(TF_SubOp $max_range, $min_range),
          (TF_ConstOp (GetF32Scalar<255>)))),
      $min_range),
    /*truncate=*/ConstBoolAttrFalse),
  [(TensorOf<[TF_Qint8, TF_Quint8]> $input),
   (TF_Float32Tensor $min_range),
   (TF_Float32Tensor $max_range),
   (TensorOf<[TF_Float32, TF_Bfloat16]> $result)]>;

//===----------------------------------------------------------------------===//
// Difference op patterns.

  }];

  let arguments = (ins
    Arg<TensorOf<[TF_Bfloat16, TF_Float16, TF_Float32]>, [{A 4D Tensor for input data.}]>:$x,
    Arg<TensorOf<[TF_Bfloat16, TF_Float32]>, [{A 1D Tensor for scaling factor, to scale the normalized x.}]>:$scale,
    Arg<TensorOf<[TF_Bfloat16, TF_Float32]>, [{A 1D Tensor for offset, to shift to the normalized x.}]>:$offset,

// TFL Relu doesn't support I32/I64 type, so legalizes TF Relu to TFL Maximum.
def LegalizeReluI32 :
  Pat<(TF_ReluOp TensorOf<[I32]>:$arg),
      (TFL_MaximumOp $arg,
        (Arith_ConstantOp ConstantAttr<RankedI32ElementsAttr<[]>,"0">))>;
def LegalizeReluI64 :
  Pat<(TF_ReluOp TensorOf<[I64]>:$arg),
      (TFL_MaximumOp $arg,
        (Arith_ConstantOp

class TFL_TensorOf<list<Type> allowedRuntimeTypes,
                   list<Type> allowedOpTypes = [AnyType]> :
  TensorOf<allowedOpTypes>, TFL_RuntimeType<TensorOf<allowedRuntimeTypes>> {
  // Set the summary equal to that representing the runtime types.
  let summary = TensorOf<allowedRuntimeTypes>.summary;
}

class TFL_TensorOfOrNone<list<Type> allowedRuntimeTypes, string description = "",