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dnn(test): avoid calling of cv::setNumThreads() in tests directly

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It is not necessary by default.
Also it breaks test system command-line parameters: --perf_threads / --test_threads
This commit is contained in:
Alexander Alekhin 2017-12-27 14:56:29 +00:00
parent 5232ea1ee6
commit 9b131b5f7e
3 changed files with 2 additions and 10 deletions
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4
modules/dnn/perf/opencl/perf_convolution.cpp
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@ -77,8 +77,6 @@ OCL_PERF_TEST_P( ConvolutionPerfTest, perf, Combine(
std::vector<Mat*> inpBlobs(1, &inpBlob); std::vector<Mat*> inpBlobs(1, &inpBlob);
std::vector<Mat> outBlobs, internalBlobs; std::vector<Mat> outBlobs, internalBlobs;
cv::setNumThreads(cv::getNumberOfCPUs());
Ptr<Layer> layer = cv::dnn::LayerFactory::createLayerInstance("Convolution", lp); Ptr<Layer> layer = cv::dnn::LayerFactory::createLayerInstance("Convolution", lp);
std::vector<MatShape> inputShapes(1, shape(inpBlob)), outShapes, internals; std::vector<MatShape> inputShapes(1, shape(inpBlob)), outShapes, internals;
layer->getMemoryShapes(inputShapes, 0, outShapes, internals); layer->getMemoryShapes(inputShapes, 0, outShapes, internals);
@ -99,7 +97,7 @@ OCL_PERF_TEST_P( ConvolutionPerfTest, perf, Combine(
Mat inpBlob2D = inpBlob.reshape(1, outCn); Mat inpBlob2D = inpBlob.reshape(1, outCn);
Mat wgtBlob2D = wgtBlob.reshape(1, outCn*(inpCn/groups)); Mat wgtBlob2D = wgtBlob.reshape(1, outCn*(inpCn/groups));
Mat outBlob2D = outBlobs[0].reshape(1, outBlobs[0].size[0]); Mat outBlob2D = outBlobs[0].reshape(1, outBlobs[0].size[0]);
declare.in(inpBlob2D, wgtBlob2D, WARMUP_RNG).out(outBlob2D).tbb_threads(cv::getNumThreads()); declare.in(inpBlob2D, wgtBlob2D, WARMUP_RNG).out(outBlob2D);
// warmup // warmup
layer->forward(inpBlobs, outBlobs, internalBlobs); layer->forward(inpBlobs, outBlobs, internalBlobs);

4
modules/dnn/perf/perf_convolution.cpp
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@ -60,8 +60,6 @@ PERF_TEST_P( ConvolutionPerfTest, perf, Combine(
std::vector<Mat*> inpBlobs(1, &inpBlob); std::vector<Mat*> inpBlobs(1, &inpBlob);
std::vector<Mat> outBlobs, internalBlobs; std::vector<Mat> outBlobs, internalBlobs;
cv::setNumThreads(cv::getNumberOfCPUs());
Ptr<Layer> layer = cv::dnn::LayerFactory::createLayerInstance("Convolution", lp); Ptr<Layer> layer = cv::dnn::LayerFactory::createLayerInstance("Convolution", lp);
std::vector<MatShape> inputShapes(1, shape(inpBlob)), outShapes, internals; std::vector<MatShape> inputShapes(1, shape(inpBlob)), outShapes, internals;
layer->getMemoryShapes(inputShapes, 0, outShapes, internals); layer->getMemoryShapes(inputShapes, 0, outShapes, internals);
@ -81,7 +79,7 @@ PERF_TEST_P( ConvolutionPerfTest, perf, Combine(
Mat inpBlob2D = inpBlob.reshape(1, outCn); Mat inpBlob2D = inpBlob.reshape(1, outCn);
Mat wgtBlob2D = wgtBlob.reshape(1, outCn*(inpCn/groups)); Mat wgtBlob2D = wgtBlob.reshape(1, outCn*(inpCn/groups));
Mat outBlob2D = outBlobs[0].reshape(1, outBlobs[0].size[0]); Mat outBlob2D = outBlobs[0].reshape(1, outBlobs[0].size[0]);
declare.in(inpBlob2D, wgtBlob2D, WARMUP_RNG).out(outBlob2D).tbb_threads(cv::getNumThreads()); declare.in(inpBlob2D, wgtBlob2D, WARMUP_RNG).out(outBlob2D);
layer->forward(inpBlobs, outBlobs, internalBlobs); /// warmup layer->forward(inpBlobs, outBlobs, internalBlobs); /// warmup

4
modules/dnn/test/test_layers.cpp
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@ -107,8 +107,6 @@ void testLayerUsingCaffeModels(String basename, int targetId = DNN_TARGET_CPU,
String inpfile = (useCommonInputBlob) ? _tf("blob.npy") : _tf(basename + ".input.npy"); String inpfile = (useCommonInputBlob) ? _tf("blob.npy") : _tf(basename + ".input.npy");
String outfile = _tf(basename + ".npy"); String outfile = _tf(basename + ".npy");
cv::setNumThreads(cv::getNumberOfCPUs());
Net net = readNetFromCaffe(prototxt, (useCaffeModel) ? caffemodel : String()); Net net = readNetFromCaffe(prototxt, (useCaffeModel) ? caffemodel : String());
ASSERT_FALSE(net.empty()); ASSERT_FALSE(net.empty());
@ -536,8 +534,6 @@ void testLayerUsingDarknetModels(String basename, bool useDarknetModel = false,
String inpfile = (useCommonInputBlob) ? _tf("blob.npy") : _tf(basename + ".input.npy"); String inpfile = (useCommonInputBlob) ? _tf("blob.npy") : _tf(basename + ".input.npy");
String outfile = _tf(basename + ".npy"); String outfile = _tf(basename + ".npy");
cv::setNumThreads(cv::getNumberOfCPUs());
Net net = readNetFromDarknet(cfg, (useDarknetModel) ? weights : String()); Net net = readNetFromDarknet(cfg, (useDarknetModel) ? weights : String());
ASSERT_FALSE(net.empty()); ASSERT_FALSE(net.empty());