169 lines
6.2 KiB
C++
169 lines
6.2 KiB
C++
/*
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* Copyright (c) 2017-2019 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_DEQUANTIZATION_LAYER_FIXTURE
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#define ARM_COMPUTE_TEST_DEQUANTIZATION_LAYER_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 "arm_compute/runtime/Tensor.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/DequantizationLayer.h"
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#include <random>
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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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template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
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class DequantizationValidationFixture : public framework::Fixture
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{
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public:
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template <typename...>
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void setup(TensorShape shape, DataType src_data_type, DataType dst_datatype, DataLayout data_layout)
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{
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_quantization_info = generate_quantization_info(src_data_type, shape.z());
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_target = compute_target(shape, src_data_type, dst_datatype, data_layout);
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_reference = compute_reference(shape, src_data_type);
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}
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protected:
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template <typename U>
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void fill(U &&tensor)
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{
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library->fill_tensor_uniform(tensor, 0);
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}
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TensorType compute_target(TensorShape shape, DataType src_data_type, DataType dst_datatype, DataLayout data_layout)
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{
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if(data_layout == DataLayout::NHWC)
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{
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permute(shape, PermutationVector(2U, 0U, 1U));
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}
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// Create tensors
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TensorType src = create_tensor<TensorType>(shape, src_data_type, 1, _quantization_info, data_layout);
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TensorType dst = create_tensor<TensorType>(shape, dst_datatype, 1, QuantizationInfo(), data_layout);
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// Create and configure function
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FunctionType dequantization_layer;
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dequantization_layer.configure(&src, &dst);
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ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
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ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
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// Allocate tensors
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src.allocator()->allocate();
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dst.allocator()->allocate();
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ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
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ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
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// Fill tensors
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fill(AccessorType(src));
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// Compute function
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dequantization_layer.run();
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return dst;
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}
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SimpleTensor<T> compute_reference(const TensorShape &shape, DataType src_data_type)
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{
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switch(src_data_type)
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{
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case DataType::QASYMM8:
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{
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SimpleTensor<uint8_t> src{ shape, src_data_type, 1, _quantization_info };
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fill(src);
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return reference::dequantization_layer<T>(src);
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}
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case DataType::QASYMM8_SIGNED:
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case DataType::QSYMM8_PER_CHANNEL:
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case DataType::QSYMM8:
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{
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SimpleTensor<int8_t> src{ shape, src_data_type, 1, _quantization_info };
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fill(src);
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return reference::dequantization_layer<T>(src);
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}
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case DataType::QSYMM16:
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{
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SimpleTensor<int16_t> src{ shape, src_data_type, 1, _quantization_info };
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fill(src);
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return reference::dequantization_layer<T>(src);
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}
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default:
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ARM_COMPUTE_ERROR("Unsupported data type");
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}
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}
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protected:
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QuantizationInfo generate_quantization_info(DataType data_type, int32_t num_channels)
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{
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std::mt19937 gen(library.get()->seed());
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std::uniform_int_distribution<> distribution_scale_q8(1, 255);
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std::uniform_int_distribution<> distribution_offset_q8(1, 127);
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std::uniform_int_distribution<> distribution_scale_q16(1, 32768);
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switch(data_type)
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{
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case DataType::QSYMM16:
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return QuantizationInfo(1.f / distribution_scale_q16(gen));
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case DataType::QSYMM8:
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return QuantizationInfo(1.f / distribution_scale_q8(gen));
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case DataType::QSYMM8_PER_CHANNEL:
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{
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std::vector<float> scale(num_channels);
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for(int32_t i = 0; i < num_channels; ++i)
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{
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scale[i] = 1.f / distribution_offset_q8(gen);
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}
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return QuantizationInfo(scale);
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}
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case DataType::QASYMM8:
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return QuantizationInfo(1.f / distribution_scale_q8(gen), distribution_offset_q8(gen));
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case DataType::QASYMM8_SIGNED:
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return QuantizationInfo(1.f / distribution_scale_q8(gen), -distribution_offset_q8(gen));
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default:
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ARM_COMPUTE_ERROR("Unsupported data type");
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}
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}
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protected:
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TensorType _target{};
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SimpleTensor<T> _reference{};
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QuantizationInfo _quantization_info{};
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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_DEQUANTIZATION_LAYER_FIXTURE */
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