143 lines
6.0 KiB
C++
143 lines
6.0 KiB
C++
/*
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* Copyright (c) 2018-2019 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#ifndef ARM_COMPUTE_TEST_RANGE_FIXTURE
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#define ARM_COMPUTE_TEST_RANGE_FIXTURE
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#include "arm_compute/core/TensorShape.h"
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#include "arm_compute/core/Types.h"
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#include "tests/AssetsLibrary.h"
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#include "tests/Globals.h"
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#include "tests/IAccessor.h"
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#include "tests/framework/Asserts.h"
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#include "tests/framework/Fixture.h"
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#include "tests/validation/Helpers.h"
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#include "tests/validation/reference/Range.h"
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#include <algorithm>
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namespace arm_compute
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{
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namespace test
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{
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namespace validation
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{
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namespace
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{
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size_t num_of_elements_in_range(float start, float end, float step)
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{
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ARM_COMPUTE_ERROR_ON(step == 0);
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return size_t(std::ceil((end - start) / step));
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}
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}
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template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
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class RangeFixture : public framework::Fixture
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{
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public:
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template <typename...>
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void setup(const DataType data_type0, float start, float step, const QuantizationInfo qinfo0 = QuantizationInfo())
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{
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_target = compute_target(data_type0, qinfo0, start, step);
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_reference = compute_reference(data_type0, qinfo0, start, step);
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}
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protected:
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float get_random_end(const DataType output_data_type, const QuantizationInfo qinfo_out, float start, float step)
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{
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std::uniform_real_distribution<> distribution(1, 100);
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std::mt19937 gen(library->seed());
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float end = start;
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switch(output_data_type)
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{
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case DataType::U8:
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end += std::max((uint8_t)1, static_cast<uint8_t>(distribution(gen))) * step;
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return utility::clamp<float, uint8_t>(end);
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case DataType::U16:
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end += std::max((uint16_t)1, static_cast<uint16_t>(distribution(gen))) * step;
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return utility::clamp<float, uint16_t>(end);
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case DataType::U32:
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end += std::max((uint32_t)1, static_cast<uint32_t>(distribution(gen))) * step;
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return utility::clamp<float, uint32_t>(end);
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case DataType::S8:
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end += std::max((int8_t)1, static_cast<int8_t>(distribution(gen))) * step;
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return utility::clamp<float, int8_t>(end);
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case DataType::S16:
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end += std::max((int16_t)1, static_cast<int16_t>(distribution(gen))) * step;
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return utility::clamp<float, int16_t>(end);
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case DataType::S32:
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end += std::max((int32_t)1, static_cast<int32_t>(distribution(gen))) * step;
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return utility::clamp<float, int32_t>(end);
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case DataType::F32:
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end += std::max(1.0f, static_cast<float>(distribution(gen))) * step;
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return end;
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case DataType::F16:
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end += std::max(half(1.0f), static_cast<half>(distribution(gen))) * step;
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return utility::clamp<float, half>(end);
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case DataType::QASYMM8:
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return utility::clamp<float, uint8_t>(end + (float)distribution(gen) * step,
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dequantize_qasymm8(0, qinfo_out.uniform()),
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dequantize_qasymm8(std::numeric_limits<uint8_t>::max(), qinfo_out.uniform()));
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default:
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return 0;
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}
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}
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TensorType compute_target(const DataType output_data_type, const QuantizationInfo qinfo_out, float start, float step)
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{
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float end = get_random_end(output_data_type, qinfo_out, start, step);
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size_t num_of_elements = num_of_elements_in_range(start, end, step);
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// Create tensor
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TensorType dst = create_tensor<TensorType>(TensorShape(num_of_elements), output_data_type, 1, qinfo_out);
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// Create and configure function
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FunctionType range_func;
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range_func.configure(&dst, start, end, step);
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ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
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// Allocate tensors
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dst.allocator()->allocate();
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ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
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// Compute function
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range_func.run();
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return dst;
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}
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SimpleTensor<T> compute_reference(const DataType output_data_type, const QuantizationInfo qinfo_out, float start, float step)
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{
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// Create tensor
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const float end = get_random_end(output_data_type, qinfo_out, start, step);
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size_t num_of_elements = num_of_elements_in_range(start, end, step);
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SimpleTensor<T> ref_dst{ TensorShape(num_of_elements ? num_of_elements : 1), output_data_type, 1, qinfo_out };
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return reference::range<T>(ref_dst, start, num_of_elements, step);
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}
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TensorType _target{};
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SimpleTensor<T> _reference{};
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};
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} // namespace validation
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} // namespace test
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} // namespace arm_compute
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#endif /* ARM_COMPUTE_TEST_RANGE_FIXTURE */
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