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Solve the bug of same shape broadcast with CUDA

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This commit is contained in:
wanli 2023-04-28 17:25:49 +08:00 committed by Wanli
parent 85b04f0b4d
commit 46991bcd62
3 changed files with 8 additions and 4 deletions
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5
modules/dnn/src/cuda/eltwise_ops.cu
View File

@ -150,7 +150,7 @@ void eltwise_op(const Stream& stream, TensorSpan<T> output, TensorView<T> x, Ten
*/
for (int r = 0; r < output.rank(); r++)
{
while (x.get_axis_size(r) == 1 && y.get_axis_size(r) == 1) {
while (x.rank() > r && y.rank() > r && x.get_axis_size(r) == 1 && y.get_axis_size(r) == 1) {
CV_Assert(output.get_axis_size(r) == 1);
x.squeeze(r);
@ -183,6 +183,9 @@ void eltwise_op(const Stream& stream, TensorSpan<T> output, TensorView<T> x, Ten
auto new_size = inShape1[i] * inShape1[j];
inShape1[i] = new_size;
inShape2[i] = new_size;
// outShape should be changed after merged
auto output_new_size = outShape[i] * outShape[j];
outShape[i] = output_new_size;
/* delete axis `j` */
inShape1.erase(std::begin(inShape1) + j);

2
modules/dnn/src/layers/nary_eltwise_layers.cpp
View File

@ -51,8 +51,6 @@ public:
WHERE,
} op;
// If the eltwise implementation is modified, you need to force enable the 'Layer_Test_Eltwise_bcast'
// test in the 'test_layers.cpp' file to make sure it all passes
NaryEltwiseLayerImpl(const LayerParams& params)
{
setParamsFrom(params);

5
modules/dnn/test/test_layers.cpp
View File

@ -1949,6 +1949,9 @@ public:
int backend = get<0>(backend_target);
int target = get<1>(backend_target);
if (backend == DNN_BACKEND_CUDA && dim > 4)
applyTestTag(CV_TEST_TAG_LONG);
vector<vector<int>> dim_shape_list;
get_all_arr(dim_shape_list, dim);
replace(dim_shape_list, 1, 3);
@ -2028,7 +2031,7 @@ private:
}
};
TEST_P(Layer_Test_Eltwise_bcast, DISABLED_brute_force)
TEST_P(Layer_Test_Eltwise_bcast, brute_force)
{
test_bcast();
}