From 22b1b1edacd0e7744ad3dc8884e03e14afd09358 Mon Sep 17 00:00:00 2001
From: Abduragim Shtanchaev <44877829+Abdurrahheem@users.noreply.github.com>
Date: Fri, 5 Apr 2024 16:55:23 +0400
Subject: [PATCH] Merge pull request #25071 from Abdurrahheem:ash/1D-scatter

1D Scatter Layer Test #25071

This PR introduces parametrized test for `Scatter` layer to test its functionality for 1D arrays


### 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
---
 modules/dnn/test/test_layers_1d.cpp | 50 +++++++++++++++++++++++++++++
 1 file changed, 50 insertions(+)

diff --git a/modules/dnn/test/test_layers_1d.cpp b/modules/dnn/test/test_layers_1d.cpp
index 3a0f9540d3..a79614c3f6 100644
--- a/modules/dnn/test/test_layers_1d.cpp
+++ b/modules/dnn/test/test_layers_1d.cpp
@@ -430,4 +430,54 @@ INSTANTIATE_TEST_CASE_P(/*nothing*/, Layer_Softmax_Test, Combine(
     testing::Values(0, 1)
 ));
 
+typedef testing::TestWithParam<tuple<std::vector<int>, std::string>> Layer_Scatter_Test;
+TEST_P(Layer_Scatter_Test, Accuracy1D) {
+
+    std::vector<int> input_shape = get<0>(GetParam());
+    std::string opr = get<1>(GetParam());
+
+    LayerParams lp;
+    lp.type = "Scatter";
+    lp.name = "addLayer";
+    lp.set("axis", 0);
+    lp.set("reduction", opr);
+    Ptr<ScatterLayer> layer = ScatterLayer::create(lp);
+
+    cv::Mat input = cv::Mat(input_shape.size(), input_shape.data(), CV_32F);
+    cv::randn(input, 0.0, 1.0);
+
+    int indices[] = {3, 2, 1, 0};
+    cv::Mat indices_mat(input_shape.size(), input_shape.data(), CV_32S, indices);
+    cv::Mat output(input_shape.size(), input_shape.data(), CV_32F, 0.0);
+
+    // create reference output
+    cv::Mat output_ref(input_shape, CV_32F, 0.0);
+    for (int i = 0; i < input_shape[0]; i++){
+        output_ref.at<float>(indices[i]) = input.at<float>(i);
+    }
+
+    if (opr == "add"){
+        output_ref += output;
+    } else if (opr == "mul"){
+        output_ref = output.mul(output_ref);
+    } else if (opr == "max"){
+        cv::max(output_ref, output, output_ref);
+    } else if (opr == "min"){
+        cv::min(output_ref, output, output_ref);
+    }
+
+    std::vector<Mat> inputs{output, indices_mat, input};
+    std::vector<Mat> outputs;
+    runLayer(layer, inputs, outputs);
+    ASSERT_EQ(outputs.size(), 1);
+    ASSERT_EQ(shape(output_ref), shape(outputs[0]));
+}
+INSTANTIATE_TEST_CASE_P(/*nothing*/, Layer_Scatter_Test, Combine(
+/*input blob shape*/    testing::Values(std::vector<int>{4},
+                                        std::vector<int>{1, 4}),
+/*reduce*/              Values("none", "add", "mul", "max", "min")
+));
+
+
+
 }}