// as we are replacing it with tf_saved_model.index_path.
  SmallVector<NamedAttribute> new_arg_attrs;
  for (auto arg_attr : arg_attrs) {
    if (arg_attr.getName() == "tf_saved_model.bound_input") continue;
    new_arg_attrs.emplace_back(arg_attr);
  }

  const NamedAttribute index_path_attr(
      builder.getStringAttr(kTfSavedModelIndexPathAttr),
      builder.getStrArrayAttr({index_path}));

  func::FuncOp main_func_op = GetMainFuncOp(*module_op);
  DictionaryAttr arg_attrs = main_func_op.getArgAttrDict(/*index=*/0);

  EXPECT_THAT(arg_attrs.get("tf_saved_model.bound_input"), IsNull());

  const ArrayRef<Attribute> index_path_attrs =
      mlir::cast<ArrayAttr>(arg_attrs.get("tf_saved_model.index_path"))
          .getValue();
  EXPECT_THAT(index_path_attrs, SizeIs(1));

  // TF op.
  LogicalResult CollectInputsAndAttributes(
      PatternRewriter& rewriter, TFRFuncOp signature, CallOp call_op,
      SmallVectorImpl<Value>* inputs, NamedAttrList* arg_attrs,
      llvm::StringMap<Attribute>* derived_attrs) const;

  // Uses the collected attribute values to derive all the output types.
  LogicalResult DeriveOutputTypes(Location loc, FunctionType signature,

    llvm::SmallVector<Type> arg_types;
    llvm::SmallVector<Type> res_types;
    llvm::SmallVector<DictionaryAttr> arg_attrs;
    llvm::SmallVector<DictionaryAttr> res_attrs;
    if (failed(FilterTfgSpecificArgResultAttributes(
            getContext(), ftype.getInputs(), graph_func.getAllArgAttrs(),
            arg_types, arg_attrs)) ||
        failed(FilterTfgSpecificArgResultAttributes(

      llvm::StringSet<> all_attrs;
      for (auto& attr : (*this)->getAttrs()) {
        all_attrs.insert(attr.getName().strref());
      }
      for (const auto& operand : llvm::enumerate(getArgumentTypes())) {
        if (auto attr_name = getArgAttrOfType<StringAttr>(
            operand.index(), kAttrArgumentNameAttr)) {
          all_attrs.insert(attr_name.getValue());
        }
      }

    const absl::InlinedVector<Node*, 4>& control_ret_nodes) {
  // Store the arg/return attributes as a list rather than uniqueuing during
  // construction.
  llvm::SmallVector<mlir::NamedAttrList, 4> arg_attrs;
  arg_attrs.resize(func.getNumArguments());
  llvm::SmallVector<mlir::NamedAttrList, 4> ret_attrs;
  ret_attrs.resize(func.getNumResults());

  auto set_attributes_on_func = [&](Node* node, int64_t index, bool is_arg) {

  // Fetch inputs and outputs from the signature.
  llvm::SmallVector<mlir::DictionaryAttr, 4> arg_attrs, res_attrs;
  main_op.getAllArgAttrs(arg_attrs);
  main_op.getAllResultAttrs(res_attrs);
  std::vector<std::string> sig_def_inputs =
      GetStringsFromDictionaryAttr(arg_attrs, kTfSavedModelIndexPathAttr);
  std::vector<std::string> sig_def_outputs =

\07\03\01\05\03\11\01\t\05\03\05\0B\03\01\01\05\06\13\03\01\03\01\07\04\01\03\03\06\03\01\05\01\00\9A\04-\0F\0B\03!\1B\1D\05\1B\83/\1F\15\1D\15\11\13\15\11\11\0F\0B\11builtin\00vhlo\00module\00func_v1\00sine_v1\00return_v1\00sym_name\00jit_sin\00arg_attrs\00function_type\00res_attrs\00sym_visibility\00jit(sin)/jit(main)/sin\00third_party/py/jax/experimental/jax2tf/tests/back_compat_test.py\00jax.arg_info\00x\00mhlo.sharding\00{replicated}\00jax.result_info\00\00main\00public\00", platforms = ["CPU"],...