auto w = ops::Placeholder(scope.WithOpName("W"), DT_RESOURCE);

  NameAttrList function;
  function.set_name("launch0");
  auto launch = ops::XlaLaunch(
      scope.WithOpName("launch0").WithDevice("/gpu:0"),
      std::initializer_list<Input>{}, std::initializer_list<Input>{a, b, c, d},
      std::initializer_list<Input>{u, v, w},
      DataTypeVector{DT_FLOAT, DT_INT32, DT_FLOAT, DT_FLOAT}, function);

  return Scope(new Impl(*this, Impl::Tags::ControlDeps(),
                        std::vector<Operation>(),
                        /* clear_control_deps */ true));
}

Scope Scope::WithDevice(const string& device) const {
  return Scope(new Impl(*this, Impl::Tags::Device(), device));
}

Scope Scope::WithAssignedDevice(const string& assigned_device) const {

  }
  std::sort(edges.begin(), edges.end());
  return edges;
}

TEST(EncapsulateSubgraphsTest, InputDeduplication) {
  Scope root = Scope::NewRootScope().ExitOnError().WithDevice(
      "/job:localhost/replica:0/task:0/cpu:0");
  auto x = ops::Placeholder(root.WithOpName("x"), DT_FLOAT);
  auto add1 = ops::Add(root.WithOpName("add1"), x, x);
  add1.node()->AddAttr("_cluster", "cluster1");

  // [[[105, 192], [105, 192], [105, 192]], [[0, 180], [0, 180], [0, 180]]]
  auto grad_tiled = Tile(scope, grad, tile_scaling);

  Scope cpu_scope = scope.WithDevice("/cpu:0");

  // [3]
  auto rank = Rank(cpu_scope, op.input(0));

  // Normalize any negative indices in the reduction_axes to positive values.
  auto reduction_indices_pos =