125 lines
4.1 KiB
C++
125 lines
4.1 KiB
C++
/*
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* Copyright (c) 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_MEAN_STDDEV_NORMALIZATION_LAYER_FIXTURE
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#define ARM_COMPUTE_TEST_MEAN_STDDEV_NORMALIZATION_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 "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/MeanStdDevNormalizationLayer.h"
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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 MeanStdDevNormalizationLayerValidationFixture : 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 dt, bool in_place, float epsilon = 1e-8f)
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{
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_data_type = dt;
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_target = compute_target(shape, dt, in_place, epsilon);
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_reference = compute_reference(shape, dt, epsilon);
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}
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protected:
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template <typename U>
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void fill(U &&src_tensor)
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{
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const float min_bound = -1.f;
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const float max_bound = 1.f;
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std::uniform_real_distribution<> distribution(min_bound, max_bound);
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library->fill(src_tensor, distribution, 0);
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}
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TensorType compute_target(TensorShape shape, DataType dt, bool in_place, float epsilon)
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{
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// Create tensors
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TensorType src = create_tensor<TensorType>(shape, dt, 1);
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TensorType dst;
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TensorType *dst_ptr = in_place ? &src : &dst;
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// Create and configure function
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FunctionType norm;
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norm.configure(&src, dst_ptr, epsilon);
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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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ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
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if(!in_place)
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{
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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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}
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// Fill tensors
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fill(AccessorType(src));
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// Compute function
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norm.run();
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if(in_place)
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{
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return src;
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}
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else
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{
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return dst;
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}
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}
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SimpleTensor<T> compute_reference(const TensorShape &shape, DataType dt, float epsilon)
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{
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// Create reference
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SimpleTensor<T> ref_src{ shape, dt, 1 };
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// Fill reference
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fill(ref_src);
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return reference::mean_std_normalization_layer(ref_src, epsilon);
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}
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TensorType _target{};
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SimpleTensor<T> _reference{};
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DataType _data_type{};
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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_MEAN_STDDEV_NORMALIZATION_LAYER_FIXTURE */
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