code: def _to_tensor(self):
      data = self.model_inputs[0].zvalue
      alpha = (
          float(self.onnx_attr["alpha"])
          if "alpha" in self.onnx_attr
          else 0.0001
      )
      beta = (
          float(self.onnx_attr["beta"])
          if "beta" in self.onnx_attr
          else 0.75
      )
      bias = (
          float(self.onnx_attr["bias"])
          if "bias" in self.onnx_attr
          else 1.0
      )
      size = int(self.onnx_attr["size"])
      dim_ordering = "th"
  
      return zlayers.LRN2D(
          alpha=alpha,
          k=bias,
          beta=beta,
          n=size,
          dim_ordering=dim_ordering,
      )(data)
  
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
label_desc: Use image node_id 2 for calling the LRNMapper obj's underlying member method code with example usage: obj._to_tensor() and returns: zlayers