// TODO(jpienaar): Temporary flag, flip default and remove.
extern llvm::cl::opt<bool> enable_shape_inference;
extern llvm::cl::opt<bool> unconditionally_use_set_output_shapes;
extern llvm::cl::opt<bool> enable_soft_placement;
extern llvm::cl::opt<bool> set_original_tf_func_name;

// Export options.
extern llvm::cl::opt<bool> export_entry_func_to_flib;
extern llvm::cl::opt<bool> export_original_tf_func_name;

  specs.unconditionally_use_set_output_shapes =
      import_options.unconditionally_use_set_output_shapes;
  specs.xla_compile_device_type = import_options.xla_compile_device_type;
  specs.enable_soft_placement = import_options.enable_soft_placement;
  specs.set_original_tf_func_name = import_options.set_original_tf_func_name;
  TF_RETURN_IF_ERROR(ParseInputArrayInfo(input_arrays, input_dtypes,

      prune_unused_nodes,     convert_legacy_fed_inputs,
      graph_as_function,      upgrade_legacy,
      enable_shape_inference, unconditionally_use_set_output_shapes,
      enable_soft_placement,  set_original_tf_func_name};

  auto module_or = tensorflow::GraphdefToMlirTranslateFunction(
      input, input_arrays, input_dtypes, input_shapes, output_arrays,
      control_output_arrays, options, context);

  bool prune_unused_nodes;
  bool convert_legacy_fed_inputs;
  bool graph_as_function;
  bool upgrade_legacy;
  bool enable_shape_inference;
  bool unconditionally_use_set_output_shapes;
  bool enable_soft_placement;
  bool set_original_tf_func_name = false;
};

// TODO(antiagainst): Directly manipulating files in library functions is not
// a good idea. We should pass in a string/stream here.

    llvm::cl::desc("Enable using the _output_shapes unconditionally on import "
                   "(temporary)"),
    llvm::cl::init(false));

// NOLINTNEXTLINE
opt<bool> enable_soft_placement(
    "tf-enable-soft-placement-on-import",
    llvm::cl::desc("Enable soft device placement on import."),
    llvm::cl::init(false));

// NOLINTNEXTLINE
opt<bool> set_original_tf_func_name(

  // XLA compilation.
  string xla_compile_device_type;
  // If true, enables moving ops to different devices or moving unsupported ops
  // out of a compilation cluster.
  bool enable_soft_placement = false;
  // If true, a function attribute, `tf._original_func_name`, will be set in
  // functions which contains the corresponding original TF function name.
  bool set_original_tf_func_name = false;
};

  // during import is not necessary.
  import_config.enable_shape_inference = false;
  import_config.xla_compile_device_type =
      function_options.xla_compile_device_type;
  import_config.enable_soft_placement = function_options.allow_soft_placement;

  static const char* kTfMlirCategory = "TfMlir";
  tensorflow::metrics::ScopedCounter<2> timings(
      tensorflow::metrics::GetGraphOptimizationCounter(),

      /*convert_legacy_fed_inputs=*/true,
      /*graph_as_function=*/false,
      specs.upgrade_legacy,
      /*enable_shape_inference=*/false,
      /*unconditionally_use_set_output_shapes=*/true,
      /*enable_soft_placement=*/false};

  if (use_splatted_constant) {
    return GraphdefToSplattedMlirTranslateFunction(
        file->getBuffer(), input_arrays, input_dtypes, input_shapes,

                         b.getStringAttr(specs.xla_compile_device_type)));
    }
    attrs.push_back(b.getNamedAttr("allow_soft_placement",
                                   b.getBoolAttr(specs.enable_soft_placement)));
  } else {
    // Collects the argument and return nodes by looking up the node names
    // specified by the user.
    TF_ASSIGN_OR_RETURN(func_type, importer.InferMainFunctionType(