1 files changed, 0 insertions, 125 deletions
diff --git a/compiler/luci-interpreter/src/kernels/MaxPool2D.test.cpp b/compiler/luci-interpreter/src/kernels/MaxPool2D.test.cpp
deleted file mode 100644
index 1d7fe06c4..000000000
--- a/compiler/luci-interpreter/src/kernels/MaxPool2D.test.cpp
+++ /dev/null
@@ -1,125 +0,0 @@
-/*
- * Copyright (c) 2020 Samsung Electronics Co., Ltd. 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/MaxPool2D.h"
-#include "kernels/TestUtils.h"
-
-namespace luci_interpreter
-{
-namespace kernels
-{
-namespace
-{
-
-using namespace testing;
-
-TEST(MaxPool2DTest, Float)
-{
-  Shape input_shape{1, 3, 5, 1};
-  std::vector<float> input_data{
-      1,  -1, 0,  -2, 2,  //
-      -7, -6, -5, -4, -3, //
-      5,  4,  3,  6,  7,  //
-  };
-  Tensor input_tensor = makeInputTensor<DataType::FLOAT32>(input_shape, input_data);
-  Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
-
-  Pool2DParams params{};
-  params.padding = Padding::VALID;
-  params.filter_height = 2;
-  params.filter_width = 3;
-  params.stride_height = 1;
-  params.stride_width = 2;
-  params.activation = Activation::RELU6;
-
-  MaxPool2D kernel(&input_tensor, &output_tensor, params);
-  kernel.configure();
-  kernel.execute();
-
-  std::vector<float> ref_output_data{
-      1, 2, //
-      5, 6, //
-  };
-  std::initializer_list<int32_t> ref_output_shape{1, 2, 2, 1};
-  EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(ref_output_data));
-  EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(ref_output_shape));
-}
-
-TEST(MaxPool2DTest, Uint8)
-{
-  std::pair<float, int32_t> quant_param = quantizationParams<uint8_t>(-15.9375, 15.9375);
-  std::vector<float> input_data{
-      0,  -6, 12, 4, //
-      -3, -2, 10, 7, //
-  };
-  Tensor input_tensor = makeInputTensor<DataType::U8>({1, 2, 4, 1}, quant_param.first,
-                                                      quant_param.second, input_data);
-  Tensor output_tensor = makeOutputTensor(DataType::U8, quant_param.first, quant_param.second);
-
-  Pool2DParams params{};
-  params.padding = Padding::VALID;
-  params.filter_height = 2;
-  params.filter_width = 2;
-  params.stride_height = 2;
-  params.stride_width = 2;
-  params.activation = Activation::RELU6;
-
-  MaxPool2D kernel(&input_tensor, &output_tensor, params);
-  kernel.configure();
-  kernel.execute();
-
-  std::vector<float> ref_output_data{0.0, 6.0};
-  std::initializer_list<int32_t> ref_output_shape{1, 1, 2, 1};
-  EXPECT_THAT(dequantizeTensorData(output_tensor), FloatArrayNear(ref_output_data));
-  EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(ref_output_shape));
-}
-
-TEST(MaxPool2DTest, SInt16)
-{
-  Shape input_shape{1, 3, 5, 1};
-  std::vector<int32_t> ref_output_shape{1, 2, 2, 1};
-  std::vector<float> input_data{
-      1,  -1, 0,  -2, 2,  //
-      -7, -6, -5, -4, -3, //
-      5,  4,  3,  6,  7,  //
-  };
-  std::vector<float> ref_output_data{
-      1, 2, //
-      5, 6, //
-  };
-
-  Tensor input_tensor = makeInputTensor<DataType::S16>(input_shape, 0.2, 0, input_data);
-  Tensor output_tensor = makeOutputTensor(DataType::S16, 0.2, 0);
-
-  Pool2DParams params{};
-  params.padding = Padding::VALID;
-  params.filter_height = 2;
-  params.filter_width = 3;
-  params.stride_height = 1;
-  params.stride_width = 2;
-  params.activation = Activation::RELU6;
-
-  MaxPool2D kernel(&input_tensor, &output_tensor, params);
-  kernel.configure();
-  kernel.execute();
-
-  EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(ref_output_shape));
-  EXPECT_THAT(dequantizeTensorData(output_tensor), FloatArrayNear(ref_output_data));
-}
-
-} // namespace
-} // namespace kernels
-} // namespace luci_interpreter