TEST(CAPI, MessageBufferConversion) {
  NodeDef node_in, node_out;
  node_in.set_name("Test name");
  node_in.set_op("Test op");

  TF_Buffer* buffer = TF_NewBuffer();
  TF_CHECK_OK(MessageToBuffer(node_in, buffer));
  TF_CHECK_OK(BufferToMessage(buffer, &node_out));
  TF_DeleteBuffer(buffer);

  protobuf::util::MessageDifferencer differencer;
  EXPECT_TRUE(differencer.Compare(node_in, node_out));
}

      // Fill graph_def with nodes with ids in the range
      // [session->last_num_graph_nodes, num_nodes), that is the nodes
      // added since the last TF_SessionRun() call.
      for (auto id = session->last_num_graph_nodes; id < num_nodes; ++id) {
        Node* const node = graph.FindNodeId(id);
        if (node != nullptr && node->IsOp()) {
          NodeDef* const node_def = graph_def.add_node();

// 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.

*   `tf.saved_model.SaveOptions`

    * `SaveOptions` now takes a new argument called
      `experimental_debug_stripper`. When enabled, this strips the debug nodes
      from both the node defs and the function defs of the graph. Note that
      this currently only strips the `Assert` nodes from the graph and
      converts them into `NoOp`s instead.

*   `tf.data`

    * `tf.data` now has an `autotune_options.initial_parallelism` option to

  status->status = absl::OkStatus();
}

TFE_Executor* TFE_NewExecutor(bool is_async, bool enable_streaming_enqueue,
                              int in_flight_nodes_limit) {
  return new TFE_Executor(is_async, enable_streaming_enqueue,
                          in_flight_nodes_limit);
}

void TFE_DeleteExecutor(TFE_Executor* executor) { delete executor; }

bool TFE_ExecutorIsAsync(TFE_Executor* executor) {

        "//smartass/brain/configure/...",
        "//tensorflow/...",
        "//tensorflow_decision_forests/...",
        "//tensorflow_federated/...",
        "//tensorflow_models/google/recml/...",
        "//third_party/cloud_tpu/convergence_tools/sdc_monitoring/...",
        "//third_party/cloud_tpu/inference_converter/...",
        "//third_party/py/cloud_ml_autoflow/...",

#include "tensorflow/core/platform/platform.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/profiler/lib/traceme.h"
#include "tensorflow/core/protobuf/error_codes.pb.h"
#include "tensorflow/core/public/version.h"

#if !defined(IS_MOBILE_PLATFORM)
#include "tensorflow/core/common_runtime/eager/context_distributed_manager.h"
#endif  // !IS_MOBILE_PLATFORM

using tensorflow::string;

namespace {

    }
  }

  // Compute body nodes.
  std::vector<const Node*> body_nodes;
  status->status = tensorflow::ComputeBodyNodes(
      fn_body, fn_name, num_opers, opers, input_nodes, &body_nodes);
  if (TF_GetCode(status) != TF_OK) return nullptr;

  // Compute body nodes.
  std::vector<const Node*> control_output_nodes;
  control_output_nodes.reserve(ncontrol_outputs);