virtual bool UsesTFRT() = 0;

  // List attributes of available devices
  virtual void ListDevices(std::vector<DeviceAttributes>* devices) = 0;

  // Add `devices` into context's device manager. Context's device manager
  // will take ownership and maintain devices' lifetime.
  virtual Status AddDevices(std::vector<std::unique_ptr<Device>> devices) = 0;

  // Block until all pending nodes are finished.

limitations under the License.
==============================================================================*/

#include <memory>
#include <utility>
#include <vector>

#include "absl/strings/str_cat.h"
#include "tensorflow/c/c_api.h"
#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/eager/c_api_internal.h"

    absl::flat_hash_set<int> null_indices;
    {
      AbstractContextPtr func_ctx(BuildFunction(fn_name));
      std::vector<AbstractTensorHandle*> func_inputs;
      func_inputs.reserve(inputs.size());
      TF_RETURN_IF_ERROR(
          CreateParamsForInputs(func_ctx.get(), inputs, &func_inputs));
      std::vector<AbstractTensorHandle*> model_outputs;
      model_outputs.resize(outputs.size());

  }

  // Checks the expected result of shape inference for the given `op`.
  void CheckOutputShapes(
      TFE_Op* op,
      const std::vector<absl::optional<std::vector<int64_t>>>& input_shapes_vec,
      const std::vector<TF_Tensor*>& input_tensors,
      const absl::optional<std::vector<int64_t>>& expected_shape) {
    // Create input_shapes.
    TF_ShapeAndTypeList* input_shapes =

        "//tensorflow/core:protos_all_cc",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",
        "//tensorflow/core/kernels:ops_testutil",
        "@com_google_absl//absl/container:inlined_vector",
        "@com_google_absl//absl/strings:str_format",
        "@eigen_archive//:eigen3",
    ],
)

tf_cc_test(
    name = "ops_test",
    size = "medium",
    srcs = ["ops_test.cc"],

// gradient registerer to instantiate a GradientFunction.
struct ForwardOperation {
 public:
  string op_name;
  std::vector<AbstractTensorHandle*> inputs;
  std::vector<AbstractTensorHandle*> outputs;
  std::vector<int64_t> skip_input_indices;
  AttrBuilder attrs;
};

using GradientFunctionFactory =
    std::function<GradientFunction*(const ForwardOperation& op)>;

==============================================================================*/

#include "tensorflow/c/eager/c_api_experimental.h"

#include <cstdint>
#include <memory>
#include <utility>
#include <vector>

#include "absl/container/flat_hash_map.h"
#include "absl/strings/match.h"
#include "absl/time/time.h"
#include "tensorflow/c/c_api.h"
#include "tensorflow/c/eager/c_api_internal.h"

  job_def->mutable_tasks()->at(task_index) =
      tensorflow::strings::StrCat(host, ":", port);
}

std::vector<std::string> ListDeviceNames(TFE_Context* ctx) {
  TF_Status* status = TF_NewStatus();
  std::vector<std::string> device_names;
  TF_DeviceList* devices = TFE_ContextListDevices(ctx, status);
  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

    return false;
  }
  return true;
}

static std::vector<std::string> GetChildrenBounded(
    GCSFile* gcs_file, std::string dir, uint64_t max_results, bool recursive,
    bool include_self_directory_marker, TF_Status* status) {
  std::string bucket, prefix;
  MaybeAppendSlash(&dir);
  ParseGCSPath(dir, true, &bucket, &prefix, status);

  std::vector<std::string> result;
  uint64_t count = 0;

    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        "//tensorflow/core:lib",
        "//tensorflow/core:protos_all_cc",
        "@com_google_absl//absl/container:inlined_vector",
    ],
)

cc_library(
    name = "abstract_operation",
    hdrs = ["abstract_operation.h"],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [