| /* |
| * 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. |
| */ |
| #ifndef ARM_COMPUTE_TEST_RANGE_FIXTURE |
| #define ARM_COMPUTE_TEST_RANGE_FIXTURE |
| |
| #include "arm_compute/core/TensorShape.h" |
| #include "arm_compute/core/Types.h" |
| #include "tests/AssetsLibrary.h" |
| #include "tests/Globals.h" |
| #include "tests/IAccessor.h" |
| #include "tests/framework/Asserts.h" |
| #include "tests/framework/Fixture.h" |
| #include "tests/validation/Helpers.h" |
| #include "tests/validation/reference/Range.h" |
| |
| #include <algorithm> |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace |
| { |
| size_t num_of_elements_in_range(float start, float end, float step) |
| { |
| ARM_COMPUTE_ERROR_ON(step == 0); |
| return size_t(std::ceil((end - start) / step)); |
| } |
| } |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class RangeFixture : public framework::Fixture |
| { |
| public: |
| template <typename...> |
| void setup(const DataType data_type0, float start, float step, const QuantizationInfo qinfo0 = QuantizationInfo()) |
| { |
| _target = compute_target(data_type0, qinfo0, start, step); |
| _reference = compute_reference(data_type0, qinfo0, start, step); |
| } |
| |
| protected: |
| float get_random_end(const DataType output_data_type, const QuantizationInfo qinfo_out, float start, float step) |
| { |
| std::uniform_real_distribution<> distribution(1, 100); |
| std::mt19937 gen(library->seed()); |
| float end = start; |
| switch(output_data_type) |
| { |
| case DataType::U8: |
| end += std::max((uint8_t)1, static_cast<uint8_t>(distribution(gen))) * step; |
| return utility::clamp<float, uint8_t>(end); |
| case DataType::U16: |
| end += std::max((uint16_t)1, static_cast<uint16_t>(distribution(gen))) * step; |
| return utility::clamp<float, uint16_t>(end); |
| case DataType::U32: |
| end += std::max((uint32_t)1, static_cast<uint32_t>(distribution(gen))) * step; |
| return utility::clamp<float, uint32_t>(end); |
| case DataType::S8: |
| end += std::max((int8_t)1, static_cast<int8_t>(distribution(gen))) * step; |
| return utility::clamp<float, int8_t>(end); |
| case DataType::S16: |
| end += std::max((int16_t)1, static_cast<int16_t>(distribution(gen))) * step; |
| return utility::clamp<float, int16_t>(end); |
| case DataType::S32: |
| end += std::max((int32_t)1, static_cast<int32_t>(distribution(gen))) * step; |
| return utility::clamp<float, int32_t>(end); |
| case DataType::F32: |
| end += std::max(1.0f, static_cast<float>(distribution(gen))) * step; |
| return end; |
| case DataType::F16: |
| end += std::max(half(1.0f), static_cast<half>(distribution(gen))) * step; |
| return utility::clamp<float, half>(end); |
| case DataType::QASYMM8: |
| return utility::clamp<float, uint8_t>(end + (float)distribution(gen) * step, |
| dequantize_qasymm8(0, qinfo_out.uniform()), |
| dequantize_qasymm8(std::numeric_limits<uint8_t>::max(), qinfo_out.uniform())); |
| default: |
| return 0; |
| } |
| } |
| |
| TensorType compute_target(const DataType output_data_type, const QuantizationInfo qinfo_out, float start, float step) |
| { |
| float end = get_random_end(output_data_type, qinfo_out, start, step); |
| size_t num_of_elements = num_of_elements_in_range(start, end, step); |
| // Create tensor |
| TensorType dst = create_tensor<TensorType>(TensorShape(num_of_elements), output_data_type, 1, qinfo_out); |
| // Create and configure function |
| FunctionType range_func; |
| range_func.configure(&dst, start, end, step); |
| |
| ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); |
| // Allocate tensors |
| dst.allocator()->allocate(); |
| |
| ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); |
| |
| // Compute function |
| range_func.run(); |
| return dst; |
| } |
| |
| SimpleTensor<T> compute_reference(const DataType output_data_type, const QuantizationInfo qinfo_out, float start, float step) |
| { |
| // Create tensor |
| const float end = get_random_end(output_data_type, qinfo_out, start, step); |
| size_t num_of_elements = num_of_elements_in_range(start, end, step); |
| SimpleTensor<T> ref_dst{ TensorShape(num_of_elements ? num_of_elements : 1), output_data_type, 1, qinfo_out }; |
| return reference::range<T>(ref_dst, start, num_of_elements, step); |
| } |
| |
| TensorType _target{}; |
| SimpleTensor<T> _reference{}; |
| }; |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |
| #endif /* ARM_COMPUTE_TEST_RANGE_FIXTURE */ |