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Diffstat (limited to 'compiler/luci-interpreter/src/kernels/Dequantize.test.cpp')
| -rw-r--r-- | compiler/luci-interpreter/src/kernels/Dequantize.test.cpp | 149 |
1 files changed, 149 insertions, 0 deletions
diff --git a/compiler/luci-interpreter/src/kernels/Dequantize.test.cpp b/compiler/luci-interpreter/src/kernels/Dequantize.test.cpp new file mode 100644 index 000000000..0cab633d6 --- /dev/null +++ b/compiler/luci-interpreter/src/kernels/Dequantize.test.cpp @@ -0,0 +1,149 @@ +/* + * Copyright (c) 2022 Samsung Electronics Co., Ltd. All Rights Reserved + * Copyright 2019 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/Dequantize.h" +#include "kernels/TestUtils.h" +#include "luci_interpreter/TestMemoryManager.h" + +namespace luci_interpreter +{ +namespace kernels +{ +namespace +{ + +using namespace testing; + +class DequantizeTest : public ::testing::Test +{ +protected: + void SetUp() override { _memory_manager = std::make_unique<TestMemoryManager>(); } + + std::unique_ptr<IMemoryManager> _memory_manager; +}; + +TEST_F(DequantizeTest, Uint8) +{ + std::vector<uint8_t> input_data{0, 1, 2, 3, 4, 251, 252, 253, 254, 255}; + + std::vector<float> ref_output_data{-63.5, -63, -62.5, -62, -61.5, 62, 62.5, 63, 63.5, 64}; + + Tensor input_tensor(loco::DataType::U8, {2, 5}, {{0.5}, {127}}, ""); + + _memory_manager->allocate_memory(input_tensor); + input_tensor.writeData(input_data.data(), input_data.size() * sizeof(uint8_t)); + + Tensor output_tensor = makeOutputTensor(DataType::FLOAT32); + + Dequantize kernel(&input_tensor, &output_tensor); + kernel.configure(); + _memory_manager->allocate_memory(output_tensor); + kernel.execute(); + + EXPECT_THAT(extractTensorData<float>(output_tensor), + ::testing::ElementsAreArray(ref_output_data)); + EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray({2, 5})); +} + +TEST_F(DequantizeTest, Sint8) +{ + std::vector<int8_t> input_data{-128, -127, -126, -125, -124, 123, 124, 125, 126, 127}; + + std::vector<float> ref_output_data{-63.5, -63, -62.5, -62, -61.5, 62, 62.5, 63, 63.5, 64}; + + Tensor input_tensor(loco::DataType::S8, {2, 5}, {{0.5}, {-1}}, ""); + + _memory_manager->allocate_memory(input_tensor); + input_tensor.writeData(input_data.data(), input_data.size() * sizeof(int8_t)); + + Tensor output_tensor = makeOutputTensor(DataType::FLOAT32); + + Dequantize kernel(&input_tensor, &output_tensor); + kernel.configure(); + _memory_manager->allocate_memory(output_tensor); + kernel.execute(); + + EXPECT_THAT(extractTensorData<float>(output_tensor), + ::testing::ElementsAreArray(ref_output_data)); + EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray({2, 5})); +} + +TEST_F(DequantizeTest, Sint16) +{ + std::vector<int16_t> input_data{-129, -126, -125, -124, -123, 124, 125, 126, 127, 131}; + + std::vector<float> ref_output_data{-64.5, -63, -62.5, -62, -61.5, 62, 62.5, 63, 63.5, 65.5}; + + Tensor input_tensor(loco::DataType::S16, {2, 5}, {{0.5}, {0}}, ""); + + _memory_manager->allocate_memory(input_tensor); + input_tensor.writeData(input_data.data(), input_data.size() * sizeof(int16_t)); + + Tensor output_tensor = makeOutputTensor(DataType::FLOAT32); + + Dequantize kernel(&input_tensor, &output_tensor); + kernel.configure(); + _memory_manager->allocate_memory(output_tensor); + kernel.execute(); + + EXPECT_THAT(extractTensorData<float>(output_tensor), + ::testing::ElementsAreArray(ref_output_data)); + EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray({2, 5})); +} + +TEST_F(DequantizeTest, InvalidInputType_NEG) +{ + std::vector<float> input_data{-129, -126, -125, -124, -123, 124, 125, 126, 127, 131}; + + Tensor input_tensor = + makeInputTensor<DataType::FLOAT32>({2, 5}, input_data, _memory_manager.get()); + Tensor output_tensor = makeOutputTensor(DataType::FLOAT32); + + Dequantize kernel(&input_tensor, &output_tensor); + EXPECT_ANY_THROW(kernel.configure()); +} + +TEST_F(DequantizeTest, InvalidOutputType_NEG) +{ + std::vector<int16_t> input_data{-129, -126, -125, -124, -123, 124, 125, 126, 127, 131}; + + Tensor input_tensor(loco::DataType::S16, {2, 5}, {{0.5}, {0}}, ""); + + _memory_manager->allocate_memory(input_tensor); + input_tensor.writeData(input_data.data(), input_data.size() * sizeof(int16_t)); + + Tensor output_tensor = makeOutputTensor(DataType::S8, /*scale*/ 0.5, /*zero_point*/ -1); + + Dequantize kernel(&input_tensor, &output_tensor); + EXPECT_ANY_THROW(kernel.configure()); +} + +TEST_F(DequantizeTest, InvalidInputZeroPoint_NEG) +{ + std::vector<float> input_data{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}; + + Tensor input_tensor = + makeInputTensor<DataType::S16>({2, 5}, 0.5, -1, input_data, _memory_manager.get()); + Tensor output_tensor = makeOutputTensor(DataType::FLOAT32); + + Dequantize kernel(&input_tensor, &output_tensor); + EXPECT_ANY_THROW(kernel.configure()); +} + +} // namespace +} // namespace kernels +} // namespace luci_interpreter |