protected:
  ShapeInferenceTest()
      : status_(TF_NewStatus()), tfe_context_options_(TFE_NewContextOptions()) {
    tfe_context_ = TFE_NewContext(tfe_context_options_, status_);
    CHECK_EQ(TF_OK, TF_GetCode(status_)) << TF_Message(status_);
  }

  ~ShapeInferenceTest() override {
    TFE_DeleteContextOptions(tfe_context_options_);
    TFE_DeleteContext(tfe_context_);
    TF_DeleteStatus(status_);
  }

        pruning_thread_(nullptr,
                        [](TF_Thread* thread) { TF_JoinThread(thread); }) {
    if (max_staleness_ > 0) {
      TF_ThreadOptions thread_options;
      TF_DefaultThreadOptions(&thread_options);
      pruning_thread_.reset(
          TF_StartThread(&thread_options, "TF_prune_FBC", PruneThread, this));
    }
    TF_VLog(1, "GCS file block cache is %s.\n",
            (IsCacheEnabled() ? "enabled" : "disabled"));
  }

        and `tf.data.Dataset.range`.
    *   Promote `tf.data.Options.experimental_deterministic` API to
        `tf.data.Options.deterministic` and deprecate the experimental endpoint.
    *   Move autotuning options
        from`tf.data.Options.experimental_optimization.autotune*` to a newly
        created `tf.data.Options.autotune.*` and remove support for
        `tf.data.Options.experimental_optimization.autotune_buffers`.

  if (prefix == nullptr || strlen(prefix) == 0)
    prefix = "/job:localhost/replica:0/task:0";

  tensorflow::SessionOptions sess_options;
  (*sess_options.config.mutable_device_count())["CPU"] = num_cpus;
  status->status =
      tensorflow::DeviceFactory::AddCpuDevices(sess_options, prefix, &devices);

  // Remove the device that has the host device name since host device is alreay
  // in an initialized context.

# under the root of srcjars jars created by bazel, rather than under
# the maven-style src/main/java subdirectory.
#
# Bazel manages annotation generated source as follows: First, it
# calls javac with options that create generated files under a
# bazel-out directory. Next, it archives the generated source files
# into a srcjar directly under the root. There doesn't appear to be a

        "//tensorflow/compiler/mlir/tensorflow:error_util",
        "//tensorflow/compiler/mlir/tensorflow:export_graphdef",
        "//tensorflow/compiler/mlir/tensorflow:mlir_import_options",
        "//tensorflow/compiler/mlir/tensorflow:mlir_roundtrip_flags",
        "//tensorflow/compiler/mlir/tensorflow:translate_lib",
        "@local_xla//xla/service:computation_placer",
        "//tensorflow/core",

# This file tries to group and simplify build options for TensorFlow
#
# ----CONFIG OPTIONS----
# Android options:
#    android:
#    android_arm:
#    android_arm64:
#    android_x86:
#    android_x86_64:
#
# iOS options:
#     ios:
#     ios_armv7:
#     ios_arm64:
#     ios_x86_64:
#     ios_fat:
#
# Macosx options
#     darwin_arm64:
#
# Compiler options:

  return static_cast<TF_Operation*>(static_cast<void*>(node));
}

void TF_EnableXLACompilation(TF_SessionOptions* options, unsigned char enable) {
  tensorflow::ConfigProto& config = options->options.config;
  auto* optimizer_options =
      config.mutable_graph_options()->mutable_optimizer_options();
  if (enable) {
    optimizer_options->set_global_jit_level(tensorflow::OptimizerOptions::ON_1);

using tensorflow::unwrap;
using tensorflow::wrap;
using tensorflow::strings::StrCat;

TF_ExecutionContext* TF_NewEagerExecutionContext(TFE_ContextOptions* options,
                                                 TF_Status* s) {
  TFE_Context* c_ctx = TFE_NewContext(options, s);
  if (TF_GetCode(s) != TF_OK) {
    return nullptr;
  }
  return wrap(static_cast<AbstractContext*>(unwrap(c_ctx)));
}

// TODO(b/154564140): Move this to its own header. This requires splitting
// c_api_experimental.h
struct TFE_ContextOptions {
  TF_SessionOptions session_options;
  // true if async execution is enabled.
  bool async = false;
  TFE_ContextDevicePlacementPolicy device_placement_policy{
      TFE_DEVICE_PLACEMENT_SILENT};
  // If true, use TFRT backend
  bool use_tfrt = false;