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https://github.com/opencv/opencv.git
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d85e67d3ec
support eltwise sum with different number of input channels in CUDA backend * add shortcut primitive * add offsets in shortcut kernel * skip tests involving more than two inputs * remove redundant modulus operation * support multiple inputs * remove whole file indentation * skip acc in0 trunc test if weighted * use shortcut iff channels are unequal
77 lines
2.3 KiB
C++
77 lines
2.3 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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#ifndef OPENCV_DNN_SRC_CUDA4DNN_PRIMITIVES_SHORTCUT_HPP
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#define OPENCV_DNN_SRC_CUDA4DNN_PRIMITIVES_SHORTCUT_HPP
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#include "../../op_cuda.hpp"
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#include "../csl/stream.hpp"
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#include "../csl/tensor.hpp"
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#include "../csl/tensor_ops.hpp"
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#include "../kernels/shortcut.hpp"
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#include <opencv2/core.hpp>
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#include <utility>
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namespace cv { namespace dnn { namespace cuda4dnn {
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template <class T>
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class ShortcutOp final : public CUDABackendNode {
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public:
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using wrapper_type = GetCUDABackendWrapperType<T>;
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ShortcutOp(csl::Stream stream_) : stream(std::move(stream_)) { }
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void forward(
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const std::vector<cv::Ptr<BackendWrapper>>& inputs,
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const std::vector<cv::Ptr<BackendWrapper>>& outputs,
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csl::Workspace& workspace) override
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{
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CV_Assert(outputs.size() == 1);
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auto output_wrapper = outputs[0].dynamicCast<wrapper_type>();
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auto output = output_wrapper->getSpan();
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auto input_wrapper = inputs[0].dynamicCast<wrapper_type>();
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auto input = input_wrapper->getView();
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/* output shape is determined by the input shape */
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CV_Assert(is_shape_same(output, input));
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for (int i = 1; i < inputs.size(); i++)
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{
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auto from_wrapper = inputs[i].dynamicCast<wrapper_type>();
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auto from = from_wrapper->getView();
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CV_Assert(output.rank() == from.rank());
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for (int i = 0; i < output.rank(); i++) {
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if (i != 1) {
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CV_Assert(from.get_axis_size(i) == output.get_axis_size(i));
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}
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}
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if (i == 1)
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{
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/* optimized path for first two inputs */
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kernels::input_shortcut<T>(stream, output, input, from);
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}
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else
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{
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kernels::input_shortcut<T>(stream, output, output, from);
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}
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}
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}
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private:
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csl::Stream stream;
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};
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}}} /* namespace cv::dnn::cuda4dnn */
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#endif /* OPENCV_DNN_SRC_CUDA4DNN_PRIMITIVES_SHORTCUT_HPP */
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