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fix incorrect steps and elemsize when dtype changes

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This commit is contained in:
fengyuentau 2024-02-06 16:27:25 +08:00
parent 8850a8219e
commit fcaa8ce3c2
1 changed files with 31 additions and 11 deletions
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42
modules/dnn/src/layers/nary_eltwise_layers.cpp
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@ -47,11 +47,12 @@ public:
std::vector<char*> ptrs; std::vector<char*> ptrs;
std::vector<std::vector<int>> shapes; std::vector<std::vector<int>> shapes;
std::vector<std::vector<size_t>> steps; std::vector<std::vector<size_t>> steps;
std::vector<size_t> elemsize;
NaryEltwiseHelper() { NaryEltwiseHelper() {
} }
void helperInit(const std::vector<Mat>& inputs, const std::vector<Mat>& outputs) void init(const std::vector<Mat>& inputs, const std::vector<Mat>& outputs)
{ {
narrays = 0; narrays = 0;
max_ndims = 0; max_ndims = 0;
@ -61,6 +62,7 @@ public:
ptrs.clear(); ptrs.clear();
shapes.clear(); shapes.clear();
steps.clear(); steps.clear();
elemsize.clear();
ninputs = inputs.size(); ninputs = inputs.size();
narrays = ninputs + 1; narrays = ninputs + 1;
@ -95,15 +97,33 @@ public:
} }
orig_shapes.push_back(_size); orig_shapes.push_back(_size);
orig_steps.push_back(_step); orig_steps.push_back(_step);
int esz = i == 0 ? outputs[0].elemSize() : inputs[i - 1].elemSize();
elemsize.push_back(esz);
} }
} }
// use FP32 as default type in finalized() function void reInit(size_t newElemSize) {
template <typename T> std::vector<size_t> newElemSizes(elemsize.size(), newElemSize);
reInit(newElemSizes);
}
void reInit(std::vector<size_t> newElemSizes) {
for (size_t array_index = 0; array_index < orig_steps.size(); array_index++) {
auto &step = orig_steps[array_index];
int esz = elemsize[array_index];
int new_esz = newElemSizes[array_index];
for (size_t step_index = 0; step_index < step.size(); step_index++) {
step[step_index] = static_cast<size_t>(step[step_index] / esz * new_esz);
}
elemsize[array_index] = newElemSizes[array_index];
}
prepare_for_broadcast_op();
}
bool prepare_for_broadcast_op() bool prepare_for_broadcast_op()
{ {
int i, j, k; int i, j, k;
std::vector<size_t> elemsize(this->all_ndims.size(), sizeof(T));
// step 1. // step 1.
// * make all inputs and the output max_ndims-dimensional. // * make all inputs and the output max_ndims-dimensional.
@ -313,8 +333,8 @@ public:
inputs_arr.getMatVector(inputs); inputs_arr.getMatVector(inputs);
outputs_arr.getMatVector(outputs); outputs_arr.getMatVector(outputs);
helper.helperInit(inputs, outputs); helper.init(inputs, outputs);
CV_Assert(helper.prepare_for_broadcast_op<float>()); CV_Assert(helper.prepare_for_broadcast_op());
} }
bool getMemoryShapes(const std::vector<MatShape> &inputs, bool getMemoryShapes(const std::vector<MatShape> &inputs,
@ -579,6 +599,7 @@ public:
if (inputs_arr.depth() == CV_16F) if (inputs_arr.depth() == CV_16F)
{ {
helper.reInit(sizeof(float));
forward_fallback(inputs_arr, outputs_arr, internals_arr); forward_fallback(inputs_arr, outputs_arr, internals_arr);
return; return;
} }
@ -733,14 +754,13 @@ public:
switch (type) switch (type)
{ {
case CV_8U: case CV_8U:
// TODO: integrate with type inference
helper.reInit(sizeof(uint8_t));
opDispatch<uint8_t>(std::forward<Args>(args)...); opDispatch<uint8_t>(std::forward<Args>(args)...);
helper.prepare_for_broadcast_op<uint8_t>();
/*
recompute broadcasted shapes
because default type is FP32 which is calculated in finalize() function
*/
break; break;
case CV_32S: case CV_32S:
// TODO: integrate with type inference
helper.reInit(sizeof(int32_t));
opDispatch<int32_t>(std::forward<Args>(args)...); opDispatch<int32_t>(std::forward<Args>(args)...);
break; break;
case CV_32F: case CV_32F: