// Process inputs.
  std::vector<tensorflow::OutputTensor> input_tensors;
  std::unordered_map<const Node*, std::vector<int>> input_nodes;
  status->status = tensorflow::ProcessInputs(fn_body, fn_name, ninputs, inputs,
                                             &input_tensors, &input_nodes);
  if (TF_GetCode(status) != TF_OK) return nullptr;

  // Process outputs.
  std::vector<tensorflow::OutputTensor> output_tensors;

    // Input tensors
    const std::vector<std::pair<string, Tensor>>& input_pairs,
    // Output tensors
    const std::vector<string>& output_tensor_names, TF_Tensor** c_outputs,
    // Target nodes
    const std::vector<string>& target_oper_names, TF_Buffer* run_metadata,
    TF_Status* status) {
  const int noutputs = output_tensor_names.size();
  std::vector<Tensor> outputs(noutputs);
  Status result;

  if (!status->status.ok()) return;

  // Initialize a input_tensor vector with `nullptr` values.
  std::vector<const Tensor*> input_tensors_vector(num_inputs, nullptr);
  // A vector to keep track of newly created `tf::Tensor` objects.
  std::vector<Tensor> all_input_tensors;
  // Update the vector with information from `input_tensors` if provided.
  if (input_tensors != nullptr) {

  std::vector<tensorflow::string> tensor_id_data;
};

struct TF_ImportGraphDefResults {
  std::vector<TF_Output> return_tensors;
  std::vector<TF_Operation*> return_nodes;
  std::vector<const char*> missing_unused_key_names;
  std::vector<int> missing_unused_key_indexes;

  // Backing memory for missing_unused_key_names values.
  std::vector<tensorflow::string> missing_unused_key_names_data;

	// 31.11.15: Vector Integer Merge Instructions
	VMERGEVVM	V1, V2, V0, V3			// d781205c
	VMERGEVXM	X10, V2, V0, V3			// d741255c
	VMERGEVIM	$15, V2, V0, V3			// d7b1275c

	// 31.11.16: Vector Integer Move Instructions
	VMVVV		V2, V3				// d701015e
	VMVVX		X10, V3				// d741055e
	VMVVI		$15, V3				// d7b1075e

	// 31.12.1: Vector Single-Width Saturating Add and Subtract

  }

  // Checks the expected result of shape inference for the given `op`.
  void CheckOutputShapes(
      TFE_Op* op,
      const std::vector<absl::optional<std::vector<int64_t>>>& input_shapes_vec,
      const std::vector<TF_Tensor*>& input_tensors,
      const absl::optional<std::vector<int64_t>>& expected_shape) {
    // Create input_shapes.
    TF_ShapeAndTypeList* input_shapes =

        .createTestSuite();
  }

  // We are testing Vector / testing our tests on Vector.
  @SuppressWarnings("JdkObsolete")
  private Test testsForVector() {
    return ListTestSuiteBuilder.using(
            new TestStringListGenerator() {
              @Override
              protected List<String> create(String[] elements) {
                return new Vector<>(MinimalCollection.of(elements));
              }
            })

        .createTestSuite();
  }

  // We are testing Vector / testing our tests on Vector.
  @SuppressWarnings("JdkObsolete")
  private Test testsForVector() {
    return ListTestSuiteBuilder.using(
            new TestStringListGenerator() {
              @Override
              protected List<String> create(String[] elements) {
                return new Vector<>(MinimalCollection.of(elements));
              }
            })

  bool ret = TF_GetCode(s) == TF_OK;
  if (ret) ret = attr_value->ParseFromArray(buffer->data, buffer->length);
  TF_DeleteBuffer(buffer);
  return ret;
}

std::vector<std::pair<string, string>> GetGradDefs(
    const tensorflow::GraphDef& graph_def) {
  std::vector<std::pair<string, string>> grads;
  for (const tensorflow::GradientDef& grad : graph_def.library().gradient()) {
    grads.emplace_back(grad.function_name(), grad.gradient_func());

            if (mechs != null) {
                final ASN1EncodableVector vector = new ASN1EncodableVector();
                for (final ASN1ObjectIdentifier mech : mechs) {
                    vector.add(mech);
                }
                fields.add(new DERTaggedObject(true, 0, new DERSequence(vector)));
            }
            final int ctxFlags = getContextFlags();
            if (ctxFlags != 0) {