code: def convert_LogSumExp(
      func, opset_version, input_names, output_names, context
  ):
      # Use keepdims=False by default
      # since the chainer does not support keepdims option
      kwargs = {"keepdims": False}
      if hasattr(func, "keepdims"):
          kwargs["keepdims"] = func.keepdims
      if func.axis is not None:
          kwargs["axes"] = func.axis
      return (
          onnx_helper.make_node(
              "ReduceLogSumExp", input_names, output_names, **kwargs
          ),
      )
  
imports: import numpy
  from onnx.mapping import NP_TYPE_TO_TENSOR_TYPE
  from onnx_chainer.functions.opset_version import support
  from onnx_chainer import onnx_helper
label_desc: Use image node_id 30 for calling a global function with example usage: convert_LogSumExp(func, opset_version, input_names, output_names, context) and returns: onnx_helper