155 lines
6.2 KiB
C++
155 lines
6.2 KiB
C++
/*
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* Copyright (c) 2017-2020 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_SOFTMAX_LAYER_FIXTURE
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#define ARM_COMPUTE_TEST_SOFTMAX_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/reference/SoftmaxLayer.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, bool IS_LOG = false>
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class SoftmaxValidationGenericFixture : 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 data_type, QuantizationInfo quantization_info, float beta, size_t axis)
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{
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_quantization_info = quantization_info;
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_reference = compute_reference(shape, data_type, quantization_info, beta, axis);
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_target = compute_target(shape, data_type, quantization_info, beta, axis);
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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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if(!is_data_type_quantized(tensor.data_type()))
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{
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std::uniform_real_distribution<> distribution(-10.f, 10.f);
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library->fill(tensor, distribution, 0);
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}
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else // data type is quantized_asymmetric (signed or unsigned)
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{
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std::uniform_int_distribution<> distribution(0, 100);
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library->fill(tensor, distribution, 0);
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}
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}
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TensorType compute_target(const TensorShape &shape, DataType data_type,
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QuantizationInfo quantization_info, float beta, int32_t axis)
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{
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// Create tensors
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TensorType src = create_tensor<TensorType>(shape, data_type, 1, quantization_info);
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TensorType dst = create_tensor<TensorType>(shape, data_type, 1, get_softmax_output_quantization_info(data_type, IS_LOG));
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// Create and configure function
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FunctionType smx_layer;
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smx_layer.configure(&src, &dst, beta, axis);
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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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smx_layer.run();
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return dst;
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}
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SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type,
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QuantizationInfo quantization_info, float beta, int32_t axis)
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{
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// Create reference
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SimpleTensor<T> src{ shape, data_type, 1, quantization_info };
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// Fill reference
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fill(src);
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return reference::softmax_layer<T>(src, beta, axis, IS_LOG);
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}
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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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template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool IS_LOG = false>
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class SoftmaxValidationFixture : public SoftmaxValidationGenericFixture<TensorType, AccessorType, FunctionType, T, IS_LOG>
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{
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public:
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template <typename...>
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void setup(TensorShape shape, DataType data_type, float beta, size_t axis)
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{
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SoftmaxValidationGenericFixture<TensorType, AccessorType, FunctionType, T, IS_LOG>::setup(shape,
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data_type,
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QuantizationInfo(),
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beta,
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axis);
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}
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};
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template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool IS_LOG = false>
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class SoftmaxValidationQuantizedFixture : public SoftmaxValidationGenericFixture<TensorType, AccessorType, FunctionType, T, IS_LOG>
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{
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public:
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template <typename...>
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void setup(TensorShape shape, DataType data_type, QuantizationInfo quantization_info, float beta, size_t axis)
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{
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SoftmaxValidationGenericFixture<TensorType, AccessorType, FunctionType, T, IS_LOG>::setup(shape,
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data_type,
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quantization_info,
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beta,
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axis);
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}
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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_SOFTMAX_LAYER_FIXTURE */
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