code: def _run(self, data, axes=None, keepdims=None):  # type: ignore
      tax = tuple(axes) if axes is not None else None
  
      if data.size == 0:
          return self.reduce_constant(data, -np.inf, tax, keepdims)
      return compute_log_sum_exp(data, tax, keepdims)
  
file_path: onnx/onnx/reference/ops/op_reduce_log_sum_exp.py
imports: import numpy
  from onnx.reference.ops._op import OpRunReduceNumpy
label_desc: Use image node_id 1 for calling the ReduceLogSumExp_1 obj's underlying member method code with example usage: obj._run(data, axes, keepdims) and returns: compute_log_sum_exp, self