From 869016d8b159bef6bddbe778dafa1a6bb8c65d3b Mon Sep 17 00:00:00 2001
From: Abduragim Shtanchaev <44877829+Abdurrahheem@users.noreply.github.com>
Date: Mon, 15 Apr 2024 09:15:36 +0300
Subject: [PATCH] Merge pull request #25208 from
 Abdurrahheem:ash/0D-fullyConnected-test

Fully connected 0D test. #25208

This PR introduces parametrized `0/1D` input support test for `Fullyconnected` layer.

### 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
---
 .../dnn/src/layers/fully_connected_layer.cpp  |  5 +--
 modules/dnn/test/test_layers_1d.cpp           | 36 +++++++++++++++++++
 2 files changed, 39 insertions(+), 2 deletions(-)

diff --git a/modules/dnn/src/layers/fully_connected_layer.cpp b/modules/dnn/src/layers/fully_connected_layer.cpp
index e3d4a111c8..ba741aa662 100644
--- a/modules/dnn/src/layers/fully_connected_layer.cpp
+++ b/modules/dnn/src/layers/fully_connected_layer.cpp
@@ -167,10 +167,11 @@ public:
             cAxis = normalize_axis(axis, inputsTmp[0]);
         }
 
-        MatShape outShape(cAxis + 1);
+        MatShape outShape((!inputs[0].empty()) ? cAxis + 1 : cAxis);
         for (int i = 0; i < cAxis; ++i)
             outShape[i] = inputsTmp[0][i];
-        outShape.back() = numOutput;
+        if (!inputs[0].empty())
+            outShape.back() = numOutput;
 
         outputs.resize(1, outShape);
         return false;
diff --git a/modules/dnn/test/test_layers_1d.cpp b/modules/dnn/test/test_layers_1d.cpp
index 4dbc8ba696..4e5e82e031 100644
--- a/modules/dnn/test/test_layers_1d.cpp
+++ b/modules/dnn/test/test_layers_1d.cpp
@@ -567,4 +567,40 @@ INSTANTIATE_TEST_CASE_P(/*nothing*/, Layer_Slice_Test,
                 std::vector<int>({1, 4})
 ));
 
+typedef testing::TestWithParam<tuple<std::vector<int>>> Layer_FullyConnected_Test;
+TEST_P(Layer_FullyConnected_Test, Accuracy_01D)
+{
+    LayerParams lp;
+    lp.type = "InnerProduct";
+    lp.name = "InnerProductLayer";
+    lp.set("num_output", 1);
+    lp.set("bias_term", false);
+    lp.set("axis", 0);
+
+    std::vector<int> input_shape = get<0>(GetParam());
+
+    RNG& rng = TS::ptr()->get_rng();
+    float inp_value = rng.uniform(0.0, 10.0);
+    Mat weights(std::vector<int>{total(input_shape), 1}, CV_32F, inp_value);
+    lp.blobs.push_back(weights);
+
+    Ptr<Layer> layer = LayerFactory::createLayerInstance("InnerProduct", lp);
+
+    Mat input(input_shape.size(), input_shape.data(), CV_32F);
+    randn(input, 0, 1);
+    Mat output_ref = input.reshape(1, 1) * weights;
+    output_ref.dims = 1;
+
+    std::vector<Mat> inputs{input};
+    std::vector<Mat> outputs;
+    runLayer(layer, inputs, outputs);
+    normAssert(output_ref, outputs[0]);
+}
+INSTANTIATE_TEST_CASE_P(/*nothting*/, Layer_FullyConnected_Test,
+                        testing::Values(
+                            std::vector<int>({}),
+                            std::vector<int>({1}),
+                            std::vector<int>({4})
+));
+
 }}