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diff --git a/onert-micro/luci-interpreter/src/kernels/L2Pool2D.test.cpp b/onert-micro/luci-interpreter/src/kernels/L2Pool2D.test.cpp
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+++ b/onert-micro/luci-interpreter/src/kernels/L2Pool2D.test.cpp
@@ -0,0 +1,291 @@
+/*
+ * Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
+ * Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "kernels/L2Pool2D.h"
+#include "kernels/TestUtils.h"
+#include "luci_interpreter/TestMemoryManager.h"
+
+namespace luci_interpreter
+{
+namespace kernels
+{
+namespace
+{
+
+using namespace testing;
+
+class L2Pool2DTest : public ::testing::Test
+{
+protected:
+  void SetUp() override { _memory_manager = std::make_unique<TestMemoryManager>(); }
+
+  std::unique_ptr<IMemoryManager> _memory_manager;
+};
+
+TEST_F(L2Pool2DTest, FloatNone)
+{
+  Shape input_shape{1, 2, 4, 1};
+  std::vector<float> input_data{
+    0, 6, 2,  4, //
+    3, 2, 10, 7, //
+  };
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>(input_shape, input_data, _memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
+
+  Pool2DParams params{};
+  params.padding = Padding::VALID;
+  params.activation = Activation::NONE;
+  params.filter_height = 2;
+  params.filter_width = 2;
+  params.stride_height = 2;
+  params.stride_width = 2;
+
+  L2Pool2D kernel(&input_tensor, &output_tensor, params);
+  kernel.configure();
+  _memory_manager->allocate_memory(output_tensor);
+  kernel.execute();
+
+  std::vector<float> ref_output_data{3.5, 6.5};
+  EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(ref_output_data));
+  // TODO make a Shape checking of output_tensor.
+}
+
+TEST_F(L2Pool2DTest, FloatRelu)
+{
+  Shape input_shape{1, 2, 4, 1};
+  std::vector<float> input_data{
+    -1, -6, 2,  4, //
+    -3, -2, 10, 7, //
+  };
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>(input_shape, input_data, _memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
+
+  Pool2DParams params{};
+  params.padding = Padding::VALID;
+  params.activation = Activation::RELU;
+  params.filter_height = 2;
+  params.filter_width = 2;
+  params.stride_height = 2;
+  params.stride_width = 2;
+
+  L2Pool2D kernel(&input_tensor, &output_tensor, params);
+  kernel.configure();
+  _memory_manager->allocate_memory(output_tensor);
+  kernel.execute();
+
+  std::vector<float> ref_output_data{3.53553, 6.5};
+  EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(ref_output_data));
+  // TODO make a Shape checking of output_tensor.
+}
+
+TEST_F(L2Pool2DTest, FloatRelu1)
+{
+  Shape input_shape{1, 2, 4, 1};
+  std::vector<float> input_data{
+    -0.1, -0.6, 2,  4, //
+    -0.3, -0.2, 10, 7, //
+  };
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>(input_shape, input_data, _memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
+
+  Pool2DParams params{};
+  params.padding = Padding::VALID;
+  params.activation = Activation::RELU_N1_TO_1;
+  params.filter_height = 2;
+  params.filter_width = 2;
+  params.stride_height = 2;
+  params.stride_width = 2;
+
+  L2Pool2D kernel(&input_tensor, &output_tensor, params);
+  kernel.configure();
+  _memory_manager->allocate_memory(output_tensor);
+  kernel.execute();
+
+  std::vector<float> ref_output_data{0.353553, 1.0};
+  EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(ref_output_data));
+  // TODO make a Shape checking of output_tensor.
+}
+
+TEST_F(L2Pool2DTest, FloatRelu6)
+{
+  Shape input_shape{1, 2, 4, 1};
+  std::vector<float> input_data{
+    -0.1, -0.6, 2,  4, //
+    -0.3, -0.2, 10, 7, //
+  };
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>(input_shape, input_data, _memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
+
+  Pool2DParams params{};
+  params.padding = Padding::VALID;
+  params.activation = Activation::RELU6;
+  params.filter_height = 2;
+  params.filter_width = 2;
+  params.stride_height = 2;
+  params.stride_width = 2;
+
+  L2Pool2D kernel(&input_tensor, &output_tensor, params);
+  kernel.configure();
+  _memory_manager->allocate_memory(output_tensor);
+  kernel.execute();
+
+  std::vector<float> ref_output_data{0.353553, 6.0};
+  EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(ref_output_data));
+  // TODO make a Shape checking of output_tensor.
