diff options
Diffstat (limited to 'tests/validation')
-rw-r--r-- | tests/validation/CL/ActivationLayer.cpp | 282 | ||||
-rw-r--r-- | tests/validation/NEON/ActivationLayer.cpp | 328 | ||||
-rw-r--r-- | tests/validation/Reference.cpp | 50 | ||||
-rw-r--r-- | tests/validation/Reference.h | 10 | ||||
-rw-r--r-- | tests/validation/ReferenceCPP.cpp | 8 | ||||
-rw-r--r-- | tests/validation/ReferenceCPP.h | 7 | ||||
-rw-r--r-- | tests/validation/TensorOperations.h | 103 | ||||
-rw-r--r-- | tests/validation/TensorVisitors.h | 20 |
8 files changed, 0 insertions, 808 deletions
diff --git a/tests/validation/CL/ActivationLayer.cpp b/tests/validation/CL/ActivationLayer.cpp deleted file mode 100644 index a1e00b681b..0000000000 --- a/tests/validation/CL/ActivationLayer.cpp +++ /dev/null @@ -1,282 +0,0 @@ -/* - * Copyright (c) 2017 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. - */ -#include "AssetsLibrary.h" -#include "CL/CLAccessor.h" -#include "Globals.h" -#include "PaddingCalculator.h" -#include "TypePrinter.h" -#include "Utils.h" -#include "validation/Datasets.h" -#include "validation/Helpers.h" -#include "validation/Reference.h" -#include "validation/Validation.h" - -#include "arm_compute/core/Helpers.h" -#include "arm_compute/core/Types.h" -#include "arm_compute/runtime/CL/CLTensor.h" -#include "arm_compute/runtime/CL/CLTensorAllocator.h" -#include "arm_compute/runtime/CL/functions/CLActivationLayer.h" - -#include "boost_wrapper.h" - -#include <random> -#include <string> -#include <tuple> - -using namespace arm_compute; -using namespace arm_compute::test; -using namespace arm_compute::test::validation; - -namespace -{ -/** Define tolerance of the activation layer - * - * @param[in] activation The activation function used. - * @param[in] fixed_point_position Number of bits for the fractional part.. - * - * @return Tolerance depending on the activation function. - */ -float activation_layer_tolerance(ActivationLayerInfo::ActivationFunction activation, int fixed_point_position = 0) -{ - switch(activation) - { - case ActivationLayerInfo::ActivationFunction::LOGISTIC: - case ActivationLayerInfo::ActivationFunction::SOFT_RELU: - case ActivationLayerInfo::ActivationFunction::SQRT: - case ActivationLayerInfo::ActivationFunction::TANH: - return (fixed_point_position != 0) ? 5.f : 0.00001f; - break; - default: - return 0.f; - } -} - -/** Compute CL activation layer function. - * - * @param[in] in_place Compute the activation layer in-place. - * @param[in] shape Shape of the input and output tensors. - * @param[in] dt Shape Data type of tensors. - * @param[in] act_info Activation layer information. - * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of fixed point numbers. - * - * @return Computed output tensor. - */ -CLTensor compute_activation_layer(bool in_place, const TensorShape &shape, DataType dt, ActivationLayerInfo act_info, int fixed_point_position = 0) -{ - // Create tensors - CLTensor src = create_tensor<CLTensor>(shape, dt, 1, fixed_point_position); - CLTensor dst = create_tensor<CLTensor>(shape, dt, 1, fixed_point_position); - - // Create and configure function - CLActivationLayer act_layer; - - if(in_place) - { - act_layer.configure(&src, nullptr, act_info); - } - else - { - act_layer.configure(&src, &dst, act_info); - } - - // Allocate tensors - src.allocator()->allocate(); - BOOST_TEST(!src.info()->is_resizable()); - - if(!in_place) - { - dst.allocator()->allocate(); - BOOST_TEST(!dst.info()->is_resizable()); - } - - // Fill tensors - if(dt == DataType::F32) - { - float min_bound = 0; - float max_bound = 0; - std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<float>(act_info.activation()); - std::uniform_real_distribution<> distribution(min_bound, max_bound); - library->fill(CLAccessor(src), distribution, 0); - } - else - { - int min_bound = 0; - int max_bound = 0; - if(dt == DataType::QS8) - { - std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<int8_t>(act_info.activation(), fixed_point_position); - } - else - { - std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<int16_t>(act_info.activation(), fixed_point_position); - } - std::uniform_int_distribution<> distribution(min_bound, max_bound); - library->fill(CLAccessor(src), distribution, 