/*
* Copyright (c) 2020 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.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
-// TODO enable it
-#if 0
-#include "kernels/Logistic.h"
+
#include "kernels/TestUtils.h"
-#include "luci_interpreter/TestMemoryManager.h"
+#include "luci_interpreter/test_models/logistic/FloatLogisticKernel.h"
+#include "luci_interpreter/test_models/logistic/NegLogisticKernel.h"
+
+#include "loader/ModuleLoader.h"
namespace luci_interpreter
{
-namespace kernels
-{
namespace
{
using namespace testing;
+class LogisticTest : public ::testing::Test
+{
+ // Do nothing
+};
+
template <typename T>
-void Check(std::initializer_list<int32_t> input_shape, std::initializer_list<int32_t> output_shape,
- std::initializer_list<float> input_data, std::initializer_list<float> output_data)
+std::vector<T> checkLogisticKernel(test_kernel::TestDataBase<T> *test_data_base)
{
- std::unique_ptr<IMemoryManager> memory_manager = std::make_unique<TestMemoryManager>();
+ MemoryManager memory_manager{};
+ RuntimeModule runtime_module{};
+ bool dealloc_input = true;
- Tensor input_tensor =
- makeInputTensor<getElementType<T>()>(input_shape, input_data, memory_manager.get());
- Tensor output_tensor = makeOutputTensor(getElementType<T>());
+ // Load model with single op
+ auto *model_data_raw = reinterpret_cast<const char *>(test_data_base->get_model_ptr());
+ ModuleLoader::load(&runtime_module, &memory_manager, model_data_raw, dealloc_input);
- Logistic kernel(&input_tensor, &output_tensor);
- kernel.configure();
- memory_manager->allocate_memory(output_tensor);
- kernel.execute();
+ auto *main_runtime_graph = runtime_module.getMainGraph();
+ assert(main_runtime_graph->getNumOfInputTensors() == 1);
- EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(output_data));
- EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(output_shape));
-}
+ // Set input data
+ {
+ auto *input_tensor_data = reinterpret_cast<T *>(main_runtime_graph->configureGraphInput(0));
+ std::copy(test_data_base->get_input_data_by_index(0).begin(),
+ test_data_base->get_input_data_by_index(0).end(), input_tensor_data);
+ }
-template <>
-void Check<uint8_t>(std::initializer_list<int32_t> input_shape,
- std::initializer_list<int32_t> output_shape,
- std::initializer_list<float> input_data,
- std::initializer_list<float> output_data)
-{
- std::unique_ptr<IMemoryManager> memory_manager = std::make_unique<TestMemoryManager>();
-
- std::pair<float, int32_t> input_quant_param =
- quantizationParams<uint8_t>(std::min(input_data), std::max(input_data));
- Tensor input_tensor =
- makeInputTensor<DataType::U8>(input_shape, input_quant_param.first, input_quant_param.second,
- input_data, memory_manager.get());
- Tensor output_tensor = makeOutputTensor(DataType::U8, 1. / 256, 0);
-
- Logistic kernel(&input_tensor, &output_tensor);
- kernel.configure();
- memory_manager->allocate_memory(output_tensor);
- kernel.execute();
-
- EXPECT_THAT(dequantizeTensorData(output_tensor),
- FloatArrayNear(output_data, output_tensor.scale() * 2));
- EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(output_shape));
-}
+ runtime_module.execute();
-template <typename T> class LogisticTest : public ::testing::Test
-{
-};
+ assert(main_runtime_graph->getNumOfOutputTensors() == 1);
-using DataTypes = ::testing::Types<float, uint8_t>;
-TYPED_TEST_SUITE(LogisticTest, DataTypes);
+ T *output_data = reinterpret_cast<T *>(main_runtime_graph->getOutputDataByIndex(0));
+ const size_t num_elements = (main_runtime_graph->getOutputDataSizeByIndex(0) / sizeof(T));
+ std::vector<T> output_data_vector(output_data, output_data + num_elements);
+ return output_data_vector;
+}
-TYPED_TEST(LogisticTest, Simple)
+TEST_F(LogisticTest, Float_P)
{
- Check<TypeParam>(
- {89}, {89},
- {-10.0000000000, -9.7727272727, -9.5454545455, -9.3181818182, -9.0909090909, -8.8636363636,
- -8.6363636364, -8.4090909091, -8.1818181818, -7.9545454545, -7.7272727273, -7.5000000000,
- -7.2727272727, -7.0454545455, -6.8181818182, -6.5909090909, -6.3636363636, -6.1363636364,
- -5.9090909091, -5.6818181818, -5.4545454545, -5.2272727273, -5.0000000000, -4.7727272727,
- -4.5454545455, -4.3181818182, -4.0909090909, -3.8636363636, -3.6363636364, -3.4090909091,
- -3.1818181818, -2.9545454545, -2.7272727273, -2.5000000000, -2.2727272727, -2.0454545455,
