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Diffstat (limited to 'compiler/luci-interpreter/src/kernels/LogSoftmax.test.cpp')
-rw-r--r-- | compiler/luci-interpreter/src/kernels/LogSoftmax.test.cpp | 111 |
1 files changed, 111 insertions, 0 deletions
diff --git a/compiler/luci-interpreter/src/kernels/LogSoftmax.test.cpp b/compiler/luci-interpreter/src/kernels/LogSoftmax.test.cpp new file mode 100644 index 000000000..d3b331dfe --- /dev/null +++ b/compiler/luci-interpreter/src/kernels/LogSoftmax.test.cpp @@ -0,0 +1,111 @@ +/* + * 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/LogSoftmax.h" +#include "kernels/TestUtils.h" + +namespace luci_interpreter +{ +namespace kernels +{ +namespace +{ + +using namespace testing; + +TEST(LogSoftmaxTest, Float) +{ + Shape input_shape{2, 4}; + std::vector<float> input_data{ + 0, -6, 2, 4, // + 3, -2, 10, 1, // + }; + Tensor input_tensor = makeInputTensor<DataType::FLOAT32>(input_shape, input_data); + Tensor output_tensor = makeOutputTensor(DataType::FLOAT32); + + LogSoftmax kernel(&input_tensor, &output_tensor); + kernel.configure(); + kernel.execute(); + + std::vector<float> ref_output_data{ + -4.14297, -10.14297, -2.14297, -.142971, // + -7.00104, -12.00104, -.00104087, -9.00104, // + }; + EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(ref_output_data)); +} + +TEST(LogSoftmaxTest, Uint8) +{ + float kMin = -10; + float kMax = 10; + float kLogSoftmaxQuantizedTolerance = 16. / 256; + std::pair<float, int32_t> quant_param = quantizationParams<uint8_t>(kMin, kMax); + std::vector<float> input_data{ + 0, -6, 2, 4, // + 3, -2, 10, 1, // + }; + Tensor input_tensor = + makeInputTensor<DataType::U8>({2, 4}, quant_param.first, quant_param.second, input_data); + Tensor output_tensor = makeOutputTensor(DataType::U8, 16. / 256, 255); + + LogSoftmax kernel(&input_tensor, &output_tensor); + kernel.configure(); + kernel.execute(); + + std::vector<float> ref_output_data{ + -4.14297, -10.14297, -2.14297, -.142971, // + -7.00104, -12.00104, -.00104087, -9.00104, // + }; + std::vector<int32_t> ref_output_shape{2, 4}; + EXPECT_THAT(dequantizeTensorData(output_tensor), + FloatArrayNear(ref_output_data, kLogSoftmaxQuantizedTolerance)); + EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(ref_output_shape)); + EXPECT_THAT(extractTensorData<uint8_t>(output_tensor), + ::testing::ElementsAreArray({189, 93, 221, 253, 142, 63, 255, 111})); +} + +TEST(LogSoftmaxTest, InvalidInputOutputType_NEG) +{ + std::vector<float> input_data{ + 0, -6, 2, 4, // + 3, -2, 10, 1, // + }; + Tensor input_tensor = makeInputTensor<DataType::FLOAT32>({2, 4}, input_data); + Tensor output_tensor = makeOutputTensor(DataType::U8, 16. / 256, 255); + + LogSoftmax kernel(&input_tensor, &output_tensor); + EXPECT_ANY_THROW(kernel.configure()); +} + +TEST(LogSoftmaxTest, InvalidOutputQuantParam_NEG) +{ + std::pair<float, int32_t> quant_param = quantizationParams<uint8_t>(-10, 10); + std::vector<float> input_data{ + 0, -6, 2, 4, // + 3, -2, 10, 1, // + }; + Tensor input_tensor = + makeInputTensor<DataType::U8>({2, 4}, quant_param.first, quant_param.second, input_data); + Tensor output_tensor = makeOutputTensor(DataType::U8, 20. / 256, 255); + + LogSoftmax kernel(&input_tensor, &output_tensor); + EXPECT_ANY_THROW(kernel.configure()); +} + +} // namespace +} // namespace kernels +} // namespace luci_interpreter |