if (operation_name == std::string("_EagerConst")) {
        // Non-parallel tensors from _EagerConst/tf.constant are implicitly
        // broadcast, i.e. set as the input to each parallel operation. This
        // allows code like "tf.constant(1.)" or "tf.reduce_sum(..., axis=1)"
        // (where the value starts on the host), without allowing other implicit

unsigned char TF_GetXlaConstantFoldingDisabled() {
  return static_cast<unsigned char>(
      tensorflow::GetBuildXlaOpsPassFlags()->tf_xla_disable_constant_folding);
}

void TF_SetXlaConstantFoldingDisabled(unsigned char should_enable) {
  tensorflow::GetBuildXlaOpsPassFlags()->tf_xla_disable_constant_folding =
      static_cast<bool>(should_enable);
}

void TF_SetXlaMinClusterSize(int size) {

    feed2_ = Placeholder(graph_, s_, "feed2");
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

    constant_ = ScalarConst(10, graph_, s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

    desc_ = TF_NewOperation(graph_, "AddN", "add");
    TF_Output inputs[] = {{feed1_, 0}, {constant_, 0}};
    TF_AddInputList(desc_, inputs, TF_ARRAYSIZE(inputs));
  }

  ~CApiColocationTest() override {

  CONFIG_TOGGLE(implementation_selector);
  CONFIG_TOGGLE(function_optimization);
  CONFIG_TOGGLE(common_subgraph_elimination);
  CONFIG_TOGGLE(arithmetic_optimization);
  CONFIG_TOGGLE(debug_stripper);
  CONFIG_TOGGLE(constant_folding);
  CONFIG_TOGGLE(shape_optimization);
  CONFIG_TOGGLE(auto_mixed_precision);
  CONFIG_TOGGLE(auto_mixed_precision_onednn_bfloat16);
  CONFIG_TOGGLE(auto_mixed_precision_mkl);

  // Workaround for not being able to initialize empty map using {}
  std::unordered_set<string> empty_;
};

TEST_F(CApiFunctionTest, OneOp_ZeroInputs_OneOutput) {
  /*
   *                constant
   *                   |
   *                   v
   */
  // Define
  TF_Operation* c = ScalarConst(10, func_graph_, s_, "scalar10");
  Define(-1, {}, {}, {c}, {});

  // Use, run, and verify