Status ConvertToTensorProto(mlir::ElementsAttr attr,
                            TensorProto* output_tensor);

// Converts an MLIR elements attribute to a TensorFlow tensor.
Status ConvertToTensor(mlir::ElementsAttr attr, Tensor* output_tensor);

}  // namespace tensorflow

        "Operand idx 1 is not a tf.ConstOp. The initializing tensor is not "
        "saved to checkpoint.");
    return "";
  }

  Tensor const_tensor{};
  if (const absl::Status status = mlir::tfg::ConvertToTensor(
          /*attr=*/const_op.getValue(), /*output_tensor=*/&const_tensor);
      !status.ok()) {
    return status;
  }

  if (!bundle_writer.Add(/*key=*/var_handle_op.getSharedName(), const_tensor)

  }

  VLOG(1) << "Start to evaluate node: " << *node_def;

  // Adds inputs to the TF operation.
  for (const auto operand : operands) {
    Tensor tensor;
    RETURN_FAILURE_IF_ERROR(ConvertToTensor(operand, &tensor));
    TF_Tensor* tf_tensor = TF_TensorFromTensor(tensor, &status->status);
    RETURN_FAILURE_IF_ERROR(status);
    auto clean_tensor =
        MakeCleanup([tf_tensor] { TF_DeleteTensor(tf_tensor); });

  std::vector<tensorflow::Tensor> inputs;

  // Adds inputs to the TF operation.
  for (const ElementsAttr& operand : operands) {
    tensorflow::Tensor tensor;
    RETURN_FAILURE_IF_ERROR(tensorflow::ConvertToTensor(operand, &tensor));
    inputs.push_back(std::move(tensor));
  }

  std::vector<tensorflow::TensorValue> input_values;
  for (tensorflow::Tensor& tensor : inputs) {
    input_values.emplace_back();