// don't want to have a `std::vector<std::string>` at global level, we use a
// static pointer to such a vector: we construct it via `SchemeVector()` below
// and when tests are instantiated we process it using `GetSchemes()`.
static std::vector<std::string>* SchemeVector() {
  static std::vector<std::string>* schemes = new std::vector<std::string>;
  return schemes;
}

    EXPECT_TRUE(found);
    TF_DeleteBuffer(op_list_buffer);
  }
}

void TestEncodeDecode(int line, const std::vector<string>& data) {
  const int64_t n = data.size();
  Status status;
  for (const std::vector<int64_t>& dims :
       std::vector<std::vector<int64_t>>{{n}, {1, n}, {n, 1}, {n / 2, 2}}) {
    // Create C++ Tensor
    Tensor src(tensorflow::DT_STRING, TensorShape(dims));

  // `ctx_0`, `ctx_1`, `ctx_2` contains `remote_device`.
  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_0);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());
  }

  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_1);

    std::vector<TF_Output> out;
    for (auto op : ops) {
      out.push_back({op, 0});
    }
    return out;
  }

  void Define(int num_opers, const std::vector<TF_Operation*>& opers,
              const std::vector<TF_Operation*>& inputs,
              const std::vector<TF_Operation*>& outputs,
              const std::vector<string>& output_names,
              bool expect_failure = false) {

build:release_arm64_linux --config=linux_arm64
build:release_arm64_linux --crosstool_top="@ml2014_clang_aarch64_config_aarch64//crosstool:toolchain"
build:release_arm64_linux --config=mkl_aarch64_threadpool
build:release_arm64_linux --copt=-flax-vector-conversions
test:release_arm64_linux --flaky_test_attempts=3

# The old gcc linux build options are preserved in the unsupported_*_linux
# configs. If your project fails to build with Clang, you can use these

//
//    ncontrol_outputs: Number of control outputs of the function.
//    control_outputs: vector of TF_Operation objects to be marked as control
//      outputs of the function. Operations marked as control outputs are
//      guaranteed to execute.
//    control_output_names: Optional. If not nullptr, vector of strings, one
//      per control output, with their names to be added to the function's
//      OpDef.