ASSERT_EQ(1, TF_OperationNumInputs(neg));
  TF_Output neg_input = TF_OperationInput({neg, 0});
  EXPECT_EQ(scalar, neg_input.oper);
  EXPECT_EQ(0, neg_input.index);

  // Test that we can't see control edges involving the source and sink nodes.
  TF_Operation* control_ops[100];
  EXPECT_EQ(0, TF_OperationNumControlInputs(scalar));
  EXPECT_EQ(0, TF_OperationGetControlInputs(scalar, control_ops, 100));

    TFE_DeleteContextOptions(opts);
    TFE_Executor* executor = TFE_NewExecutor(
        /*is_async=*/false, /*enable_streaming_enqueue=*/true,
        /*in_flight_nodes_limit=*/0);
    TFE_ContextSetExecutorForThread(ctx, executor);

    TFE_DeleteContext(ctx);
    TFE_DeleteExecutor(executor);
  }

  {
    TFE_ContextOptions* opts = TFE_NewContextOptions();

    tensorflow::ConfigProto config;
    // Do not skip grappler optimization even for small graphs.
    config.mutable_graph_options()
        ->mutable_rewrite_options()
        ->set_min_graph_nodes(-1);
    string serialized_config;
    ASSERT_TRUE(config.SerializeToString(&serialized_config));
    TFE_OpSetAttrString(
        op, "config_proto",
        reinterpret_cast<const void*>(serialized_config.c_str()),

  }

  // Populate return_nodes
  DCHECK(tf_results->return_nodes.empty());
  tf_results->return_nodes.resize(results.return_nodes.size());
  for (int i = 0; i < results.return_nodes.size(); ++i) {
    tf_results->return_nodes[i] = ToOperation(results.return_nodes[i]);
  }

  // Populate missing unused map keys

  TF_SetStatus(status, TF_OK, "");
  const std::unordered_set<std::string>& nodes =
      reinterpret_cast<const tensorflow::grappler::GrapplerItem*>(item)
          ->NodesToPreserve();
  *num_values = nodes.size();
  *storage_size = 0;
  for (const std::string& str : nodes) {
    *storage_size += str.size();
  }
}

// Creates a new eager Executor. Nodes in one executor are guaranteed to be
// executed in sequence. Assigning nodes to different executors allows executing
// nodes in parallel.
// in_flight_nodes_limit: when is_async is true, this value controls the
// maximum number of in flight async nodes. Enqueuing of additional async ops
// after the limit is reached blocks until some inflight nodes finishes.

        "//tensorflow/core/grappler/costs:graph_properties",
        "//tensorflow/core/grappler/inputs:trivial_test_graph_input_yielder",
        "//tensorflow/core/protobuf:error_codes_proto_impl_cc",
    ],

Goodman, Dave Decker, David Dao, David Kretch, Dongjoon Hyun, Dustin Dorroh,
@e-lin, Eurico Doirado, Erik Erwitt, Fabrizio Milo, @gaohuazuo, Iblis Lin, Igor
Babuschkin, Isaac Hodes, Isaac Turner, Iván Vallés, J Yegerlehner, Jack Zhang,
James Wexler, Jan Zikes, Jay Young, Jeff Hodges, @jmtatsch, Johnny Lim, Jonas
Meinertz Hansen, Kanit Wongsuphasawat, Kashif Rasul, Ken Shirriff, Kenneth

          return tensorflow::errors::InvalidArgument(
              "Unsupported Complex bits: ", dtype.bits);
      }
      break;
    default:
      return tensorflow::errors::InvalidArgument("Unsupported Type Codes: ",
                                                 dtype.code);
  }
}

// Wraps the deleter function of DLManagedTensor to match the function signature
// TFE_NewTensorHandleFromDeviceMemory.

      const tensorflow::FunctionDef& fdef,
      const std::vector<EdgeSpec>& e_edges,  // expected edges
      const std::vector<EdgeSpec>& c_edges,  // expected ctrl edges
      bool is_exact_edges = true) {
    // Build a set of edges from fdef
    std::set<EdgeSpec> a_edges;  // actual edges
    // Get edges from inputs to body nodes and between body nodes
    for (const NodeDef& node_def : fdef.node_def()) {