(HasRankAtMost<4> $input),
   (HasRankAtMost<4> $operand)]>;

  def FuseTileBroadcastToBinaryOp2#BinaryOp : Pat<
    (BinaryOp:$result $operand,
      (TFL_TileOp $input, (Arith_ConstantOp $tile)), $act_func),
    (BinaryOp $operand, $input, $act_func),
  [(OperandsBroadcastToOutputType $operand, $input, $result),
   (HasRankAtMost<4> $operand),
   (HasRankAtMost<4> $input)]>;
}

  RankedTensorType type = GetRankedTensorTypeForOperand(value);
  return !type || type.getRank() >= rank;
}

// Returns true if the given `value` has at most the specified rank or has
// unranked type.
inline bool HasRankAtMost(Value value, int64_t rank) {
  RankedTensorType type = GetRankedTensorTypeForOperand(value);
  return !type || type.getRank() <= rank;
}

inline bool IsUnknownDimOrRank(int64_t dim_or_rank) {

  if (!ttype.hasRank()) return success();
  if (!HasRankAtLeast(op.getInput(), 2))
    return op.emitOpError(
        "requires ranked input tensor to be of rank 2 or more");
  if (!HasRankAtMost(op.getInput(), std::numeric_limits<int32_t>::max()))
    return op.emitOpError(
        "requires ranked input tensor to be of rank INT32_MAX or less");

  return success();
}

  Operation::operand_range values = op.getValues();

  int axis_idx = std::is_same<OpT, ConcatOp>() ? 0 : 1;
  Value axis = *op.getODSOperands(axis_idx).begin();
  if (!HasRankAtMost(axis, 1)) {
    return op.emitOpError(
        "requires axis to be of scalar type (or vector type for older "
        "versions)");
  }

  return VerifyTypesCompatibility(values,

//       $qparams)),
//   $act_fn),
//   [(AnyStaticShapeTensor $lhs),
//    (IsLastDimEqualToNumElements $bias, $bias),
//    (HasOneUse $const_op),
//    (HasRankAtMost<4> $bias),
//    (HasRankAtLeast<2> $bias),
//    (IsDefinedByFullyConnectedOp $lhs)]>;
struct UndoBroadcastFullyConnectedBiasAddWithQDQs
    : public OpRewritePattern<TFL::AddOp> {