diff --git a/modules/dnn/test/test_common.impl.hpp b/modules/dnn/test/test_common.impl.hpp
index 70e1505f69c1..0dddc850f4c0 100644
--- a/modules/dnn/test/test_common.impl.hpp
+++ b/modules/dnn/test/test_common.impl.hpp
@@ -79,6 +79,7 @@ void normAssert(
         cv::InputArray ref, cv::InputArray test, const char *comment /*= ""*/,
         double l1 /*= 0.00001*/, double lInf /*= 0.0001*/)
 {
+    std::cout << "ref size: " << ref.size() << std::endl;
     double normL1 = cvtest::norm(ref, test, cv::NORM_L1) / ref.getMat().total();
     EXPECT_LE(normL1, l1) << comment << "  |ref| = " << cvtest::norm(ref, cv::NORM_INF);
 
diff --git a/modules/dnn/test/test_layers_1d.cpp b/modules/dnn/test/test_layers_1d.cpp
index ffe18d04fa3c..070650b87d4e 100644
--- a/modules/dnn/test/test_layers_1d.cpp
+++ b/modules/dnn/test/test_layers_1d.cpp
@@ -537,11 +537,11 @@ TEST_P(Layer_Padding_Test, Accuracy_01D){
     if (input_shape.size() == 0 || input_shape.size() == 1){
         std::cout << "shape output_ref: " << shape(output_ref) << std::endl;
         std::cout << "total: " << output_ref.total() << std::endl;
-        // output_ref = output_ref.reshape(1, {3});
+        std::cout << "output_ref: " << output_ref.size() << std::endl;
+        output_ref = output_ref.reshape(1, (int)output_ref.total());
         output_ref.dims = 1;
+        std::cout << "output_ref: " << output_ref.size() << std::endl;
     }
-    std::cout << "input: " << input << std::endl;
-    std::cout << "output_ref: " << output_ref << std::endl;
     std::cout << "shape output_ref: " << shape(output_ref) << std::endl;
 
     std::vector<Mat> inputs{input};
@@ -550,6 +550,8 @@ TEST_P(Layer_Padding_Test, Accuracy_01D){
     runLayer(layer, inputs, outputs);
     std::cout << "output[0]: " << outputs[0] << std::endl;
     std::cout << "output[0] shape: " << shape(outputs[0]) << std::endl;
+    std::cout << "output_ref: " << output_ref.size() << std::endl;
+    std::cout << "output[0]: " << outputs[0].size() << std::endl;
     ASSERT_EQ(outputs.size(), 1);
     ASSERT_EQ(shape(output_ref), shape(outputs[0]));
     normAssert(output_ref, outputs[0]);
diff --git a/modules/ts/src/ts_func.cpp b/modules/ts/src/ts_func.cpp
index ad320e98bb9d..90eff960fc8b 100644
--- a/modules/ts/src/ts_func.cpp
+++ b/modules/ts/src/ts_func.cpp
@@ -1465,6 +1465,8 @@ double norm(InputArray _src, int normType, InputArray _mask)
 double norm(InputArray _src1, InputArray _src2, int normType, InputArray _mask)
 {
     Mat src1 = _src1.getMat(), src2 = _src2.getMat(), mask = _mask.getMat();
+    std::cout << "scr1 size: " << src1.size << std::endl;
+    std::cout << "scr2 size: " << src2.size << std::endl;
     if( src1.depth() == CV_16F || src1.depth() == CV_16BF )
     {
         Mat src1_32f, src2_32f;
@@ -1502,6 +1504,8 @@ double norm(InputArray _src1, InputArray _src2, int normType, InputArray _mask)
     normType = normType == NORM_L2SQR ? NORM_L2 : normType;
 
     CV_CheckTypeEQ(src1.type(), src2.type(), "");
+    std::cout << "scr1 size: " << src1.size << std::endl;
+    std::cout << "scr2 size: " << src2.size << std::endl;
     CV_Assert(src1.size == src2.size);
     CV_Assert( mask.empty() || (src1.size == mask.size && mask.type() == CV_8U) );
     CV_Assert( normType == NORM_INF || normType == NORM_L1 || normType == NORM_L2 );