Blame view

3rdparty/opencv-4.5.4/modules/dnn/src/cuda4dnn/primitives/shuffle_channel.hpp 2.74 KB
f4334277   Hu Chunming   提交3rdparty
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
  // This file is part of OpenCV project.
  // It is subject to the license terms in the LICENSE file found in the top-level directory
  // of this distribution and at http://opencv.org/license.html.
  
  #ifndef OPENCV_DNN_SRC_CUDA4DNN_PRIMITIVES_SHUFFLE_CHANNEL_HPP
  #define OPENCV_DNN_SRC_CUDA4DNN_PRIMITIVES_SHUFFLE_CHANNEL_HPP
  
  #include "../../op_cuda.hpp"
  
  #include "../csl/stream.hpp"
  #include "../csl/tensor_ops.hpp"
  
  #include "../kernels/permute.hpp"
  
  #include <opencv2/core.hpp>
  
  #include <vector>
  #include <utility>
  
  namespace cv { namespace dnn { namespace cuda4dnn {
  
      template <class T>
      class ShuffleChannelOp final : public CUDABackendNode {
      public:
          using wrapper_type = GetCUDABackendWrapperType<T>;
  
          ShuffleChannelOp(csl::Stream stream_, std::size_t group_)
              : stream(std::move(stream_)), group{ group_ } { }
  
          void forward(
              const std::vector<cv::Ptr<BackendWrapper>>& inputs,
              const std::vector<cv::Ptr<BackendWrapper>>& outputs,
              csl::Workspace& workspace) override
          {
              CV_Assert(inputs.size() == 1 && outputs.size() == 1);
  
              auto input_wrapper = inputs[0].dynamicCast<wrapper_type>();
              auto input = input_wrapper->getView();
  
              auto output_wrapper = outputs[0].dynamicCast<wrapper_type>();
              auto output = output_wrapper->getSpan();
  
              if (group == 1) {
                  /* permute is redundant; check else branch to know why */
                  if (input.get() != output.get()) {
                      input.reshape_as(output);
                      csl::tensor_ops::copy(stream, output, input);
                  }
              } else {
                  const std::size_t permute_input_shape[] = {
                     input.get_axis_size(0),
                     group,
                     input.get_axis_size(1) / group,
                     input.get_axis_size(2) * input.get_axis_size(3)
                  };
  
                  constexpr std::size_t order[] = { 0, 2, 1, 3 };
  
                  const std::size_t permute_output_shape[] = {
                      permute_input_shape[order[0]],
                      permute_input_shape[order[1]],
                      permute_input_shape[order[2]],
                      permute_input_shape[order[3]],
                  };
  
                  input.reshape(std::begin(permute_input_shape), std::end(permute_input_shape));
                  output.reshape(std::begin(permute_output_shape), std::end(permute_output_shape));
                  kernels::permute(stream, output, input, { std::begin(order), std::end(order) });
              }
          }
  
      private:
          csl::Stream stream;
          std::size_t group;
      };
  
  }}} /* namespace cv::dnn::cuda4dnn */
  
  #endif /* OPENCV_DNN_SRC_CUDA4DNN_PRIMITIVES_SHUFFLE_CHANNEL_HPP */