0); - } - - // Compute function - act_layer.run(); - - if(in_place) - { - return src; - } - else - { - return dst; - } -} -} // namespace - -#ifndef DOXYGEN_SKIP_THIS -BOOST_AUTO_TEST_SUITE(CL) -BOOST_AUTO_TEST_SUITE(ActivationLayer) - -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly")) -BOOST_DATA_TEST_CASE(Configuration, boost::unit_test::data::make({ false, true }) * (SmallShapes() + LargeShapes()) * CNNDataTypes(), in_place, shape, dt) -{ - // Set fixed point position data type allowed - const int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0; - - // Create tensors - CLTensor src = create_tensor<CLTensor>(shape, dt, 1, fixed_point_position); - CLTensor dst = create_tensor<CLTensor>(shape, dt, 1, fixed_point_position); - - BOOST_TEST(src.info()->is_resizable()); - BOOST_TEST(dst.info()->is_resizable()); - - // Create and configure function - CLActivationLayer act_layer; - - if(in_place) - { - act_layer.configure(&src, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::ABS)); - } - else - { - act_layer.configure(&src, &dst, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::ABS)); - } - - // Validate valid region - const ValidRegion valid_region = shape_to_valid_region(shape); - validate(src.info()->valid_region(), valid_region); - - if(!in_place) - { - validate(dst.info()->valid_region(), valid_region); - } - - // Validate padding - const int step = 16 / arm_compute::data_size_from_type(dt); - const PaddingSize padding = PaddingCalculator(shape.x(), step).required_padding(); - validate(src.info()->padding(), padding); - - if(!in_place) - { - validate(dst.info()->padding(), padding); - } -} - -BOOST_AUTO_TEST_SUITE(Float) -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) -BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * CNNFloatDataTypes() * ActivationFunctions() * boost::unit_test::data::make({ 0.5f, 1.f }), - in_place, shape, dt, act_function, alpha_beta) -{ - // Create activation layer info - ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta); - - // Compute function - CLTensor dst = compute_activation_layer(in_place, shape, dt, act_info); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, dt, act_info); - - // Validate output - validate(CLAccessor(dst), ref_dst, activation_layer_tolerance(act_function)); -} - -BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly")) -BOOST_DATA_TEST_CASE(RunLarge, boost::unit_test::data::make({ false, true }) * LargeShapes() * CNNFloatDataTypes() * ActivationFunctions() * boost::unit_test::data::make({ 0.5f, 1.f }), - in_place, shape, dt, act_function, alpha_beta) -{ - // Create activation layer info - ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta); - - // Compute function - CLTensor dst = compute_activation_layer(in_place, shape, dt, act_info); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, dt, act_info); - - // Validate output - validate(CLAccessor(dst), ref_dst, activation_layer_tolerance(act_function)); -} -BOOST_AUTO_TEST_SUITE_END() - -/** @note We test for fixed point precision [3,5] because [1,2] and [6,7] ranges - * cause overflowing issues in most of the transcendentals functions. - */ -BOOST_AUTO_TEST_SUITE(Quantized) -BOOST_AUTO_TEST_SUITE(QS8) -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) -BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * ActivationFunctions() * boost::unit_test::data::xrange(3, 6, 1) * boost::unit_test::data::make({ 0.5f, 1.f }), - in_place, shape, act_function, fixed_point_position, alpha_beta) -{ - // Create activation layer info - ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta); - - // Compute function - CLTensor dst = compute_activation_layer(in_place, shape, DataType::QS8, act_info, fixed_point_position); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, DataType::QS8, act_info, fixed_point_position); - - // Validate output - validate(CLAccessor(dst), ref_dst, activation_layer_tolerance(act_function, fixed_point_position)); -} -BOOST_AUTO_TEST_SUITE_END() - -BOOST_AUTO_TEST_SUITE(QS16) -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) -BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * ActivationFunctions() * boost::unit_test::data::xrange(3, 