code: def convert_batchnorm(node, **kwargs):
      
      name, input_nodes, attrs = get_inputs(node, kwargs)
  
      momentum = float(attrs.get("momentum", 0.9))
      eps = float(attrs.get("eps", 0.001))
  
      bn_node = onnx.helper.make_node(
          "BatchNormalization",
          input_nodes,
          [name],
          name=name,
          epsilon=eps,
          momentum=momentum,
          # MXNet computes mean and variance per feature for batchnorm
          # Default for onnx is across all spatial features. So disabling the parameter.
          spatial=0
      )
      return [bn_node]
docs: Map MXNet's BatchNorm operator attributes to onnx's BatchNormalization operator
      and return the created node.