"/job:localhost/replica:0/task:1/device:CPU:0";
  CheckRemoteMatMulExecutesOK(ctx, remote_device_name, local_device_name);

  // Adding a non-existent remote worker to cluster def. This should cause the
  // UpdateServerDef call to fail.
  tensorflow::ClusterDef* cluster_def = server_def.mutable_cluster();
  tensorflow::JobDef* job_def = cluster_def->mutable_job(0);
  int port = tensorflow::testing::PickUnusedPortOrDie();

  TF_EXPECT_OK(ReadCache(&cache, "", block_size, 1, &out));
  TF_EXPECT_OK(ReadCache(&cache, "", block_size, 1, &out));
  calls.push_back(2 * block_size);
  // Cache miss followed by cache hit.  Causes eviction of LRU element.
  TF_EXPECT_OK(ReadCache(&cache, "", 2 * block_size, 1, &out));
  TF_EXPECT_OK(ReadCache(&cache, "", 2 * block_size, 1, &out));
  // LRU element was at offset 0.  Cache miss.
  calls.push_back(0);

  EXPECT_TRUE(cache2.Lookup("b", &value));
  EXPECT_EQ(value, 2);
  EXPECT_TRUE(cache2.Lookup("c", &value));
  EXPECT_EQ(value, 3);
  EXPECT_TRUE(cache2.Lookup("d", &value));
  EXPECT_EQ(value, 4);
  // Insertion of "e" causes "a" to be evicted, but the other entries are still
  // there.
  cache2.Insert("e", 5);
  EXPECT_FALSE(cache2.Lookup("a", &value));
  EXPECT_TRUE(cache2.Lookup("b", &value));
  EXPECT_EQ(value, 2);

                        const int in_flight_nodes_limit)
      : status_(TF_NewStatus()),
        // If the context's default exector is set to async, re-using that in
        // each thread would cause collectives to deadlock. For consistency we
        // create a new sync executor for every thread.
        //
        // TODO(allenl): We should have an async API that works with the
        // parallel device.