void TF_DeleteAbstractFunction(TF_AbstractFunction* func) {
  unwrap(func)->Unref();
}

void TF_ExecutionContextRegisterFunction(TF_ExecutionContext* ctx,
                                         TF_AbstractFunction* func,
                                         TF_Status* s) {
  tsl::Set_TF_Status_from_Status(s,
                                 unwrap(ctx)->RegisterFunction(unwrap(func)));

namespace tracing {
namespace graph {
GraphFunction::GraphFunction(FunctionDef fdef)
    : AbstractFunction(kGraph),
      func_record_(new FunctionRecord(std::move(fdef), {}, true)) {}
GraphFunction::~GraphFunction() {}
Status GraphFunction::GetFunctionDef(const FunctionDef **fdef) {
  *fdef = &(func_record_->fdef());
  return absl::OkStatus();
}
}  // namespace graph
}  // namespace tracing

void TestRemoteExecuteSilentCopiesOp(bool async, bool remote,
                                     bool remote_func_outputs = false) {
  return TestRemoteExecuteSilentCopies(async, remote, /*func=*/false,
                                       /*heavy_load_on_streaming_rpc=*/false,
                                       remote_func_outputs);
}

TEST(CAPI, RemoteExecuteSilentCopies) {

                                       bool remote_func_outputs = false,
                                       bool has_packed_input = false) {
  return TestRemoteExecuteSilentCopies(async, remote, /*func=*/true,
                                       heavy_load_on_streaming_rpc,
                                       remote_func_outputs, has_packed_input);
}

TEST(CAPI, RemoteExecuteSilentCopiesAsyncFunc) {

  options->stack_size = 0;
  options->guard_size = 0;
  options->numa_node = -1;
}

TF_Thread* TF_StartThread(const TF_ThreadOptions* options,
                          const char* thread_name, void (*work_func)(void*),
                          void* param) {
  ::tensorflow::ThreadOptions cc_options;
  cc_options.stack_size = options->stack_size;
  cc_options.guard_size = options->guard_size;

    {
      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());
      TF_RETURN_IF_ERROR(model(func_ctx.get(), absl::MakeSpan(func_inputs),

  return def.SerializeAsString();
}

void TestRemoteExecuteSilentCopies(bool async, bool remote, bool func,
                                   bool heavy_load_on_streaming_rpc,
                                   bool remote_func_outputs,
                                   bool has_packed_input) {
  CHECK(!has_packed_input || func);
  tensorflow::ServerDef server_def = GetServerDef(3);

  // This server def has the task index set to 0.

}
Status TapeContext::RegisterFunction(AbstractFunction* f) {
  return parent_ctx_->RegisterFunction(f);
}
Status TapeContext::RemoveFunction(const string& func) {
  return parent_ctx_->RemoveFunction(func);
}

}  // namespace gradients

  value = -1;

  // Read our first value
  cache2.LookupOrCompute("a", &value, compute_func, &status);
  TF_EXPECT_OK(status.status);
  EXPECT_EQ(value, 0);
  EXPECT_EQ(num_compute_calls, 1);
  // Re-read, exepct no additional function compute_func calls.
  cache2.LookupOrCompute("a", &value, compute_func, &status);
  TF_EXPECT_OK(status.status);
  EXPECT_EQ(value, 0);
  EXPECT_EQ(num_compute_calls, 1);