code: def benchmarkMatrixLogarithmOp(self):
      for shape in self.shapes:
          with ops.Graph().as_default(), session.Session(
              config=benchmark.benchmark_config()
          ) as sess, ops.device("/cpu:0"):
              matrix = self._GenerateMatrix(shape)
              logm = gen_linalg_ops.matrix_logarithm(matrix)
              self.evaluate(variables.global_variables_initializer())
              self.run_op_benchmark(
                  sess,
                  control_flow_ops.group(logm),
                  min_iters=25,
                  name="matrix_logarithm_cpu_{shape}".format(
                      shape=shape
                  ),
              )
  
imports: import numpy
  from tensorflow.python.client import session
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import gen_linalg_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import stateless_random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops.linalg import linalg_impl
  from tensorflow.python.platform import benchmark
  from tensorflow.python.platform import test
label_desc: Use image node_id 2 for calling the MatrixLogarithmBenchmark obj's underlying member method code with example usage: obj.benchmarkMatrixLogarithmOp() without return types