message: Use a non-trivial benchmark for kernel_tests/benchmark_test.py
  Otherwise XLA constant folds the computation resulting in
  allocator_maximum_num_bytes_* getting a value of 0.  At least that's what I
  think is happening, I have not dug beyond confirming that the failure goes away
  with this change.
diff: @@ -21,9 +21,12 @@ import json
  import os
  import random
  +import numpy as np
  +
  from tensorflow.core.util import test_log_pb2
  from tensorflow.python.client import session
  -from tensorflow.python.framework import constant_op
  +from tensorflow.python.framework import dtypes
  +from tensorflow.python.ops import array_ops
  from tensorflow.python.platform import benchmark
  from tensorflow.python.platform import gfile
  from tensorflow.python.platform import test
  @@ -64,11 +67,17 @@ class TestReportingBenchmark(test.Benchmark):
  "other_key": "string"})
  def benchmark_times_an_op(self):
  + input_size = 5
  with session.Session(config=benchmark.benchmark_config()) as sess:
  - a = constant_op.constant(0.0)
  + a = array_ops.placeholder(dtype=dtypes.float32, shape=(input_size))
  a_plus_a = a + a
  return self.run_op_benchmark(
  - sess, a_plus_a, min_iters=1000, store_trace=True, name="op_benchmark")
  + sess,
  + a_plus_a,
  + feed_dict={a: np.arange(input_size)},
  + min_iters=1000,
  + store_trace=True,
  + name="op_benchmark")
  class BenchmarkTest(test.TestCase):
  