj.to_zoo_format(trainable_values) and returns: list