+}
+
+TEST_F(L2Pool2DTest, FloatPaddingSame)
+{
+  Shape input_shape{1, 2, 4, 1};
+  std::vector<float> input_data{
+    0, 6, 2,  4, //
+    3, 2, 10, 7, //
+  };
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>(input_shape, input_data, _memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
+
+  Pool2DParams params{};
+  params.padding = Padding::SAME;
+  params.activation = Activation::NONE;
+  params.filter_height = 2;
+  params.filter_width = 2;
+  params.stride_height = 2;
+  params.stride_width = 2;
+
+  L2Pool2D kernel(&input_tensor, &output_tensor, params);
+  kernel.configure();
+  _memory_manager->allocate_memory(output_tensor);
+  kernel.execute();
+
+  std::vector<float> ref_output_data{3.5, 6.5};
+  EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(ref_output_data));
+  // TODO make a Shape checking of output_tensor.
+}
+
+TEST_F(L2Pool2DTest, FloatPaddingSameStride)
+{
+  Shape input_shape{1, 2, 4, 1};
+  std::vector<float> input_data{
+    0, 6, 2,  4, //
+    3, 2, 10, 7, //
+  };
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>(input_shape, input_data, _memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
+
+  Pool2DParams params{};
+  params.padding = Padding::SAME;
+  params.activation = Activation::NONE;
+  params.filter_height = 2;
+  params.filter_width = 2;
+  params.stride_height = 1;
+  params.stride_width = 1;
+
+  L2Pool2D kernel(&input_tensor, &output_tensor, params);
+  kernel.configure();
+  _memory_manager->allocate_memory(output_tensor);
+  kernel.execute();
+
+  std::vector<float> ref_output_data{3.5, 6.0, 6.5, 5.70088, 2.54951, 7.2111, 8.63134, 7.0};
+  // NOTE with NEON+ruy, error is #1=-1.14441e-05, #6=-1.81198e-05
+  EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(ref_output_data, 1.0e-4f));
+  // TODO make a Shape checking of output_tensor.
+}
+
+TEST_F(L2Pool2DTest, FloatPaddingValidStride)
+{
+  Shape input_shape{1, 2, 4, 1};
+  std::vector<float> input_data{
+    0, 6, 2,  4, //
+    3, 2, 10, 7, //
+  };
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>(input_shape, input_data, _memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
+
+  Pool2DParams params{};
+  params.padding = Padding::VALID;
+  params.activation = Activation::NONE;
+  params.filter_height = 2;
+  params.filter_width = 2;
+  params.stride_height = 1;
+  params.stride_width = 1;
+
+  L2Pool2D kernel(&input_tensor, &output_tensor, params);
+  kernel.configure();
+  _memory_manager->allocate_memory(output_tensor);
+  kernel.execute();
+
+  std::vector<float> ref_output_data{3.5, 6.0, 6.5};
+  EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(ref_output_data));
+  // TODO make a Shape checking of output_tensor.
+}
+
+TEST_F(L2Pool2DTest, InvalidInputShape_NEG)
+{
+  Shape input_shape{1, 2, 4};
+  std::vector<float> input_data{
+    0, 6, 2,  4, //
+    3, 2, 10, 7, //
+  };
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>(input_shape, input_data, _memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
+
+  Pool2DParams params{};
+  params.padding = Padding::VALID;
+  params.activation = Activation::NONE;
+  params.filter_height = 2;
+  params.filter_width = 2;
+  params.stride_height = 1;
+  params.stride_width = 1;
+
+  L2Pool2D kernel(&input_tensor, &output_tensor, params);
+  EXPECT_ANY_THROW(kernel.configure());
+}
+
+TEST_F(L2Pool2DTest, InvalidInputOutputType_NEG)
+{
+  Shape input_shape{1, 2, 4};
+  std::vector<float> input_data{
+    0, 6, 2,  4, //
+    3, 2, 10, 7, //
+  };
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>(input_shape, input_data, _memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::U8);
+
+  Pool2DParams params{};
+  params.padding = Padding::VALID;
+  params.activation = Activation::NONE;
+  params.filter_height = 2;
+  params.filter_width = 2;
+  params.stride_height = 1;
+  params.stride_width = 1;
+
+  L2Pool2D kernel(&input_tensor, &output_tensor, params);
+  EXPECT_ANY_THROW(kernel.configure());
+}
+
+} // namespace
+} // namespace kernels
+} // namespace luci_interpreter