14, 1) * boost::unit_test::data::make({ 0.5f, 1.f }), - in_place, shape, act_function, fixed_point_position, alpha_beta) -{ - // Create activation layer info - ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta); - - // Compute function - CLTensor dst = compute_activation_layer(in_place, shape, DataType::QS16, act_info, fixed_point_position); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, DataType::QS16, act_info, fixed_point_position); - - // Validate output - validate(CLAccessor(dst), ref_dst, activation_layer_tolerance(act_function, fixed_point_position)); -} -BOOST_AUTO_TEST_SUITE_END() -BOOST_AUTO_TEST_SUITE_END() - -BOOST_AUTO_TEST_SUITE_END() -BOOST_AUTO_TEST_SUITE_END() -#endif /* DOXYGEN_SKIP_THIS */
\ No newline at end of file diff --git a/tests/validation/NEON/ActivationLayer.cpp b/tests/validation/NEON/ActivationLayer.cpp deleted file mode 100644 index 5f1a2c6fb6..0000000000 --- a/tests/validation/NEON/ActivationLayer.cpp +++ /dev/null @@ -1,328 +0,0 @@ -/* - * Copyright (c) 2017 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. - */ -#include "AssetsLibrary.h" -#include "Globals.h" -#include "NEON/Accessor.h" -#include "PaddingCalculator.h" -#include "TypePrinter.h" -#include "Utils.h" -#include "validation/Datasets.h" -#include "validation/Helpers.h" -#include "validation/Reference.h" -#include "validation/Validation.h" - -#include "arm_compute/core/Helpers.h" -#include "arm_compute/core/Types.h" -#include "arm_compute/runtime/NEON/functions/NEActivationLayer.h" -#include "arm_compute/runtime/Tensor.h" -#include "arm_compute/runtime/TensorAllocator.h" - -#include "boost_wrapper.h" - -#include <random> -#include <string> -#include <tuple> - -using namespace arm_compute; -using namespace arm_compute::test; -using namespace arm_compute::test::validation; - -namespace -{ -/** Define tolerance of the activation layer - * - * @param[in] dt The data type used. - * @param[in] activation The activation function used. - * @param[in] fixed_point_position Number of bits for the fractional part.. - * - * @return Tolerance depending on the activation function. - */ -float activation_layer_tolerance(DataType dt, ActivationLayerInfo::ActivationFunction activation, int fixed_point_position = 0) -{ - switch(activation) - { - case ActivationLayerInfo::ActivationFunction::LOGISTIC: - case ActivationLayerInfo::ActivationFunction::SOFT_RELU: - case ActivationLayerInfo::ActivationFunction::SQRT: - case ActivationLayerInfo::ActivationFunction::TANH: - switch(dt) - { - case DataType::QS8: - return 5.f; - case DataType::QS16: - return 11.f; - case DataType::F16: - return 0.01f; - default: - return 0.00001f; - } - break; - default: - return 0.f; - } -} - -/** Compute Neon activation layer function. - * - * @param[in] in_place Compute the activation layer in-place. - * @param[in] shape Shape of the input and output tensors. - * @param[in] dt Shape Data type of tensors. - * @param[in] act_info Activation layer information. - * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of fixed point numbers. - * - * @return Computed output tensor. - */ -Tensor compute_activation_layer(bool in_place, const TensorShape &shape, DataType dt, ActivationLayerInfo act_info, int fixed_point_position = 0) -{ - // Create tensors - Tensor src = create_tensor<Tensor>(shape, dt, 1, fixed_point_position); - Tensor dst = create_tensor<Tensor>(shape, dt, 1, fixed_point_position); - - // Create and configure function - NEActivationLayer act_layer; - - if(in_place) - { - act_layer.configure(&src, nullptr, act_info); - } - else - { - act_layer.configure(&src, &dst, act_info); - } - - // Allocate tensors - src.allocator()->allocate(); - BOOST_TEST(!src.info()->is_resizable()); - - if(!in_place) - { - dst.allocator()->allocate(); - BOOST_TEST(!dst.info()->is_resizable()); - } - // Fill tensors - switch(dt) - { - case DataType::QS8: - { - const std::pair<int8_t, int8_t> bounds = get_activation_layer_test_bounds<int8_t>(act_info.activation(), fixed_point_position); - std::uniform_int_distribution<> distribution(bounds.first, bounds.second); - library->fill(Accessor(src), distribution, 