// if they are all fully defined; std::nullopt otherwise.
std::optional<std::vector<PartialTensorShape>> GetInferredInputShapes(
    int num_inputs, Node* send_from_host_node) {
  std::vector<PartialTensorShape> results(num_inputs);
  for (int i = 0; i < num_inputs; i++) {
    const Edge* e;
    if (!send_from_host_node->input_edge(i, &e).ok()) {
      return std::nullopt;
    }

}

void TF_AddInputList(TF_OperationDescription* desc, const TF_Output* inputs,
                     int num_inputs) {
  std::vector<NodeBuilder::NodeOut> input_list;
  input_list.reserve(num_inputs);
  for (int i = 0; i < num_inputs; ++i) {
    input_list.emplace_back(&inputs[i].oper->node, inputs[i].index);
  }
  desc->node_builder.Input(input_list);
}

    mlir::FunctionType callee_type = callee.getFunctionType();
    SmallVector<Type, 4> expected_callee_input_types;
    auto num_inputs = op.getInputs().size() / 2;
    for (unsigned i = 0; i < num_inputs; ++i) {
      auto input_type =
          mlir::dyn_cast<RankedTensorType>(op.getOperand(i).getType());
      auto scalar = RankedTensorType::get({}, input_type.getElementType());

      }
    }

    return mlir::UnrankedTensorType::get(element_type);
  };

  // Below we only try and do some shape inference for "source" ops which have
  // no inputs.
  if (node.num_inputs() > 0) return default_type();

  // Do some simply inference here to get the function arguments correct for
  // this common case.
  // TODO(jpienaar): Reconsider post refactoring shape functions.

  const auto &inputs_ty = op.getInputs().getType();
  int n_inputs = inputs_ty.size();
  if (n_inputs < 1) return op.emitOpError() << "No inputs";

  const auto &init_values_ty = op.getInitValues().getType();
  int n_init_values = init_values_ty.size();
  if (n_init_values != n_inputs) {
    return op.emitOpError() << "Number of inputs (" << n_inputs
                            << ") is different than number of init_values ("

    int num_input = input_ty.getNumElements();
    int input_last_dim = input_ty.getShape().back();
    if (input_last_dim < 1) return std::nullopt;
    int num_result = result_ty.getNumElements();
    auto size_last = *(--size.value_end<APInt>());
    int32_t k = size_last.getSExtValue();
    if (num_input / input_last_dim * k != num_result) return std::nullopt;

			}
		}()
		f()
	}

	expectPanic("Exec Exec", func() { db.Exec("PANIC|Exec|WIPE") })
	exec(t, db, "WIPE") // check not deadlocked
	expectPanic("Exec NumInput", func() { db.Exec("PANIC|NumInput|WIPE") })
	exec(t, db, "WIPE") // check not deadlocked
	expectPanic("Exec Close", func() { db.Exec("PANIC|Close|WIPE") })
	exec(t, db, "WIPE")             // check not deadlocked