const char data[] = {1, 2, 3};
  const int64_t vec2_dims[] = {2};
  unique_tensor_ptr vec2_tensor(
      Int8Tensor(vec2_dims, TF_ARRAYSIZE(vec2_dims), data), TF_DeleteTensor);
  TF_Operation* vec2 = Const(vec2_tensor.get(), graph, status, "vec2");
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  const int64_t vec3_dims[] = {3};
  unique_tensor_ptr vec3_tensor(

            ASN1Sequence vec = (ASN1Sequence) constructed.getBaseObject();


                ASN1ObjectIdentifier spnego = (ASN1ObjectIdentifier) vec.getObjectAt(0);
                if ( !SPNEGO_OID.equals(spnego) ) {
                    throw new IOException("Malformed SPNEGO token, OID " + spnego);
                }
                ASN1TaggedObject tagged = (ASN1TaggedObject) vec.getObjectAt(1);

  std::vector<string> output_names_vec;
  if (output_names) {
    output_names_vec.reserve(noutputs);
    for (int i = 0; i < noutputs; ++i) {
      output_names_vec.push_back(string(output_names[i]));
    }
  }

  // Process control output names.
  std::vector<string> control_output_names_vec;
  if (control_output_names) {
    control_output_names_vec.reserve(ncontrol_outputs);

      }
    }
  }

 private:
  // TODO(b/174778737): Only hold needed outputs.
  vector<AbstractTensorHandle*> forward_outputs_;
};

Status BroadcastMul(AbstractContext* ctx, AbstractTensorHandle* vec,
                    AbstractTensorHandle* mat,
                    absl::Span<AbstractTensorHandle*> outputs) {
  if (!isa<ImmediateExecutionContext>(ctx)) {
    // TODO(b/168850692): Fix this.

   0E4F-0E5B
   0E81-0E82
   0E84
   0E87-0E88
   0E8A
   0E8D
   0E94-0E97
   0E99-0E9F
   0EA1-0EA3
   0EA5
   0EA7
   0EAA-0EAB
   0EAD-0EB0
   0EB2-0EB3
   0EBD
   0EC0-0EC4
   0EC6
   0ED0-0ED9
   0EDC-0EDD
   0F00-0F17
   0F1A-0F34
   0F36
   0F38
   0F3E-0F47
   0F49-0F6A
   0F7F
   0F85
   0F88-0F8B
   0FBE-0FC5
   0FC7-0FCC
   0FCF

      const std::vector<TF_Tensor*>& input_tensors,
      const absl::optional<std::vector<int64_t>>& expected_shape) {
    // Create input_shapes.
    TF_ShapeAndTypeList* input_shapes =
        TF_NewShapeAndTypeList(input_shapes_vec.size());
    for (size_t i = 0; i < input_shapes_vec.size(); ++i) {
      const auto& input_shape = input_shapes_vec[i];
      if (input_shape.has_value()) {

  }
  std::vector<tensorflow::CoordinatedTask> task_vec(tasks.length);
  auto* task_iter = static_cast<const tensorflow::CoordinatedTask*>(tasks.data);
  for (size_t i = 0; i < tasks.length; ++i) {
    task_vec[i].set_job_name(task_iter->job_name());
    task_vec[i].set_task_id(task_iter->task_id());
    ++task_iter;
  }
  auto results = coord_agent->GetTaskState(task_vec);
  if (!results.ok()) {

    const int64_t* dims) {
  if (num_dims != -1) {
    std::vector<tensorflow::shape_inference::DimensionHandle> dim_vec;
    dim_vec.reserve(num_dims);
    for (int i = 0; i < num_dims; ++i) {
      dim_vec.push_back(ic->MakeDim(dims[i]));
    }
    return ic->MakeShape(dim_vec);
  } else {
    return ic->UnknownShape();
  }
}

}  // namespace

   1EB4; 1EB5; Case map
   1EB6; 1EB7; Case map
   1EB8; 1EB9; Case map
   1EBA; 1EBB; Case map
   1EBC; 1EBD; Case map
   1EBE; 1EBF; Case map
   1EC0; 1EC1; Case map
   1EC2; 1EC3; Case map
   1EC4; 1EC5; Case map
   1EC6; 1EC7; Case map
   1EC8; 1EC9; Case map
   1ECA; 1ECB; Case map
   1ECC; 1ECD; Case map
   1ECE; 1ECF; Case map
   1ED0; 1ED1; Case map
   1ED2; 1ED3; Case map

0EBB..0EBD    ; valid                                  # 1.1  LAO VOWEL SIGN MAI KON..LAO SEMIVOWEL SIGN NYO
0EBE..0EBF    ; disallowed                             # NA   <reserved-0EBE>..<reserved-0EBF>
0EC0..0EC4    ; valid                                  # 1.1  LAO VOWEL SIGN E..LAO VOWEL SIGN AI
0EC5          ; disallowed                             # NA   <reserved-0EC5>