// This is i8 values disguised as f32 (due to the upcast trick). Simply
      // cast them to i8.
      ElementsAttr filter_value = filter_constant_op.getValue();
      filter_i8_value_attr =
          mlir::cast<DenseFPElementsAttr>(filter_value)
              .mapValues(rewriter.getI8Type(), [](const APFloat& val) -> APInt {
                APSInt convertedInt(/*BitWidth=*/8, /*isUnsigned=*/false);
                bool ignored;

  TensorType scale_type = RankedTensorType::get({}, rewriter.getF32Type());
  TensorType zero_point_type = scale_type.clone(rewriter.getI32Type());
  scale = rewriter.create<TF::ConstOp>(
      loc, scale_type,
      DenseFPElementsAttr::get(scale_type,
                               {static_cast<float>(qtype.getScale())}));
  zero_point = rewriter.create<TF::ConstOp>(
      loc, zero_point_type,
      DenseIntElementsAttr::get(zero_point_type,

  mlir::ElementsAttr layer_stats = mlir::DenseFPElementsAttr::get(
      tensorflow::GetTypeFromTFTensorShape({2}, b.getF32Type()),
      {min_maxs[0], min_maxs[1]});
  mlir::ElementsAttr axis_stats;
  mlir::IntegerAttr axis;
  if (mins.size() > 1) {
    llvm::SmallVector<int64_t, 4> axis_stats_shape{
        static_cast<int64_t>(mins.size()), 2};
    axis_stats = mlir::DenseFPElementsAttr::get(