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multi-threaded scatter and refactor perf

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This commit is contained in:
fengyuentau
2024-01-05 17:24:09 +08:00
parent a8ec658611
commit 63cde0b90d
2 changed files with 111 additions and 112 deletions
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modules/dnn/perf/perf_layer.cpp
+59 -64
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@@ -258,76 +258,71 @@ PERF_TEST_P_(Layer_Slice, FastNeuralStyle_eccv16)
test_slice<4>(inputShape, begin, end);
}
struct Layer_Scatter : public TestBaseWithParam<tuple<Backend, Target> >
{
void test_layer(const std::vector<int>& shape, const String reduction = "none", int axis = 0)
using Layer_Scatter = TestBaseWithParam<tuple<std::vector<int>, std::string, int, tuple<Backend, Target>>>;
PERF_TEST_P_(Layer_Scatter, scatter) {
std::vector<int> shape = get<0>(GetParam());
std::string reduction = get<1>(GetParam());
int axis = get<2>(GetParam());
int backend_id = get<0>(get<3>(GetParam()));
int target_id = get<1>(get<3>(GetParam()));
Mat data(shape, CV_32FC1);
Mat indices(shape, CV_32FC1);
Mat updates(shape, CV_32FC1);
randn(data, 0.f, 1.f);
randu(indices, 0, shape[axis]);
randn(updates, 0.f, 1.f);
indices.convertTo(indices, CV_32SC1, 1, -1);
Net net;
LayerParams lp;
lp.type = "Scatter";
lp.name = "testLayer";
lp.set("reduction", reduction);
lp.set("axis", axis);
int id = net.addLayerToPrev(lp.name, lp.type, lp);
net.connect(0, 0, id, 0);
net.connect(0, 1, id, 1);
net.connect(0, 2, id, 2);
// warmup
{
int backendId = get<0>(GetParam());
int targetId = get<1>(GetParam());
std::vector<String> input_names{"data", "indices", "updates"};
net.setInputsNames(input_names);
net.setInput(data, input_names[0]);
net.setInput(indices, input_names[1]);
net.setInput(updates, input_names[2]);
Mat data(shape, CV_32FC1);
Mat indices(shape, CV_32FC1);
Mat updates(shape, CV_32FC1);
Scalar mean = 0.f;
Scalar std = 1.f;
randn(data, mean, std);
randu(indices, 0, shape[axis]);
randn(updates, mean, std);
indices.convertTo(indices, CV_32SC1, 1, -1);
Net net;
LayerParams lp;
lp.type = "Scatter";
lp.name = "testLayer";
lp.set("reduction", reduction);
lp.set("axis", axis);
int id = net.addLayerToPrev(lp.name, lp.type, lp);
net.connect(0, 0, id, 0);
net.connect(0, 1, id, 1);
net.connect(0, 2, id, 2);
// warmup
{
std::vector<String> inpNames(3);
inpNames[0] = "data";
inpNames[1] = "indices";
inpNames[2] = "updates";
net.setInputsNames(inpNames);
net.setInput(data, inpNames[0]);
net.setInput(indices, inpNames[1]);
net.setInput(updates, inpNames[2]);
net.setPreferableBackend(backendId);
net.setPreferableTarget(targetId);
Mat out = net.forward();
}
TEST_CYCLE()
{
Mat res = net.forward();
}
SANITY_CHECK_NOTHING();
net.setPreferableBackend(backend_id);
net.setPreferableTarget(target_id);
Mat out = net.forward();
}
int N = 8;
int C = 256;
int H = 128;
int W = 100;
};
// perf
TEST_CYCLE()
{
Mat res = net.forward();
}
PERF_TEST_P_(Layer_Scatter, DISABLED_Scatter)
{
test_layer({N, C, H, W});
SANITY_CHECK_NOTHING();
}
PERF_TEST_P_(Layer_Scatter, DISABLED_Scatter_add)
{
test_layer({N, C, H, W}, "add");
}
INSTANTIATE_TEST_CASE_P(/**/, Layer_Scatter, Combine(
Values(std::vector<int>{2, 128, 64, 50}),
Values(std::string("none"), std::string("add")),
Values(0), // use Values(0, 1, 2, 3) for more details
dnnBackendsAndTargets(/* withInferenceEngine= */ false,
/* withHalide= */ false,
/* withCpuOCV= */ true,
/* withVkCom= */ false,
/* withCUDA= */ false,
/* withNgraph= */ false,
/* withWebnn= */ false,
/* withCann= */ false) // only test on CPU
));
struct Layer_ScatterND : public TestBaseWithParam<tuple<Backend, Target> >
{
@@ -800,7 +795,7 @@ INSTANTIATE_TEST_CASE_P(/**/, Layer_NaryEltwise, testing::Values(std::make_tuple
#ifdef HAVE_CUDA
INSTANTIATE_TEST_CASE_P(CUDA, Layer_NaryEltwise, testing::Values(std::make_tuple(DNN_BACKEND_CUDA, DNN_TARGET_CUDA)));
#endif
INSTANTIATE_TEST_CASE_P(/**/, Layer_Scatter, testing::Values(std::make_tuple(DNN_BACKEND_OPENCV, DNN_TARGET_CPU)));
// INSTANTIATE_TEST_CASE_P(/**/, Layer_Scatter, testing::Values(std::make_tuple(DNN_BACKEND_OPENCV, DNN_TARGET_CPU)));
INSTANTIATE_TEST_CASE_P(/**/, Layer_ScatterND, testing::Values(std::make_tuple(DNN_BACKEND_OPENCV, DNN_TARGET_CPU)));
INSTANTIATE_TEST_CASE_P(/**/, Layer_LayerNorm, testing::Values(std::make_tuple(DNN_BACKEND_OPENCV, DNN_TARGET_CPU)));
INSTANTIATE_TEST_CASE_P(/**/, Layer_LayerNormExpanded, testing::Values(std::make_tuple(DNN_BACKEND_OPENCV, DNN_TARGET_CPU)));