/* * 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/ResizeNearestNeighbor.h" #include "kernels/TestUtils.h" #include "luci_interpreter/TestMemoryManager.h" namespace luci_interpreter { namespace kernels { namespace { using namespace testing; template void Check(std::initializer_list input_shape, std::initializer_list size_shape, std::initializer_list output_shape, std::initializer_list input_data, std::initializer_list size_data, std::initializer_list output_data, bool align_corners, bool half_pixel_centers) { std::unique_ptr memory_manager = std::make_unique(); Tensor input_tensor = makeInputTensor(input_shape, input_data, memory_manager.get()); Tensor size_tensor = makeInputTensor(size_shape, size_data, memory_manager.get()); Tensor output_tensor = makeOutputTensor(DataType::FLOAT32); ResizeNearestNeighborParams params{}; params.align_corners = align_corners; params.half_pixel_centers = half_pixel_centers; ResizeNearestNeighbor kernel(&input_tensor, &size_tensor, &output_tensor, params); kernel.configure(); memory_manager->allocate_memory(output_tensor); kernel.execute(); EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(output_shape)); EXPECT_THAT(extractTensorData(output_tensor), FloatArrayNear(output_data)); } template <> void Check(std::initializer_list input_shape, std::initializer_list size_shape, std::initializer_list output_shape, std::initializer_list input_data, std::initializer_list size_data, std::initializer_list output_data, bool align_corners, bool half_pixel_centers) { std::unique_ptr memory_manager = std::make_unique(); std::pair quant_param = quantizationParams(std::min(input_data) < 0 ? std::min(input_data) : 0.f, std::max(input_data) > 0 ? std::max(input_data) : 0.f); Tensor input_tensor = makeInputTensor( input_shape, quant_param.first, quant_param.second, input_data, memory_manager.get()); Tensor size_tensor = makeInputTensor(size_shape, size_data, memory_manager.get()); Tensor output_tensor = makeOutputTensor(DataType::U8, quant_param.first, quant_param.first); ResizeNearestNeighborParams params{}; params.align_corners = align_corners; params.half_pixel_centers = half_pixel_centers; ResizeNearestNeighbor kernel(&input_tensor, &size_tensor, &output_tensor, params); kernel.configure(); memory_manager->allocate_memory(output_tensor); kernel.execute(); EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(output_shape)); EXPECT_THAT(dequantizeTensorData(output_tensor), FloatArrayNear(output_data, output_tensor.scale())); } template class ResizeNearestNeighborTest : public ::testing::Test { }; using DataTypes = ::testing::Types; TYPED_TEST_SUITE(ResizeNearestNeighborTest, DataTypes); TYPED_TEST(ResizeNearestNeighborTest, SimpleTest) { Check({2, 2, 2, 1}, {2}, {2, 3, 3, 1}, { 3, 6, // 9, 12, // 4, 10, // 10, 16 // }, {3, 3}, { 3, 3, 6, // 3, 3, 6, // 9, 9, 12, // 4, 4, 10, // 4, 4, 10, // 10, 10, 16, // }, false, false); } TYPED_TEST(ResizeNearestNeighborTest, AlignCenterTest) { Check({2, 2, 2, 1}, {2}, {2, 3, 3, 1}, { 3, 6, // 9, 12, // 4, 10, // 10, 16 // }, {3, 3}, { 3, 6, 6, // 9, 12, 12, // 9, 12, 12, // 4, 10, 10, // 10, 16, 16, // 10, 16, 16, // }, true, false); } TYPED_TEST(ResizeNearestNeighborTest, HalfPixelCenterTest) { Check({2, 2, 2, 1}, {2}, {2, 3, 3, 1}, { 3, 6, // 9, 12, // 4, 10, // 10, 16 // }, {3, 3}, { 3, 6, 6, // 9, 12, 12, // 9, 12, 12, // 4, 10, 10, // 10, 16, 16, // 10, 16, 16, // }, false, true); } TEST(ResizeNearestNeighborTest, InputShapeInvalid_NEG) { std::unique_ptr memory_manager = std::make_unique(); Tensor input_tensor = makeInputTensor({2, 2, 2}, { 3, 6, // 9, 12, // 4, 10, // 10, 16 // }, memory_manager.get()); Tensor size_tensor = makeInputTensor({2}, {3, 3}, memory_manager.get()); Tensor output_tensor = makeOutputTensor(DataType::FLOAT32); ResizeNearestNeighborParams params{}; params.align_corners = false; params.half_pixel_centers = false; ResizeNearestNeighbor kernel(&input_tensor, &size_tensor, &output_tensor, params); EXPECT_ANY_THROW(kernel.configure()); } TEST(ResizeNearestNeighborTest, SizeShapeInvalid_NEG) { std::unique_ptr memory_manager = std::make_unique(); Tensor input_tensor = makeInputTensor({2, 2, 2, 1}, { 3, 6, // 9, 12, // 4, 10, // 10, 16 // }, memory_manager.get()); Tensor size_tensor = makeInputTensor({2, 1}, {3, 3}, memory_manager.get()); Tensor output_tensor = makeOutputTensor(DataType::FLOAT32); ResizeNearestNeighborParams params{}; params.align_corners = false; params.half_pixel_centers = false; ResizeNearestNeighbor kernel(&input_tensor, &size_tensor, &output_tensor, params); EXPECT_ANY_THROW(kernel.configure()); } TEST(ResizeNearestNeighborTest, SizeDimInvalid_NEG) { std::unique_ptr memory_manager = std::make_unique(); Tensor input_tensor = makeInputTensor({2, 2, 2, 1}, { 3, 6, // 9, 12, // 4, 10, // 10, 16 // }, memory_manager.get()); Tensor size_tensor = makeInputTensor({3}, {3, 3, 1}, memory_manager.get()); Tensor output_tensor = makeOutputTensor(DataType::FLOAT32); ResizeNearestNeighborParams params{}; params.align_corners = false; params.half_pixel_centers = false; ResizeNearestNeighbor kernel(&input_tensor, &size_tensor, &output_tensor, params); EXPECT_ANY_THROW(kernel.configure()); } } // namespace } // namespace kernels } // namespace luci_interpreter