class Tf_GreaterOp:
    def __init__(self, *args, **kwargs) -> None: ...
    def create(self, arg0: Location, arg1: Value, arg2: Value) -> Operation: ...

class Tf_LegacyCallOp:
    def __init__(self, *args, **kwargs) -> None: ...
    def create(self, arg0: Location, arg1: list[Type], arg2: list[Value], arg3: str) -> Operation: ...

class Tf_LessEqualOp:

              mlir::Value y) -> mlir::Operation* {
             return opb.create<mlir::TF::GreaterOp>(loc, x, y).getOperation();
           });

  // mlir::TF::LegacyCallOp
  py::class_<mlir::TF::LegacyCallOp>(m, "Tf_LegacyCallOp")
      .def("create",
           [](mlir::OpBuilder& opb, mlir::Location loc,
              std::vector<mlir::Type> output, std::vector<mlir::Value> args,
              std::string f) -> mlir::Operation* {

            (CallOp $f, $args),
          [(ArgTypesMatchCallee $op, $args, $f)]>;
}

// The extra attr on this op is _disable_call_shape_inference, which we ignore
// in the bridge.
def : Pat<(TF_LegacyCallOp:$op $args, FlatSymbolRefAttr:$f, $attr),
          (CallOp $f, $args),
        [(ArgTypesMatchCallee $op, $args, $f)]>;

//===----------------------------------------------------------------------===//

  TF_DerivedOperandTypeListAttr Tnext_func_args = TF_DerivedOperandTypeListAttr<1>;
  TF_DerivedOperandTypeListAttr Tfinalize_func_args = TF_DerivedOperandTypeListAttr<2>;
}

def TF_LegacyCallOp : TF_Op<"LegacyCall",
      [CallOpInterface,
       DeclareOpInterfaceMethods<SymbolUserOpInterface>, Pure]> {
  let summary =
    "returns `f(inputs)`, where `f` is a function.";

  let description = [{