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opencv/modules/dnn/perf
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Yuantao Feng 23b244d3a3
Merge pull request #25881 from fengyuentau:dnn/cpu/optimize_activations_with_v_exp 
dnn: optimize activations with v_exp #25881

Merge with https://github.com/opencv/opencv_extra/pull/1191.

This PR optimizes the following activations:

- [x] Swish
- [x] Mish
- [x] Elu
- [x] Celu
- [x] Selu
- [x] HardSwish

### Performance (Updated on 2024-07-18)

#### AmLogic A311D2 (ARM Cortex A73 + A53)

```
Geometric mean (ms)

            Name of Test              activations activations.patch activations.patch
                                                                              vs
                                                                         activations
                                                                          (x-factor)
Celu::Layer_Elementwise::OCV/CPU        115.859          27.930              4.15
Elu::Layer_Elementwise::OCV/CPU          27.846          27.003              1.03
Gelu::Layer_Elementwise::OCV/CPU         0.657           0.602               1.09
HardSwish::Layer_Elementwise::OCV/CPU    31.885          6.781               4.70
Mish::Layer_Elementwise::OCV/CPU         35.729          32.089              1.11
Selu::Layer_Elementwise::OCV/CPU         61.955          27.850              2.22
Swish::Layer_Elementwise::OCV/CPU        30.819          26.688              1.15
```

#### Apple M1

```
Geometric mean (ms)

               Name of Test                activations activations.patch activations.patch
                                                                                   vs
                                                                              activations
                                                                               (x-factor)
Celu::Layer_Elementwise::OCV/CPU              16.184          2.118               7.64
Celu::Layer_Elementwise::OCV/CPU_FP16         16.280          2.123               7.67
Elu::Layer_Elementwise::OCV/CPU               9.123           1.878               4.86
Elu::Layer_Elementwise::OCV/CPU_FP16          9.085           1.897               4.79
Gelu::Layer_Elementwise::OCV/CPU              0.089           0.081               1.11
Gelu::Layer_Elementwise::OCV/CPU_FP16         0.086           0.074               1.17
HardSwish::Layer_Elementwise::OCV/CPU         1.560           1.555               1.00
HardSwish::Layer_Elementwise::OCV/CPU_FP16    1.536           1.523               1.01
Mish::Layer_Elementwise::OCV/CPU              6.077           2.476               2.45
Mish::Layer_Elementwise::OCV/CPU_FP16         5.990           2.496               2.40
Selu::Layer_Elementwise::OCV/CPU              11.351          1.976               5.74
Selu::Layer_Elementwise::OCV/CPU_FP16         11.533          1.985               5.81
Swish::Layer_Elementwise::OCV/CPU             4.687           1.890               2.48
Swish::Layer_Elementwise::OCV/CPU_FP16        4.715           1.873               2.52
```

#### Intel i7-12700K

```
Geometric mean (ms)

            Name of Test              activations activations.patch activations.patch
                                                                    vs
                                                               activations
                                                                (x-factor)
Celu::Layer_Elementwise::OCV/CPU        17.106       3.560         4.81
Elu::Layer_Elementwise::OCV/CPU          5.064       3.478         1.46
Gelu::Layer_Elementwise::OCV/CPU         0.036       0.035         1.04
HardSwish::Layer_Elementwise::OCV/CPU    2.914       2.893         1.01
Mish::Layer_Elementwise::OCV/CPU         3.820       3.529         1.08
Selu::Layer_Elementwise::OCV/CPU        10.799       3.593         3.01
Swish::Layer_Elementwise::OCV/CPU        3.651       3.473         1.05
```

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-07-19 16:03:19 +03:00
..
perf_caffe.cpp Merge pull request #24120 from dkurt:actualize_dnn_links 2023-08-16 15:46:11 +03:00
perf_common.cpp cmake: fix build of dnn tests with shared common code 2019-03-31 08:52:25 +00:00
perf_convolution1d.cpp Merge pull request #18783 from sl-sergei:fix_conv1d 2020-11-13 22:22:10 +00:00
perf_convolution3d.cpp Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2020-11-13 22:29:14 +00:00
perf_convolution.cpp dnn(test): skip very long debug tests, reduce test time 2023-12-25 08:44:06 +00:00
perf_einsum.cpp Merge pull request #24509 from Abdurrahheem:ash/dev_einsum_fast_gemm 2023-11-16 16:20:17 +03:00
perf_gemm.cpp Merge pull request #24694 from fengyuentau:matmul_refactor 2023-12-19 19:36:41 +03:00
perf_layer.cpp Merge pull request #25881 from fengyuentau:dnn/cpu/optimize_activations_with_v_exp 2024-07-19 16:03:19 +03:00
perf_main.cpp Merge pull request #11897 from Jakub-Golinowski:hpx_backend 2018-08-31 16:23:26 +03:00
perf_net.cpp Fix proto and weights mess in dnn performance tests. 2024-02-07 09:16:09 +03:00
perf_precomp.hpp dnn(perf): fix and merge Convolution tests 2018-08-31 15:02:19 +03:00
perf_recurrent.cpp Merge pull request #20658 from smbz:lstm_optimisation 2021-11-29 21:43:00 +00:00