* allocations in many common cases.
 *
 * <p>The message string is not formatted unless the exception will be thrown, so the cost of the
 * string formatting itself should not be a concern.
 *
 * <p>As with any performance concerns, you should consider profiling your code (in a production
 * environment if possible) before spending a lot of effort on tweaking a particular element.
 *

    internal var connectTimeout = 10_000
    internal var readTimeout = 10_000
    internal var writeTimeout = 10_000
    internal var pingInterval = 0
    internal var webSocketCloseTimeout = RealWebSocket.CANCEL_AFTER_CLOSE_MILLIS.toInt()
    internal var minWebSocketMessageToCompress = RealWebSocket.DEFAULT_MINIMUM_DEFLATE_SIZE
    internal var routeDatabase: RouteDatabase? = null
    internal var taskRunner: TaskRunner? = null

  TFE_TensorHandle* input1 = TestMatrixTensorHandle(ctx);
  TFE_TensorHandle* input2 = TestMatrixTensorHandle(ctx);
  TFE_TensorHandle* dim = TestScalarTensorHandle(ctx, 0);
  TFE_Op* concatOp = TFE_NewOp(ctx, "Concat", status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_TensorHandle* inputs[] = {input1, input2};
  TFE_OpAddInput(concatOp, dim, status);

TEST(CAPI, Status) {
  TF_Status* s = TF_NewStatus();
  EXPECT_EQ(TF_OK, TF_GetCode(s));
  EXPECT_EQ(string(), TF_Message(s));
  TF_SetStatus(s, TF_CANCELLED, "cancel");
  EXPECT_EQ(TF_CANCELLED, TF_GetCode(s));
  EXPECT_EQ(string("cancel"), TF_Message(s));
  TF_DeleteStatus(s);
}

void Deallocator(void* data, size_t, void* arg) {
  tensorflow::cpu_allocator()->DeallocateRaw(data);