const TensorShape& shape, DataType type, bool use_fast_memory,
    XlaLayoutPreference layout_preference) {
  xla::Shape xla_shape;
  TF_RETURN_IF_ERROR(
      tensorflow::TensorShapeToXLAShape(type, shape, &xla_shape));
  ApiConverter::StackHelper<XLA_Shape> se_shape(xla_shape);
  ApiConverter::StackHelper<XLA_Shape> tpu_shape;
  StatusHelper status;
  stream_executor::tpu::ExecutorApiFn()->XlaShapeToTpuShapeRepresentationFn(

      [shape_determination_fns](
          const xla::Shape& xla_shape) -> absl::StatusOr<xla::Shape> {
    TensorShape shape;
    TF_RETURN_IF_ERROR(XLAShapeToTensorShape(xla_shape, &shape));
    TF_ASSIGN_OR_RETURN(DataType dtype, EncodePrimitiveTypeAsDataType(
                                            xla_shape.element_type()));
    auto layout_preference = shape_determination_fns.layout_preference_fn(

    TF_RETURN_IF_ERROR(tensorflow::ConvertToTensor(
        llvm::dyn_cast<TF::ConstOp>(fold_results[0].getDefiningOp()).getValue(),
        &tensor));
    xla::Shape xla_shape;
    TF_RETURN_IF_ERROR(tensorflow::TensorShapeToXLAShape(
        tensor.dtype(), tensor.shape(), &xla_shape));
    xla::PjRtClient::HostBufferSemantics host_buffer_semantics =
        xla::PjRtClient::HostBufferSemantics::kImmutableUntilTransferCompletes;