return names;
}

CSession::CSession(TF_Graph* graph, TF_Status* s, bool use_XLA) {
  TF_SessionOptions* opts = TF_NewSessionOptions();
  TF_EnableXLACompilation(opts, use_XLA);
  session_ = TF_NewSession(graph, opts, s);
  TF_DeleteSessionOptions(opts);
}

CSession::CSession(TF_Session* session) : session_(session) {}

CSession::~CSession() {
  TF_Status* s = TF_NewStatus();

// been deleted (with TFE_DeleteTensorHandle).
//
// TODO(ashankar): Merge with TF_Session?
typedef struct TFE_Context TFE_Context;

TF_CAPI_EXPORT extern TFE_Context* TFE_NewContext(
    const TFE_ContextOptions* opts, TF_Status* status);
TF_CAPI_EXPORT extern void TFE_DeleteContext(TFE_Context* ctx);
TF_CAPI_EXPORT extern TF_DeviceList* TFE_ContextListDevices(TFE_Context* ctx,

      TF_NewStatus(), TF_DeleteStatus);
  TFE_ContextOptions* opts = TFE_NewContextOptions();
  TFE_ContextOptionsSetTfrt(opts, use_tfrt);
  *ctx = unwrap(TF_NewEagerExecutionContext(opts, status.get()));
  TF_RETURN_IF_ERROR(StatusFromTF_Status(status.get()));
  TFE_DeleteContextOptions(opts);
  return absl::OkStatus();
}

Status GetValue(AbstractTensorHandle* t, TF_Tensor** result_tensor) {

    srcs = [
        "c_api.cc",
        "c_api_debug.cc",
        "c_api_experimental.h",
        "c_api_internal.h",
        "c_api_unified_experimental.h",
    ],
    hdrs = ["c_api.h"],
    copts = tf_copts(),
    visibility = ["//visibility:public"],
    deps = select({
        "//tensorflow:android": [
            "//tensorflow/core:portable_tensorflow_lib_lite",
        ],
        "//conditions:default": [

  TF_Status* status = TF_NewStatus();
  TFE_ContextOptions* opts = TFE_NewContextOptions();
  opts->session_options.options.config.set_isolate_session_state(
      isolate_session_state);
  TFE_ContextOptionsSetAsync(opts, static_cast<unsigned char>(false));
  TFE_ContextOptionsSetDevicePlacementPolicy(opts, TFE_DEVICE_PLACEMENT_SILENT);
  TFE_Context* ctx = TFE_NewContext(opts, status);
  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

      opts->session_options.options,
      static_cast<tensorflow::ContextDevicePlacementPolicy>(
          opts->device_placement_policy),
      opts->async, device_mgr.release(),
      /*device_mgr_owned*/ true, std::move(r),
      /*cluster_flr=*/nullptr,
      /*collective_executor_mgr=*/nullptr,
      /*run_eager_op_as_function=*/opts->run_eager_op_as_function,

                               inputs.size(), inputs.data(), outputs.size(),
                               outputs.data(), output_names_ptr,
                               /*opts=*/nullptr, /*description=*/nullptr, s_);
    delete[] output_names_ptr;
    if (expect_failure) {
      ASSERT_EQ(func_, nullptr);
      return;
    }

    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  *func = TF_GraphToFunction(func_graph.get(), name, append_hash, -1,
                             /*opers=*/nullptr, 1, inputs, 1, outputs,
                             /*output_names=*/nullptr,
                             /*opts=*/nullptr, description, s.get());
  ASSERT_EQ(TF_OK, TF_GetCode(s.get())) << TF_Message(s.get());
  ASSERT_NE(*func, nullptr);
}

class CApiExperimentalFunctionTest : public ::testing::Test {
 protected:

#     define_values = {"PORTABLE_PROTO_TRANSITION_MODE": "third_party"},
#     visibility = ["//visibility:public"],
# )
# copybara:uncomment_end

# 'enable_registration_v2' opts-in to a different implementation of op and
# kernel registration - REGISTER_OP, REGISTER_KERNEL_BUILDER, etc.
#
# This setting is currently experimental. The 'v2' implementation does _not_

    *   **Windows x64 & x86 packages:**
        *   oneDNN optimizations are *enabled by default* on X86 CPUs
    *   To explicitly enable or disable oneDNN optimizations, set the environment variable `TF_ENABLE_ONEDNN_OPTS` to `1` (enable) or `0` (disable) before running TensorFlow. To fall back to default settings, unset the environment variable.