From d188319b82570aa3845f00b9dec07f5871b0d70d Mon Sep 17 00:00:00 2001
From: Abduragim Shtanchaev <44877829+Abdurrahheem@users.noreply.github.com>
Date: Fri, 22 Mar 2024 04:59:08 +0400
Subject: [PATCH] 0D test for Reshape layer  (#25206)

* reshape test for 0D

* fix comments according to PR
---
 modules/dnn/test/test_layers_1d.cpp | 26 ++++++++++++++++++++++++++
 1 file changed, 26 insertions(+)

diff --git a/modules/dnn/test/test_layers_1d.cpp b/modules/dnn/test/test_layers_1d.cpp
index c789d1fd10..114900abaf 100644
--- a/modules/dnn/test/test_layers_1d.cpp
+++ b/modules/dnn/test/test_layers_1d.cpp
@@ -245,4 +245,30 @@ INSTANTIATE_TEST_CASE_P(/*nothing*/, Layer_Elemwise_1d_Test, Combine(
 /*operation*/           Values("div", "prod", "max", "min", "sum")
 ));
 
+TEST(Layer_Reshape_Test, Accuracy)
+{
+    LayerParams lp;
+    lp.type = "Reshape";
+    lp.name = "ReshapeLayer";
+    lp.set("axis", 0); // Set axis to 0 to start reshaping from the first dimension
+    lp.set("num_axes", -1); // Set num_axes to -1 to indicate all following axes are included in the reshape
+    int newShape[] = {1};
+    lp.set("dim", DictValue::arrayInt(newShape, 1));
+
+    Ptr<ReshapeLayer> layer = ReshapeLayer::create(lp);
+
+    std::vector<int> input_shape = {0};
+
+    Mat input(0, input_shape.data(), CV_32F);
+    randn(input, 0.0, 1.0);
+    Mat output_ref(1, newShape, CV_32F, input.data);
+
+    std::vector<Mat> inputs{input};
+    std::vector<Mat> outputs;
+
+    runLayer(layer, inputs, outputs);
+    ASSERT_EQ(shape(output_ref), shape(outputs[0]));
+    normAssert(output_ref, outputs[0]);
+}
+
 }}