/*
* 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.
* limitations under the License.
*/
-#include "kernels/Transpose.h"
#include "kernels/TestUtils.h"
-#include "luci_interpreter/TestMemoryManager.h"
+#include "luci_interpreter/test_models/transpose/TransposeKernel.h"
+
+#include "loader/ModuleLoader.h"
namespace luci_interpreter
{
-namespace kernels
-{
namespace
{
using namespace testing;
+class TransposeTest : public ::testing::Test
+{
+ // Do nothing
+};
+
template <typename T>
-void Check(std::initializer_list<int32_t> input_shape, std::initializer_list<int32_t> perm_shape,
- std::initializer_list<int32_t> output_shape, std::initializer_list<T> input_data,
- std::initializer_list<int32_t> perm_data, std::initializer_list<T> output_data)
+std::vector<T> checkTransposeKernel(test_kernel::TestDataBase<T> *test_data_base)
{
- std::unique_ptr<IMemoryManager> memory_manager = std::make_unique<TestMemoryManager>();
- constexpr DataType element_type = getElementType<T>();
- Tensor input_tensor =
- makeInputTensor<element_type>(input_shape, input_data, memory_manager.get());
- Tensor perm_tensor = makeInputTensor<DataType::S32>(perm_shape, perm_data, memory_manager.get());
- Tensor output_tensor = makeOutputTensor(element_type);
+ MemoryManager memory_manager{};
+ RuntimeModule runtime_module{};
+ bool dealloc_input = true;
- Transpose kernel(&input_tensor, &perm_tensor, &output_tensor);
- kernel.configure();
- memory_manager->allocate_memory(output_tensor);
- kernel.execute();
+ // 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);
- EXPECT_THAT(extractTensorData<T>(output_tensor), ::testing::ElementsAreArray(output_data));
-}
+ auto *main_runtime_graph = runtime_module.getMainGraph();
+ assert(main_runtime_graph->getNumOfInputTensors() == 1);
-template <typename T> class TransposeTest : public ::testing::Test
-{
-};
+ // 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);
+ }
-using DataTypes = ::testing::Types<float, uint8_t>;
-TYPED_TEST_SUITE(TransposeTest, DataTypes);
+ runtime_module.execute();
-TYPED_TEST(TransposeTest, Small3D)
-{
- Check<TypeParam>(/*input_shape=*/{2, 3, 4}, /*perm_shape=*/{3}, /*output_shape=*/{4, 2, 3},
- /*input_data=*/{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
- 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23},
- /*perm_data=*/{2, 0, 1},
- /*output_data=*/{0, 4, 8, 12, 16, 20, 1, 5, 9, 13, 17, 21,
- 2, 6, 10, 14, 18, 22, 3, 7, 11, 15, 19, 23});
-}
+ assert(main_runtime_graph->getNumOfOutputTensors() == 1);
-TYPED_TEST(TransposeTest, Large4D)
-{
- Check<TypeParam>(
- /*input_shape=*/{2, 3, 4, 5}, /*perm_shape=*/{4}, /*output_shape=*/{4, 2, 3, 5},
- /*input_data=*/{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
- 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
- 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44,
- 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
- 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74,
- 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
- 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104,
- 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119},
- /*perm_data=*/{2, 0, 1, 3},
- /*output_data=*/{0, 1, 2, 3, 4, 20, 21, 22, 23, 24, 40, 41, 42, 43, 44,
- 60, 61, 62, 63, 64, 80, 81, 82, 83, 84, 100, 101, 102, 103, 104,
- 5, 6, 7, 8, 9, 25, 26, 27, 28, 29, 45, 46, 47, 48, 49,
- 65, 66, 67, 68, 69, 85, 86, 87, 88, 89, 105, 106, 107, 108, 109,
- 10, 11, 12, 13, 14, 30, 31, 32, 33, 34, 50, 51, 52, 53, 54,
- 70, 71, 72, 73, 74, 90, 91, 92, 93, 94, 110, 111, 112, 113, 114,
- 15, 16, 17, 18, 19, 35, 36, 37, 38, 39, 55, 56, 57, 58, 59,
- 75, 76, 77, 78, 79, 95, 96, 97, 98, 99, 115, 116, 117, 118, 119});
+ 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(TransposeTest, Large2D)
+TEST_F(TransposeTest, MainTest_P)
{
- Check<TypeParam>(
- /*input_shape=*/{10, 12}, /*perm_shape=*/{2}, /*output_shape=*/{12, 10},
- /*input_data=*/{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
- 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
- 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44,
- 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
- 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74,
- 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
- 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104,
- 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119},
- /*perm_data=*/{1, 0},
- /*output_data=*/{0, 12, 24, 36, 48, 60, 72, 84, 96, 108, 1, 13, 25, 37, 49,
- 61, 73, 85, 97, 109, 2, 14, 26, 38, 50, 62, 74, 86, 98, 110,
- 3, 15, 27, 39, 51, 63, 75, 87, 99, 111, 4, 16, 28, 40, 52,
- 64, 76, 88, 100, 112, 5, 17, 29, 41, 53, 65, 77, 89, 101, 113,
- 6, 18, 30, 42, 54, 66, 78, 90, 102, 114, 7, 19, 31, 43, 55,
- 67, 79, 91, 103, 115, 8, 20, 32, 44, 56, 68, 80, 92, 104, 116,
- 9, 21, 33, 45, 57, 69, 81, 93, 105, 117, 10, 22, 34, 46, 58,
- 70, 82, 94, 106, 118, 11, 23, 35, 47, 59, 71, 83, 95, 107, 119});
+ test_kernel::TestDataTransposeKernel<float> test_data_kernel;
+ std::vector<float> output_data_vector = checkTransposeKernel(&test_data_kernel);
+ EXPECT_THAT(output_data_vector, test_data_kernel.get_output_data_by_index(0));
}
+// TODO: add negative tests?
+
} // namespace
-} // namespace kernels
} // namespace luci_interpreter
projects / platform / core / ml / nnfw.git / blobdiff