return ConvertOpStatsToQDQs<TFL::SVDFOp>::processInputs(
        op, op_variant, op_property, rewriter);
  }
};

class PropagateTransposedPerAxisQuantDim
    : public OpRewritePattern<TFL::TransposeOp> {
 public:
  explicit PropagateTransposedPerAxisQuantDim(MLIRContext* context)
      : OpRewritePattern<TFL::TransposeOp>(context) {}
  LogicalResult matchAndRewrite(TFL::TransposeOp transpose_op,

    patterns_1.add<PrepareLstmOutputScale<UnidirectionalSequenceLSTMOp>>(ctx);
  }
  if (is_qdq_conversion_ ||
      quant_specs_.qdq_conversion_mode != quant::QDQConversionMode::kQDQNone) {
    patterns_1.add<PropagateTransposedPerAxisQuantDim>(ctx);
  }
  (void)applyPatternsAndFoldGreedily(func, std::move(patterns_1));

  // During the legalization, unsigned quantized type is used, so we have to
  // convert all of them to signed.

      // and `RequiredSameQuantizedAxes` set to false.
      // Currently, these lines of code are only applicable to TFL_TransposeOp
      // and the output q-dq propagation for this Op is performed in
      // `PropagateTransposedPerAxisQuantDim`.
      if (is_qdq_conversion_ &&
          !scale_spec->required_same_quantized_axes_func()) {
        if (HasPerAxisQuantizedOperand(op)) continue;
      }