}
    SmallVector<float> scale_factors;
    scale_factors.reserve(filter_scale_attr.size());
    for (auto value : filter_scale_attr.getValues<APFloat>()) {
      scale_factors.push_back(in_scale * value.convertToFloat() / out_scale);
    }
    rewriter.setInsertionPoint(scale_factor_op);
    const Location loc = scale_factor_op->getLoc();
    auto result_scale_op = rewriter.create<TF::ConstOp>(

  const llvm::fltSemantics& semantics = op.getMin().getSemantics();
  float rmin, rmax;
  if (&semantics == &APFloat::IEEEsingle()) {
    rmin = op.getMin().convertToFloat();
    rmax = op.getMax().convertToFloat();
  } else {
    rmin = op.getMin().convertToDouble();
    rmax = op.getMax().convertToDouble();
  }
  // Range boundaries must be valid.
  if (rmin >= rmax) {

  std::transform(real_values_attr.begin(), real_values_attr.end(),
                 std::back_inserter(real_values), [&](APFloat value) -> float {
                   return value.convertToFloat();
                 });
  const ShapedType new_dense_type = dyn_cast_or_null<ShapedType>(
      q_type.castExpressedToStorageType(real_values_attr.getType()));

    Value features = op.getFeatures();

    // Use ConstantLike for `alpha` to match the shape of feature.
    auto alphaVal = chlo::getConstantLike(
        rewriter, loc, op.getAlpha().convertToFloat(), features);
    Value zeroVal = chlo::getConstantLike(rewriter, loc, 0.0, features);

    Value leakyActivationVal =
        rewriter.create<mhlo::MulOp>(loc, features, alphaVal);