diff --git a/src/tim/vx/ops/localresponsenormalization_test.cc b/src/tim/vx/ops/localresponsenormalization_test.cc
index 84f0ff6..16b7ff2 100644
--- a/src/tim/vx/ops/localresponsenormalization_test.cc
+++ b/src/tim/vx/ops/localresponsenormalization_test.cc
@@ -47,16 +47,57 @@ TEST(localresponsenormalization, axis_0_shape_6_1_1_1_float) {
   EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(),
                                              in_data.size() * sizeof(float)));
 
-  int radius = 5;
+  int radius = 2;
+  int size = radius * 2;
   float alpha = 4.0, beta = 0.5, bias = 9.0;
   auto op = graph->CreateOperation<tim::vx::ops::LocalResponseNormalization>(
-      radius, alpha, beta, bias, 0);
+      size, alpha, beta, bias, 0);
   (*op).BindInputs({input_tensor}).BindOutputs({output_tensor});
 
   EXPECT_TRUE(graph->Compile());
   EXPECT_TRUE(graph->Run());
 
-  std::vector<float> output(18);
+  std::vector<float> output(golden.size());
+  EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+  EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
+}
+
+TEST(localresponsenormalization, axis_1_shape_2_6_float) {
+  auto ctx = tim::vx::Context::Create();
+  auto graph = ctx->CreateGraph();
+
+  tim::vx::ShapeType io_shape({2, 6});
+  tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32, io_shape,
+                                 tim::vx::TensorAttribute::INPUT);
+  tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32, io_shape,
+                                  tim::vx::TensorAttribute::OUTPUT);
+
+  auto input_tensor = graph->CreateTensor(input_spec);
+  auto output_tensor = graph->CreateTensor(output_spec);
+
+  std::vector<float> in_data = {-1.100000023841858f, -1.100000023841858f, 0.6000000238418579f,
+                                0.6000000238418579f, 0.699999988079071f, 0.699999988079071f,
+                                1.2000000476837158f, 1.2000000476837158f, -0.699999988079071f,
+                                -0.699999988079071f, 0.10000000149011612f, 0.10000000149011612f};
+  std::vector<float> golden = {-0.26492568850517273f, -0.26492568850517273f, 0.12510864436626434f,
+                                0.12510864436626434f, 0.14011213183403015f, 0.14011213183403015f,
+                                0.267261266708374f, 0.267261266708374f, -0.16178755462169647f,
+                                -0.16178755462169647f, 0.024426599964499474f, 0.024426599964499474f};
+
+  EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(),
+                                             in_data.size() * sizeof(float)));
+
+  int radius = 2;
+  int size = radius * 2;
+  float alpha = 4.0, beta = 0.5, bias = 9.0;
+  auto op = graph->CreateOperation<tim::vx::ops::LocalResponseNormalization>(
+      size, alpha, beta, bias, 1);
+  (*op).BindInputs({input_tensor}).BindOutputs({output_tensor});
+
+  EXPECT_TRUE(graph->Compile());
+  EXPECT_TRUE(graph->Run());
+
+  std::vector<float> output(golden.size());
   EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
   EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
 }
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