- -1.8181818182, -1.5909090909, -1.3636363636, -1.1363636364, -0.9090909091, -0.6818181818,
- -0.4545454545, -0.2272727273, 0.0000000000, 0.2272727273, 0.4545454545, 0.6818181818,
- 0.9090909091, 1.1363636364, 1.3636363636, 1.5909090909, 1.8181818182, 2.0454545455,
- 2.2727272727, 2.5000000000, 2.7272727273, 2.9545454545, 3.1818181818, 3.4090909091,
- 3.6363636364, 3.8636363636, 4.0909090909, 4.3181818182, 4.5454545455, 4.7727272727,
- 5.0000000000, 5.2272727273, 5.4545454545, 5.6818181818, 5.9090909091, 6.1363636364,
- 6.3636363636, 6.5909090909, 6.8181818182, 7.0454545455, 7.2727272727, 7.5000000000,
- 7.7272727273, 7.9545454545, 8.1818181818, 8.4090909091, 8.6363636364, 8.8636363636,
- 9.0909090909, 9.3181818182, 9.5454545455, 9.7727272727, 10.0000000000},
- {0.0000453979, 0.0000569815, 0.0000715205, 0.0000897689, 0.0001126729, 0.0001414198,
- 0.0001774998, 0.0002227827, 0.0002796147, 0.0003509396, 0.0004404502, 0.0005527786,
- 0.0006937345, 0.0008706021, 0.0010925128, 0.0013709094, 0.0017201256, 0.0021581065,
- 0.0027073042, 0.0033957870, 0.0042586071, 0.0053394826, 0.0066928509, 0.0083863576,
- 0.0105038445, 0.0131488902, 0.0164489307, 0.0205599431, 0.0256715863, 0.0320125562,
- 0.0398556989, 0.0495221198, 0.0613831074, 0.0758581800, 0.0934070047, 0.1145124805,
- 0.1396521834, 0.1692560327, 0.2036499335, 0.2429886272, 0.2871859014, 0.3358556241,
- 0.3882805886, 0.4434251301, 0.5000000000, 0.5565748699, 0.6117194114, 0.6641443759,
- 0.7128140986, 0.7570113728, 0.7963500665, 0.8307439673, 0.8603478166, 0.8854875195,
- 0.9065929953, 0.9241418200, 0.9386168926, 0.9504778802, 0.9601443011, 0.9679874438,
- 0.9743284137, 0.9794400569, 0.9835510693, 0.9868511098, 0.9894961555, 0.9916136424,
- 0.9933071491, 0.9946605174, 0.9957413929, 0.9966042130, 0.9972926958, 0.9978418935,
- 0.9982798744, 0.9986290906, 0.9989074872, 0.9991293979, 0.9993062655, 0.9994472214,
- 0.9995595498, 0.9996490604, 0.9997203853, 0.9997772173, 0.9998225002, 0.9998585802,
- 0.9998873271, 0.9999102311, 0.9999284795, 0.9999430185, 0.9999546021});
+ test_kernel::TestDataFloatLogistic test_data_kernel;
+ std::vector<float> output_data_vector = checkLogisticKernel(&test_data_kernel);
+ EXPECT_THAT(output_data_vector, test_data_kernel.get_output_data_by_index(0));
}
-TEST(LogisticTest, IvalidInputOutputType_NEG)
+TEST_F(LogisticTest, Input_output_type_mismatch_NEG)
{
- std::unique_ptr<IMemoryManager> memory_manager = std::make_unique<TestMemoryManager>();
-
- Shape input_shape = {1};
- std::vector<float> input_data{10};
- Tensor input_tensor =
- makeInputTensor<DataType::FLOAT32>(input_shape, input_data, memory_manager.get());
- Tensor output_tensor = makeOutputTensor(DataType::U8, 1. / 256, 0);
-
- Logistic kernel(&input_tensor, &output_tensor);
- EXPECT_ANY_THROW(kernel.configure());
+ test_kernel::NegTestDataInputOutputTypeMismatchLogisticKernel test_data_kernel;
+
+ MemoryManager memory_manager{};
+ RuntimeModule runtime_module{};
+ bool dealloc_input = true;
+ // Load model with single op
+ auto *model_data_raw = reinterpret_cast<const char *>(test_data_kernel.get_model_ptr());
+ EXPECT_DEATH(ModuleLoader::load(&runtime_module, &memory_manager, model_data_raw, dealloc_input),
+ "");
}
-TEST(LogisticTest, IvalidQuantParam_NEG)
+TEST_F(LogisticTest, No_quant_params_NEG)
{
- std::unique_ptr<IMemoryManager> memory_manager = std::make_unique<TestMemoryManager>();
- Shape input_shape = {2};
- std::vector<float> input_data{-10, 10};
- std::pair<float, int32_t> input_quant_param = quantizationParams<uint8_t>(-10, 10);
- Tensor input_tensor =
- makeInputTensor<DataType::U8>(input_shape, input_quant_param.first, input_quant_param.second,
- input_data, memory_manager.get());
- Tensor output_tensor = makeOutputTensor(DataType::U8, 1. / 255, 0);
-
- Logistic kernel(&input_tensor, &output_tensor);
- EXPECT_ANY_THROW(kernel.configure());
+ test_kernel::NegTestDataNoQuantParamsLogisticKernel test_data_kernel;
+
+ MemoryManager memory_manager{};
+ RuntimeModule runtime_module{};
+ bool dealloc_input = true;
+ // Load model with single op
+ auto *model_data_raw = reinterpret_cast<const char *>(test_data_kernel.get_model_ptr());
+ EXPECT_DEATH(ModuleLoader::load(&runtime_module, &memory_manager, model_data_raw, dealloc_input),
+ "");
}
+// TODO: add S8 test
} // namespace
-} // namespace kernels
} // namespace luci_interpreter
-#endif
projects / platform / core / ml / nnfw.git / blobdiff