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Diffstat (limited to 'tests/validation/NEON/Unstack.cpp')
-rw-r--r-- | tests/validation/NEON/Unstack.cpp | 128 |
1 files changed, 128 insertions, 0 deletions
diff --git a/tests/validation/NEON/Unstack.cpp b/tests/validation/NEON/Unstack.cpp new file mode 100644 index 0000000000..6be80df3c6 --- /dev/null +++ b/tests/validation/NEON/Unstack.cpp @@ -0,0 +1,128 @@ +/* + * Copyright (c) 2018-2019 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "arm_compute/core/Types.h" +#include "arm_compute/runtime/NEON/functions/NEUnstack.h" +#include "arm_compute/runtime/Tensor.h" +#include "arm_compute/runtime/TensorAllocator.h" + +#include "tests/NEON/Accessor.h" +#include "tests/datasets/ShapeDatasets.h" +#include "tests/framework/Asserts.h" +#include "tests/framework/Macros.h" +#include "tests/framework/datasets/Datasets.h" +#include "tests/validation/Validation.h" +#include "tests/validation/fixtures/UnstackFixture.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace +{ +const auto unstack_axis_dataset = framework::dataset::make("Axis", -3, 3); +const auto unstack_num_dataset = framework::dataset::make("Num", 1, 3); // The length of the dimension axis +const auto unstack_dataset_small = datasets::Small3DShapes() * unstack_axis_dataset * unstack_num_dataset; +} //namespace + +TEST_SUITE(NEON) +TEST_SUITE(Unstack) + +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( + framework::dataset::make("InputInfo", +{ + TensorInfo(TensorShape(1U, 9U, 8U), 1, DataType::U8), // Passes, 1 slice on x axis + TensorInfo(TensorShape(1U, 2U, 3U), 1, DataType::U8), // fails because axis > input's rank + TensorInfo(TensorShape(1U, 2U, 3U), 1, DataType::S32), // fails axis < (- input's rank) + TensorInfo(TensorShape(3U, 7U, 5U), 1, DataType::S32), // passes, 3 slices along X + TensorInfo(TensorShape(13U, 7U, 5U), 1, DataType::S16), // fails, too few output slices + TensorInfo(TensorShape(1U, 2U, 3U), 1, DataType::U8), // fails mismatching data types +}), +framework::dataset::make("OutputInfo", +{ + std::vector<TensorInfo>{ TensorInfo(TensorShape(9U, 8U), 1, DataType::U8) }, std::vector<TensorInfo>{ TensorInfo(TensorShape(2U, 3U), 1, DataType::U8) }, std::vector<TensorInfo>{ TensorInfo(TensorShape(2U, 3U), 1, DataType::S32) }, + + std::vector<TensorInfo>{ TensorInfo(TensorShape(7U, 5U), 1, DataType::S32), TensorInfo(TensorShape(7U, 5U), 1, DataType::S32), TensorInfo(TensorShape(7U, 5U), 1, DataType::S32) }, std::vector<TensorInfo>{ TensorInfo(TensorShape(7U, 5U), 1, DataType::S16) }, std::vector<TensorInfo>{ TensorInfo(TensorShape(9U, 8U), 1, DataType::S32) }, +})), +framework::dataset::make("Axis", { -3, 3, -4, -3, 1, 1 })), +framework::dataset::make("Num", { 1, 1, 1, 1, 0, 1 })), +framework::dataset::make("Expected", { true, false, false, true, false, false })), +input_info, output_info, axis, num, expected) +{ + std::vector<TensorInfo> ti(output_info); + std::vector<ITensorInfo *> vec(num); + for(size_t j = 0; j < vec.size(); ++j) + { + vec[j] = &ti[j]; + } + ARM_COMPUTE_EXPECT(bool(NEUnstack::validate(&input_info.clone()->set_is_resizable(false), vec, axis)) == expected, framework::LogLevel::ERRORS); +} + +template <typename T> +using NEUnstackFixture = UnstackValidationFixture<Tensor, ITensor, Accessor, NEUnstack, T>; + +TEST_SUITE(F32) +FIXTURE_DATA_TEST_CASE(RunSmall, NEUnstackFixture<float>, framework::DatasetMode::PRECOMMIT, unstack_dataset_small * framework::dataset::make("DataType", { DataType::F32 })) +{ + ARM_COMPUTE_ERROR_ON(_target.size() != _reference.size()); + // Validate output + for(size_t k = 0; k < _target.size(); ++k) + { + validate(Accessor(_target[k]), _reference[k]); + } +} +TEST_SUITE_END() // F32 + +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +TEST_SUITE(F16) +FIXTURE_DATA_TEST_CASE(RunSmall, NEUnstackFixture<half>, framework::DatasetMode::PRECOMMIT, unstack_dataset_small * framework::dataset::make("DataType", { DataType::F16 })) +{ + ARM_COMPUTE_ERROR_ON(_target.size() != _reference.size()); + // Validate output + for(size_t k = 0; k < _target.size(); ++k) + { + validate(Accessor(_target[k]), _reference[k]); + } +} +TEST_SUITE_END() // F16 +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ + +TEST_SUITE(Quantized) +FIXTURE_DATA_TEST_CASE(RunSmall, NEUnstackFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, unstack_dataset_small * framework::dataset::make("DataType", { DataType::QASYMM8 })) +{ + ARM_COMPUTE_ERROR_ON(_target.size() != _reference.size()); + // Validate output + for(size_t k = 0; k < _target.size(); ++k) + { + validate(Accessor(_target[k]), _reference[k]); + } +} +TEST_SUITE_END() // QASYMM8 + +TEST_SUITE_END() // Unstack +TEST_SUITE_END() // NEON +} // namespace validation +} // namespace test +} // namespace arm_compute |