0); - break; - } - case DataType::QS16: - { - const std::pair<int16_t, int16_t> bounds = get_activation_layer_test_bounds<int16_t>(act_info.activation(), fixed_point_position); - std::uniform_int_distribution<> distribution(bounds.first, bounds.second); - library->fill(Accessor(src), distribution, 0); - break; - } -#ifdef ARM_COMPUTE_ENABLE_FP16 - case DataType::F16: - { - const std::pair<float16_t, float16_t> bounds = get_activation_layer_test_bounds<float16_t>(act_info.activation()); - std::uniform_real_distribution<> distribution(bounds.first, bounds.second); - library->fill(Accessor(src), distribution, 0); - break; - } -#endif /* ARM_COMPUTE_ENABLE_FP16 */ - case DataType::F32: - { - const std::pair<float, float> bounds = get_activation_layer_test_bounds<float>(act_info.activation()); - std::uniform_real_distribution<> distribution(bounds.first, bounds.second); - library->fill(Accessor(src), distribution, 0); - break; - } - default: - { - ARM_COMPUTE_ERROR("Not supported"); - break; - } - } - - // Compute function - act_layer.run(); - - if(in_place) - { - return src; - } - else - { - return dst; - } -} -} // namespace - -#ifndef DOXYGEN_SKIP_THIS -BOOST_AUTO_TEST_SUITE(NEON) -BOOST_AUTO_TEST_SUITE(ActivationLayer) - -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly")) -BOOST_DATA_TEST_CASE(Configuration, boost::unit_test::data::make({ false, true }) * (SmallShapes() + LargeShapes()) * CNNDataTypes(), in_place, shape, dt) -{ - // Set fixed point position data type allowed - const int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0; - - // Create tensors - Tensor src = create_tensor<Tensor>(shape, dt, 1, fixed_point_position); - Tensor dst = create_tensor<Tensor>(shape, dt, 1, fixed_point_position); - - BOOST_TEST(src.info()->is_resizable()); - BOOST_TEST(dst.info()->is_resizable()); - - // Create and configure function - NEActivationLayer act_layer; - - if(in_place) - { - act_layer.configure(&src, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::ABS)); - } - else - { - act_layer.configure(&src, &dst, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::ABS)); - } - - // Validate valid region - const ValidRegion valid_region = shape_to_valid_region(shape); - validate(src.info()->valid_region(), valid_region); - - if(!in_place) - { - validate(dst.info()->valid_region(), valid_region); - } - - // Validate padding - const PaddingSize padding = PaddingCalculator(shape.x(), 16).required_padding(); - validate(src.info()->padding(), padding); - - if(!in_place) - { - validate(dst.info()->padding(), padding); - } -} - -#ifdef ARM_COMPUTE_ENABLE_FP16 -BOOST_AUTO_TEST_SUITE(Float16) -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) -BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * boost::unit_test::data::make(DataType::F16) * ActivationFunctions() * boost::unit_test::data::make({ 0.5f, 1.f }), - in_place, shape, dt, act_function, alpha_beta) -{ - // Create activation layer info - const ActivationLayerInfo act_info(act_function, alpha_beta); - - // Compute function - Tensor dst = compute_activation_layer(in_place, shape, dt, act_info); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, dt, act_info); - - // Validate output - validate(Accessor(dst), ref_dst, activation_layer_tolerance(dt, act_function)); -} -BOOST_AUTO_TEST_SUITE_END() -#endif /* ARM_COMPUTE_ENABLE_FP16 */ - -BOOST_AUTO_TEST_SUITE(Float) -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) -BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * CNNFloatDataTypes() * ActivationFunctions() * boost::unit_test::data::make({ 0.5f, 1.f }), - in_place, shape, dt, act_function, alpha_beta) -{ - // Create activation layer info - ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta); - - // Compute function - Tensor dst = compute_activation_layer(in_place, shape, dt, act_info); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, dt, act_info); - - // Validate output - validate(Accessor(dst), ref_dst, activation_layer_tolerance(dt, act_function)); -} - -BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly")) -BOOST_DATA_TEST_CASE(RunLarge, boost::unit_test::data::make({ false, true }) * LargeShapes() * CNNFloatDataTypes() * ActivationFunctions() * boost::unit_test::data::make({ 0.5f, 1.f }), - in_place, shape, dt, act_function, alpha_beta) -{ - // Create activation layer info - ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta); - - // Compute function - Tensor dst = compute_activation_layer(in_place, shape, dt, act_info); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, dt, act_info); - - // Validate output - validate(Accessor(dst), ref_dst, activation_layer_tolerance(dt, act_function)); -} -BOOST_AUTO_TEST_SUITE_END() - -/** @note We test for fixed point precision [3,5] because [1,2] and [6,7] ranges - * cause overflowing issues in most of the transcendentals functions. - */ -BOOST_AUTO_TEST_SUITE(Quantized) -BOOST_AUTO_TEST_SUITE(QS8) -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) -BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * ActivationFunctions() * boost::unit_test::data::xrange(3, 6, 1) * boost::unit_test::data::make({ 0.5f, 1.f }), - in_place, shape, act_function, fixed_point_position, alpha_beta) -{ - // Create activation layer info - ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta); - - // Compute function - Tensor dst = compute_activation_layer(in_place, shape, DataType::QS8, act_info, fixed_point_position); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, DataType::QS8, act_info, fixed_point_position); - - // Validate output - validate(Accessor(dst), ref_dst, activation_layer_tolerance(DataType::QS8, act_function, fixed_point_position)); -} -BOOST_AUTO_TEST_SUITE_END() - -BOOST_AUTO_TEST_SUITE(QS16) -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) -BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * ActivationFunctions() * boost::unit_test::data::xrange(3, 14, 1) * boost::unit_test::data::make({ 0.5f, 1.f }), - in_place, shape, act_function, fixed_point_position, alpha_beta) -{ - // Create activation layer info - ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta); - - // Compute function - Tensor dst = compute_activation_layer(in_place, shape, DataType::QS16, act_info, fixed_point_position); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, DataType::QS16, act_info, fixed_point_position); - - // Validate output - validate(Accessor(dst), ref_dst, activation_layer_tolerance(DataType::QS16, act_function, fixed_point_position)); -} -BOOST_AUTO_TEST_SUITE_END() - -BOOST_AUTO_TEST_SUITE_END() - -BOOST_AUTO_TEST_SUITE_END() -BOOST_AUTO_TEST_SUITE_END() -#endif /* DOXYGEN_SKIP_THIS */ diff --git a/tests/validation/Reference.cpp b/tests/validation/Reference.cpp index f9052f1dba..011fd091f2 100644 --- a/tests/validation/Reference.cpp +++ b/tests/validation/Reference.cpp @@ -453,56 +453,6 @@ RawTensor Reference::compute_reference_threshold(const TensorShape &shape, uint8 return ref_dst; } -RawTensor Reference::compute_reference_activation_layer(const TensorShape &shape, DataType dt, ActivationLayerInfo act_info, int fixed_point_position) -{ - // Create reference - RawTensor ref_src(shape, dt, 1, fixed_point_position); - RawTensor ref_dst(shape, dt, 1, fixed_point_position); - - // Fill tensors - switch(dt) - { - case DataType::QS8: - { - const std::pair<int8_t, int8_t> bounds = get_activation_layer_test_bounds<int8_t>(act_info.activation(), fixed_point_position); - std::uniform_int_distribution<> distribution(bounds.first, bounds.second); - library->fill(ref_src, distribution, 0); - break; - } - case DataType::QS16: - { - const std::pair<int16_t, int16_t> bounds = get_activation_layer_test_bounds<int16_t>(act_info.activation(), fixed_point_position); - std::uniform_int_distribution<> distribution(bounds.first, bounds.second); - library->fill(ref_src, distribution, 0); - break; - } - case DataType::F16: - { - const std::pair<half_float::half, half_float::half> bounds = get_activation_layer_test_bounds<half_float::half>(act_info.activation()); - std::uniform_real_distribution<> distribution(bounds.first, bounds.second); - library->fill(ref_src, distribution, 0); - break; - } - case DataType::F32: - { - const std::pair<float, float> bounds = get_activation_layer_test_bounds<float>(act_info.activation()); - std::uniform_real_distribution<> distribution(bounds.first, bounds.second); - library->fill(ref_src, distribution, 