} else if (str == "float32") {
      return builder.getF32Type();
    } else {
      return {};
    }
  };
  if (io_node_types_.size() < 2) return failure();
  if (!input_type) input_type = convert_str_to_type(io_node_types_[0]);
  if (!output_type) output_type = convert_str_to_type(io_node_types_[1]);
  return success();
}

LogicalResult ModifyIONodesPass::ModifyInputNodes(

  }];
  let constructor = "CreateModifyIONodesPass()";
  let dependentDialects = ["TFL::TensorFlowLiteDialect"];
  let options = [
      ListOption<"io_node_types_", "test-io-types", "std::string",
                 "comma separated type strings. Allowed values: 'int8', 'uint8', 'float32']">,
  ];
}

def OptimizePass : Pass<"tfl-optimize", "mlir::func::FuncOp"> {