return tensorflow::CustomDeviceTensorHandle::SummarizeValue(summary);
    }
    TF_Status c_status;
    std::unique_ptr<TF_Buffer, decltype(&TF_DeleteBuffer)> summary_buffer(
        methods_.summarize(data_, &c_status), TF_DeleteBuffer);
    if (!c_status.status.ok()) {
      return c_status.status;
    }
    summary = std::string(reinterpret_cast<const char*>(summary_buffer->data),

  absl::Status cc_status;
  if (var_info == nullptr) {
    cc_status = absl::InvalidArgumentError("TF_VariableInfo is NULL.");
    status->status = cc_status;
    return nullptr;
  }
  if (var_info->var_info.var() == nullptr) {
    cc_status = absl::InvalidArgumentError(
        "VariableInfo does not track a resource variable.");
    status->status = cc_status;
    return nullptr;
  }

                   TF_Status* status) {
  auto posix_file = static_cast<PosixFile*>(file->plugin_file);

  size_t r = fwrite(buffer, 1, n, posix_file->handle);
  if (r != n)
    TF_SetStatusFromIOError(status, errno, posix_file->filename);
  else
    TF_SetStatus(status, TF_OK, "");
}

static int64_t Tell(const TF_WritableFile* file, TF_Status* status) {

                                 TF_Status* status)) {
  auto* cc_builder = reinterpret_cast<OpDefBuilder*>(builder);
  cc_builder->SetShapeFn(
      [shape_inference_func](InferenceContext* ctx) -> tensorflow::Status {
        TF_Status* c_status = TF_NewStatus();
        auto c_ctx = reinterpret_cast<TF_ShapeInferenceContext*>(ctx);
        shape_inference_func(c_ctx, c_status);

                         TF_Status* const status) -> void {
    *stream = new SP_Stream_st(1);
  };
  se_.destroy_stream = [](const SP_Device* const device,
                          SP_Stream stream) -> void { delete stream; };
  se_.create_event = [](const SP_Device* const device, SP_Event* event,
                        TF_Status* const status) -> void {
    *event = new SP_Event_st(2);
  };

                                                    TF_Status* status);

TF_CAPI_EXPORT extern void TFE_OpSetDevice(TFE_Op* op, const char* device_name,
                                           TF_Status* status);
// The returned string remains valid throughout the lifetime of 'op'.
TF_CAPI_EXPORT extern const char* TFE_OpGetDevice(const TFE_Op* op,
                                                  TF_Status* status);

                                        TF_Status* status) {
  tensorflow::unwrap(ctx)->SetRunEagerOpAsFunction(enable);
}

void TFE_ContextSetJitCompileRewrite(TFE_Context* ctx, unsigned char enable,
                                     TF_Status* status) {
  tensorflow::unwrap(ctx)->SetJitCompileRewrite(enable);
}

const char* TFE_TensorHandleDeviceType(TFE_TensorHandle* h, TF_Status* status) {
  if (h == nullptr) {

  void (*create_stream_dependency)(const SP_Device* device, SP_Stream dependent,
                                   SP_Stream other, TF_Status* status);

  // Without blocking the device, retrieve the current stream status.
  void (*get_stream_status)(const SP_Device* device, SP_Stream stream,
                            TF_Status* status);

  /*** EVENT CALLBACKS ***/
  // Create SP_Event. Performs platform-specific allocation and initialization

                                                   TF_Status* status) {
  auto* cc_ctx = reinterpret_cast<::tensorflow::OpKernelConstruction*>(ctx);
  tensorflow::NameAttrList function;
  auto cc_status = cc_ctx->GetAttr(attr_name, &function);
  if (!cc_status.ok()) {
    tsl::Set_TF_Status_from_Status(status, cc_status);
    return nullptr;
  }
  TF_Buffer* buffer = TF_NewBuffer();
  cc_status = tensorflow::MessageToBuffer(function, buffer);

  params.patch_version = GO_PATCH;
  params.optimizer = &optimizer;
  params.optimizer_configs = &optimizer_configs;

  OwnedTFStatus c_status(TF_NewStatus());
  init_fn(&params, c_status.get());
  TF_RETURN_IF_ERROR(tsl::StatusFromTF_Status(c_status.get()));
  TF_RETURN_IF_ERROR(ValidateTPOptimizerRegistrationParams(params));
  TF_RETURN_IF_ERROR(ValidateTPOptimizer(optimizer));