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DNN: add the Winograd fp16 support (#23654)

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* add Winograd FP16 implementation

* fixed dispatching of FP16 code paths in dnn; use dynamic dispatcher only when NEON_FP16 is enabled in the build and the feature is present in the host CPU at runtime

* fixed some warnings

* hopefully fixed winograd on x64 (and maybe other platforms)

---------

Co-authored-by: Vadim Pisarevsky <vadim.pisarevsky@gmail.com>
This commit is contained in:
zihaomu
2023-11-20 18:45:37 +08:00
committed by GitHub
parent a478757483
commit b913e73d04
22 changed files with 1262 additions and 556 deletions
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modules/dnn/test/test_torch_importer.cpp
+6 -1
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@@ -358,6 +358,8 @@ TEST_P(Test_Torch_nets, OpenFace_accuracy)
net.setPreferableBackend(backend);
net.setPreferableTarget(target);
if (target == DNN_TARGET_CPU_FP16)
net.enableWinograd(false);
Mat sample = imread(findDataFile("cv/shared/lena.png"));
Mat sampleF32(sample.size(), CV_32FC3);
@@ -542,6 +544,9 @@ TEST_P(Test_Torch_nets, FastNeuralStyle_accuracy)
Mat img = imread(findDataFile("dnn/googlenet_1.png"));
Mat inputBlob = blobFromImage(img, 1.0, Size(), Scalar(103.939, 116.779, 123.68), false);
if (target == DNN_TARGET_CPU_FP16)
net.enableWinograd(false);
net.setInput(inputBlob);
Mat out = net.forward();
@@ -570,7 +575,7 @@ TEST_P(Test_Torch_nets, FastNeuralStyle_accuracy)
}
else if (target == DNN_TARGET_CPU_FP16)
{
normAssert(out, refBlob, "", 0.64, 25);
normAssert(out, refBlob, "", 0.7, 25);
}
else
normAssert(out, refBlob, "", 0.5, 1.16);