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Merge pull request #22739 from zihaomu:remove_never_used_code

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Alexander Alekhin 2022-11-03 04:41:56 +00:00
commit 91624e87ab
1 changed files with 0 additions and 33 deletions
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33
modules/dnn/src/onnx/onnx_importer.cpp
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@ -2053,39 +2053,6 @@ void ONNXImporter::parseMatMul(LayerParams& layerParams, const opencv_onnx::Node
addLayer(layerParams, node_proto); addLayer(layerParams, node_proto);
} }
void findBroadAxis(const MatShape& broadShape, const MatShape& outShape, size_t& axis, int& broadAxis)
{
// Currently, this function can only complete 1-dimensional expansion of broadShape.
// If there are two dimensions in broadShape that need to be expended, it will fail.
const size_t diff = outShape.size() - broadShape.size();
// find the first non-one element of the broadcasting shape
axis = 0;
for (; axis < broadShape.size() && broadShape[axis] == 1; ++axis) {}
// find the last non-one element of the broadcasting shape
size_t endAxis = broadShape.size();
for (; endAxis > axis && broadShape[endAxis - 1] == 1; --endAxis) {}
// find one between axis and endAxis - as it needs to be broadcasted,
// dimensions from the left of axis and from the right of endAxis will be handled by Scale layer
broadAxis = -1;
for (size_t i = axis; i < endAxis; ++i)
{
size_t outAxis = i + diff;
if (outShape[outAxis] == broadShape[i])
{
continue;
}
// ensure we need to broadcast only 1 dimension in the middle
CV_Assert(broadShape[i] == 1 && broadAxis == -1);
broadAxis = static_cast<int>(outAxis);
}
axis += diff;
}
void ONNXImporter::parseConv(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto_) void ONNXImporter::parseConv(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto_)
{ {
opencv_onnx::NodeProto node_proto = node_proto_; opencv_onnx::NodeProto node_proto = node_proto_;