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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def convert_batchnorm(node, **kwargs):
 """Map MXNet's BatchNorm operator attributes to onnx's BatchNormalization operator and return the created node. """

    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]