Dec 11, 2025 · Dec 12, 2025 · Dec 12, 2025 · Dec 15, 2025 · Dec 15, 2025 · Dec 18, 2025
diff --git a/modules/dnn/src/layers/randomnormallike_layer.cpp b/modules/dnn/src/layers/randomnormallike_layer.cpp

        Mat& out = outputs[0];

        RNG rng = hasSeed ? RNG(seed) : theRNG();
        RNG seededRng;
        RNG* rng = &theRNG();
        if (hasSeed)
        {
            seededRng = RNG(static_cast<uint64>(seed));
            rng = &seededRng;
        }

        if (out.depth() == CV_32F || out.depth() == CV_64F || out.depth() == CV_16F)
        {
            rng.fill(out, RNG::NORMAL, mean, scale);
            rng->fill(out, RNG::NORMAL, mean, scale);
        }
        else
        {
            Mat tmp(out.size.dims(), out.size.p, CV_32F);
            rng.fill(tmp, RNG::NORMAL, mean, scale);
            rng->fill(tmp, RNG::NORMAL, mean, scale);
            tmp.convertTo(out, out.type());
        }
    }
Original file line number	Diff line number	Diff line change
Expand Up		@@ -67,16 +67,22 @@ class RandomNormalLikeLayerImpl CV_FINAL : public Layer

		Mat& out = outputs[0];

		RNG rng = hasSeed ? RNG(seed) : theRNG();
		RNG seededRng;
		RNG* rng = &theRNG();
		if (hasSeed)
		{
		seededRng = RNG(static_cast<uint64>(seed));
Copy link Contributor vpisarevDec 18, 2025 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. I don't quite like that seed is rounded to unsigned integer before passing to RNG. That is, if I pass seed 1.1 and then 1.2, I will get the same results even though the seed has different values. Can we use the following approach instead? `Cvt64suf u;u.f = seed;seededRng = RNG(u.u);rng = &seededRng;`
		rng = &seededRng;
		}
Comment on lines +72 to +76 Copy link Contributor asmorkalovDec 18, 2025 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. It forces seed on each forward call. it means that forward will return the same sequence each time. Is it expected behaviour?

		if (out.depth() == CV_32F \|\| out.depth() == CV_64F \|\| out.depth() == CV_16F)
		{
		rng.fill(out, RNG::NORMAL, mean, scale);
		rng->fill(out, RNG::NORMAL, mean, scale);
		}
		else
		{
		Mat tmp(out.size.dims(), out.size.p, CV_32F);
		rng.fill(tmp, RNG::NORMAL, mean, scale);
		rng->fill(tmp, RNG::NORMAL, mean, scale);
		tmp.convertTo(out, out.type());
		}
		}
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