0); - break; - } - default: - { - ARM_COMPUTE_ERROR("Not supported"); - break; - } - } - - // Compute reference - ReferenceCPP::activation_layer(ref_src, ref_dst, act_info); - - return ref_dst; -} - RawTensor Reference::compute_reference_batch_normalization_layer(const TensorShape &shape0, const TensorShape &shape1, DataType dt, float epsilon, int fixed_point_position) { // Create reference diff --git a/tests/validation/Reference.h b/tests/validation/Reference.h index eeaa55c739..42c62f8d6a 100644 --- a/tests/validation/Reference.h +++ b/tests/validation/Reference.h @@ -295,16 +295,6 @@ public: * @return Computed raw tensor. */ static RawTensor compute_reference_threshold(const TensorShape &shape, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper); - /** Compute reference activation layer. - * - * @param[in] shape Shape of the input and output tensors. - * @param[in] dt Data type of the tensors. - * @param[in] act_info Activation layer information. - * @param[in] fixed_point_position (Optional)Number of bits for the fractional part of fixed point numbers. - * - * @return Computed raw tensor. - */ - static RawTensor compute_reference_activation_layer(const TensorShape &shape, DataType dt, ActivationLayerInfo act_info, int fixed_point_position = 0); /** Compute reference batch normalization layer. * * @param[in] shape0 Shape of the input and output tensors. diff --git a/tests/validation/ReferenceCPP.cpp b/tests/validation/ReferenceCPP.cpp index 81ec60d5b9..117fd5bebb 100644 --- a/tests/validation/ReferenceCPP.cpp +++ b/tests/validation/ReferenceCPP.cpp @@ -283,14 +283,6 @@ void ReferenceCPP::threshold(const RawTensor &src, RawTensor &dst, uint8_t thres tensor_operations::threshold(s, d, threshold, false_value, true_value, type, upper); } -// Activation layer -void ReferenceCPP::activation_layer(const RawTensor &input, RawTensor &output, ActivationLayerInfo act_info) -{ - const TensorVariant s = TensorFactory::get_tensor(input); - TensorVariant d = TensorFactory::get_tensor(output); - boost::apply_visitor(tensor_visitors::activation_layer_visitor(s, act_info), d); -} - // Batch Normalization Layer void ReferenceCPP::batch_normalization_layer(const RawTensor &src, RawTensor &dst, const RawTensor &mean, const RawTensor &var, const RawTensor &beta, const RawTensor &gamma, float epsilon, int fixed_point_position) diff --git a/tests/validation/ReferenceCPP.h b/tests/validation/ReferenceCPP.h index 97e573cfa2..0d1bea48bd 100644 --- a/tests/validation/ReferenceCPP.h +++ b/tests/validation/ReferenceCPP.h @@ -253,13 +253,6 @@ public: * @param[in] upper Upper threshold. Only used when the thresholding type is RANGE. */ static void threshold(const RawTensor &src, RawTensor &dst, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper); - /** Activation layer of @p src base on information from @p act_info. - * - * @param[in] input Input tensor. - * @param[in] output Second tensor. - * @param[out] act_info Activation layer information. - */ - static void activation_layer(const RawTensor &input, RawTensor &output, ActivationLayerInfo act_info); /** Batch Normalization of @p src based on the information from @p norm_info. * * @param[in] src Input tensor. diff --git a/tests/validation/TensorOperations.h b/tests/validation/TensorOperations.h index b472e3d5cf..db145c19ad 100644 --- a/tests/validation/TensorOperations.h +++ b/tests/validation/TensorOperations.h @@ -935,109 +935,6 @@ void threshold(const Tensor<T> &in, Tensor<T> &out, uint8_t threshold, uint8_t f } } -// Activation Layer for floating point type -template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type * = nullptr> -void activation_layer(const Tensor<T> &in, Tensor<T> &out, ActivationLayerInfo act_info) -{ - const T a = static_cast<T>(act_info.a()); - const T b = static_cast<T>(act_info.b()); - - for(int i = 0; i < in.num_elements(); ++i) - { - T x = in[i]; - switch(act_info.activation()) - { - case ActivationLayerInfo::ActivationFunction::ABS: - out[i] = std::abs(x); - break; - case ActivationLayerInfo::ActivationFunction::LINEAR: - out[i] = a * x + b; - break; - case