auto qconst_op = llvm::dyn_cast_or_null<QConstOp>(def_op);
    if (qconst_op == nullptr) return failure();

    DenseIntElementsAttr perm_tensor;
    if (!matchPattern(op.getPerm(), m_Constant(&perm_tensor))) return failure();

    if (!mlir::isa<quant::UniformQuantizedType>(
            (getElementTypeOrSelf(op.getOutput().getType()))))
      return failure();

    if (!type || !mlir::isa<FloatType>(type.getElementType())) return success();

    DenseFPElementsAttr attr;
    if (!matchPattern(const_op->getResult(0), m_Constant(&attr))) {
      const_op->emitError("Not a constant op.");
      return failure();
    }

    UniformQuantizedType quant_type = nullptr;

    const bool is_per_channel_quantization =
        enable_per_channel_quantization_ && quant_dim != -1;

    QuantizedType quant_type;
    DenseFPElementsAttr attr;
    if (!matchPattern(op->getResult(0), m_Constant(&attr))) return false;

    if (attr.size() < quant_specs_.minimum_elements_for_weights) {
      op->emitRemark("Quantization is skipped for ")
          << quantized_op->getName().getStringRef().str() << " because it has "

  }

  void rewrite(Operation* op, PatternRewriter& rewriter) const override {
    Operation* quantizable_op = *op->getUsers().begin();
    DenseFPElementsAttr attr;
    matchPattern(op->getResult(0), m_Constant(&attr));

    Method method = GetQuantizationMethodOrDefault(quantizable_op);
    const WeightOnlyPtq& weight_only_ptq = method.weight_only_ptq();

    Type weight_type;
    if (IsPerTensor(weight_only_ptq)) {

  LogicalResult matchAndRewrite(QuantizeOp op,
                                PatternRewriter& rewriter) const override {
    DenseFPElementsAttr attr;
    if (matchPattern(op.getInput(), m_Constant(&attr))) {
      auto qtype = op.getQtypeAttr();
      Attribute quantized_attr;
      if (legacy_float_scale_) {
        quantized_attr = quant::QuantizeLegacy(attr, qtype.getValue());
      } else {

    // Sink down constants (including quantized constant) into the functions.
    for (auto extern_value : region_extern_values) {
      if (!matchPattern(extern_value, m_Constant()) &&
          !llvm::dyn_cast_or_null<TFL::QConstOp>(
              extern_value.getDefiningOp())) {
        extern_values.insert(extern_value);
        continue;
      }

  auto new_value_type = mlir::cast<TensorType>(new_value.getType());

  // Get multiplier value in double.
  DenseFPElementsAttr multiplier_attr;
  if (!matchPattern(multiplier, m_Constant(&multiplier_attr)) ||
      mlir::cast<ShapedType>(multiplier_attr.getType()).getRank() > 1) {
    return {};
  }
  std::vector<double> multiplier_values;

    int weight_operand_idx = *operands.begin();

    Operation* weight_op = op.getOperand(weight_operand_idx).getDefiningOp();
    DenseFPElementsAttr attr;
    if (!matchPattern(weight_op->getResult(0), m_Constant(&attr))) {
      return failure();
    }

    // Get new shape.
    llvm::ArrayRef<int64_t> cur_shape = attr.getType().getShape();
    int cur_rank = cur_shape.size();

      ConversionPatternRewriter &rewriter) const override {
    if (!IsIllegalType(op.getOutput().getType())) return failure();
    TF::TensorProtoAttr tensor_proto_attr;
    if (!matchPattern(op.getOperation(), m_Constant(&tensor_proto_attr))) {
      return rewriter.notifyMatchFailure(op, "operand must be constant.");
    }
    auto dense_attr_or = GetDenseAttrFromTensorProtoAttr(
        tensor_proto_attr.getValue(),

      if (consumed_ops.contains(def_op)) continue;
      queue.push_back(def_op);
      consumed_ops.insert(def_op);
    }
  }
}

inline bool IsConstant(Operation *op) { return matchPattern(op, m_Constant()); }

bool AllOperationSafe(Block &block) {
  auto walk_result = block.walk([&](Operation *op) {
    // op has SideEffect.
    if (!isa_and_nonnull<TFL::WhileOp>(op) &&