bool ShouldFallbackToGraphCompiler(
    const std::variant<MlirToHloArgs, FunctionToHloArgs>& computation) {
  if (computation.index() == 1) return true;

  return std::get<0>(computation).rollout_state ==
         ConfigProto::Experimental::MLIR_BRIDGE_ROLLOUT_DISABLED;
}

void DumpComputationInput(
    const std::variant<tpu::MlirToHloArgs, tpu::FunctionToHloArgs>
        computation) {
  if (!VLOG_IS_ON(2)) {
    return;
  }

// compiled XLA HLO. V1 of the tf2xla uses MLIR whereas V0 does not use MLIR.
//
// Inputs:
//  computation - The MLIR module op. It currently takes in
//  tpu::FunctionToHloArgs but this is deprecated. arg_shapes - The shapes of
//  the arguments in module_op. device_type - The device type to compile for.
//  use_tuple_args - Pack the incoming arg shapes into a single tuple.

// converted to a Tensorflow graph. Otherwise, the graph compiler will be run.
absl::Status CompileTensorflowGraphToHlo(
    const std::variant<tpu::MlirToHloArgs, tpu::FunctionToHloArgs>& computation,
    const tpu::TPUCompileMetadataProto& metadata, bool use_tuple_args,
    XlaShapeLayoutHelpers::ShapeDeterminationFns shape_determination_funcs,
    const std::vector<tensorflow::TensorShape>& arg_shapes,