ActivationLayerInfo::ActivationFunction::LOGISTIC: - out[i] = static_cast<T>(1) / (static_cast<T>(1) + std::exp(-x)); - break; - case ActivationLayerInfo::ActivationFunction::RELU: - out[i] = std::max(static_cast<T>(0), x); - break; - case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU: - out[i] = std::min<T>(a, std::max(static_cast<T>(0), x)); - break; - case ActivationLayerInfo::ActivationFunction::LEAKY_RELU: - out[i] = (x > 0) ? x : a * x; - break; - case ActivationLayerInfo::ActivationFunction::SOFT_RELU: - out[i] = std::log(static_cast<T>(1) + std::exp(x)); - break; - case ActivationLayerInfo::ActivationFunction::SQRT: - out[i] = std::sqrt(x); - break; - case ActivationLayerInfo::ActivationFunction::SQUARE: - out[i] = x * x; - break; - case ActivationLayerInfo::ActivationFunction::TANH: - out[i] = a * std::tanh(b * x); - break; - default: - ARM_COMPUTE_ERROR("Activation function not recognised"); - break; - } - } -} - -// Activation Layer for fixed point type -template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type * = nullptr> -void activation_layer(const Tensor<T> &in, Tensor<T> &out, ActivationLayerInfo act_info) -{ - using namespace fixed_point_arithmetic; - int fixed_point_position = in.fixed_point_position(); - ActivationLayerInfo::ActivationFunction act_func = act_info.activation(); - const fixed_point<T> a(act_info.a(), fixed_point_position); - const fixed_point<T> b(act_info.b(), fixed_point_position); - const fixed_point<T> const_0(0, fixed_point_position); - const fixed_point<T> const_1(1, fixed_point_position); - - for(int i = 0; i < in.num_elements(); ++i) - { - fixed_point<T> x(in[i], fixed_point_position, true); - switch(act_func) - { - case ActivationLayerInfo::ActivationFunction::ABS: - out[i] = abs(x).raw(); - break; - case ActivationLayerInfo::ActivationFunction::LINEAR: - out[i] = add(b, mul(a, x)).raw(); - break; - case ActivationLayerInfo::ActivationFunction::LOGISTIC: - out[i] = (const_1 / (const_1 + exp(-x))).raw(); - break; - case ActivationLayerInfo::ActivationFunction::RELU: - out[i] = max(const_0, x).raw(); - break; - case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU: - out[i] = min(a, max(const_0, x)).raw(); - break; - case ActivationLayerInfo::ActivationFunction::LEAKY_RELU: - out[i] = (x > const_0) ? x.raw() : mul(a, x).raw(); - break; - case ActivationLayerInfo::ActivationFunction::SOFT_RELU: - out[i] = log(const_1 + exp(x)).raw(); - break; - case ActivationLayerInfo::ActivationFunction::SQRT: - out[i] = (const_1 / inv_sqrt(x)).raw(); - break; - case ActivationLayerInfo::ActivationFunction::SQUARE: - out[i] = mul(x, x).raw(); - break; - case ActivationLayerInfo::ActivationFunction::TANH: - out[i] = mul(a, tanh(mul(b, x))).raw(); - break; - default: - ARM_COMPUTE_ERROR("Activation function not recognised"); - break; - } - } -} - // Batch Normalization Layer for fixed point type template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type * = nullptr> void batch_normalization_layer(const Tensor<T> &in, Tensor<T> &out, const Tensor<T> &mean, const Tensor<T> &var, const Tensor<T> &beta, const Tensor<T> &gamma, float epsilon, int fixed_point_position) diff --git a/tests/validation/TensorVisitors.h b/tests/validation/TensorVisitors.h index 44ae6f13e8..365aac7758 100644 --- a/tests/validation/TensorVisitors.h +++ b/tests/validation/TensorVisitors.h @@ -228,26 +228,6 @@ private: template struct arm_compute::test::validation::tensor_visitors::table_lookup<uint8_t>; template struct arm_compute::test::validation::tensor_visitors::table_lookup<int16_t>; -// Activation layer visitor -struct activation_layer_visitor : public boost::static_visitor<> -{ -public: - explicit activation_layer_visitor(const TensorVariant &in, ActivationLayerInfo act_info) - : _in(in), _act_info(act_info) - { - } - - template <typename T> - void operator()(Tensor<T> &out) const - { - const auto &in = boost::get<Tensor<T>>(_in); - tensor_operations::activation_layer(in, out, _act_info); - } - -private: - const TensorVariant &_in; - const ActivationLayerInfo _act_info; -}; // Batch Normalization Layer visitor struct batch_normalization_layer_visitor : public boost::static_visitor<> { |