diff options
author | Pablo Tello <pablo.tello@arm.com> | 2017-07-05 11:32:17 +0100 |
---|---|---|
committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-09-17 14:16:42 +0100 |
commit | 91654c45cf1de5f41127536a0fdd310c17fdfc8e (patch) | |
tree | 1cf914061c456282f0ba899ebbdc591cabc7f0fc /tests | |
parent | ec69f93dc63408933d322ec27d0b7049b9a6e07c (diff) | |
download | ComputeLibrary-91654c45cf1de5f41127536a0fdd310c17fdfc8e.tar.gz |
COMPMID-421: Added FP16 support in ActivationLayer.
Change-Id: I7ba573b19d56e3c87996edb5218a00e5bfca451e
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/79755
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Diffstat (limited to 'tests')
-rw-r--r-- | tests/benchmark_new/NEON/ActivationLayer.cpp | 20 | ||||
-rw-r--r-- | tests/validation/Helpers.h | 13 | ||||
-rw-r--r-- | tests/validation/NEON/ActivationLayer.cpp | 73 | ||||
-rw-r--r-- | tests/validation/Reference.cpp | 51 | ||||
-rw-r--r-- | tests/validation/TensorOperations.h | 4 |
5 files changed, 114 insertions, 47 deletions
diff --git a/tests/benchmark_new/NEON/ActivationLayer.cpp b/tests/benchmark_new/NEON/ActivationLayer.cpp index 47838f43ba..21e4369aa2 100644 --- a/tests/benchmark_new/NEON/ActivationLayer.cpp +++ b/tests/benchmark_new/NEON/ActivationLayer.cpp @@ -37,23 +37,31 @@ namespace arm_compute { namespace test { +namespace +{ +#ifdef ARM_COMPUTE_ENABLE_FP16 +const auto alexnet_data_types = framework::dataset::make("DataType", { DataType::QS8, DataType::F16, DataType::F32 }); +const auto lenet_data_types = framework::dataset::make("DataType", { DataType::F16, DataType::F32 }); +#else /* ARM_COMPUTE_ENABLE_FP16 */ +const auto alexnet_data_types = framework::dataset::make("DataType", { DataType::QS8, DataType::F32 }); +const auto lenet_data_types = framework::dataset::make("DataType", { DataType::F32 }); +#endif /* ARM_COMPUTE_ENABLE_FP16 */ +} // namespace + using NEActivationLayerFixture = ActivationLayerFixture<Tensor, NEActivationLayer, neon::NEAccessor>; TEST_SUITE(NEON) REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetActivationLayer, NEActivationLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::AlexNetActivationLayerDataset(), - framework::dataset::make("DataType", { DataType::F32, DataType::QS8 })), + framework::dataset::combine(framework::dataset::combine(datasets::AlexNetActivationLayerDataset(), alexnet_data_types), framework::dataset::make("Batches", { 1, 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ActivationLayer, NEActivationLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ActivationLayerDataset(), - framework::dataset::make("DataType", DataType::F32)), + framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ActivationLayerDataset(), lenet_data_types), framework::dataset::make("Batches", { 1, 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetActivationLayer, NEActivationLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetActivationLayerDataset(), - framework::dataset::make("DataType", DataType::F32)), + framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetActivationLayerDataset(), lenet_data_types), framework::dataset::make("Batches", { 1, 4, 8 }))); TEST_SUITE_END() diff --git a/tests/validation/Helpers.h b/tests/validation/Helpers.h index 4ee2112bcc..191e32813c 100644 --- a/tests/validation/Helpers.h +++ b/tests/validation/Helpers.h @@ -35,6 +35,10 @@ #include <utility> #include <vector> +#ifdef ARM_COMPUTE_ENABLE_FP16 +#include <arm_fp16.h> +#endif /* ARM_COMPUTE_ENABLE_FP16 */ + namespace arm_compute { namespace test @@ -49,9 +53,13 @@ namespace validation * @return A pair containing the lower upper testing bounds for a given function. */ template <typename T> -std::pair<T, T> get_activation_layer_test_bounds(ActivationLayerInfo::ActivationFunction activation, int fixed_point_position = 1) +inline std::pair<T, T> get_activation_layer_test_bounds(ActivationLayerInfo::ActivationFunction activation, int fixed_point_position = 1) { - bool is_float = std::is_floating_point<T>::value; + bool is_float = std::is_same<T, float>::value; +#ifdef ARM_COMPUTE_ENABLE_FP16 + is_float = is_float || std::is_same<T, float16_t>::value; +#endif /* ARM_COMPUTE_ENABLE_FP16 */ + std::pair<T, T> bounds; // Set initial values @@ -98,7 +106,6 @@ std::pair<T, T> get_activation_layer_test_bounds(ActivationLayerInfo::Activation } return bounds; } - /** Helper function to get the testing range for batch normalization layer. * * @param[in] fixed_point_position (Optional) Number of bits for the fractional part. Defaults to 1. diff --git a/tests/validation/NEON/ActivationLayer.cpp b/tests/validation/NEON/ActivationLayer.cpp index 2b24fd5175..b8827a5324 100644 --- a/tests/validation/NEON/ActivationLayer.cpp +++ b/tests/validation/NEON/ActivationLayer.cpp @@ -73,6 +73,8 @@ float activation_layer_tolerance(DataType dt, ActivationLayerInfo::ActivationFun return 5.f; case DataType::QS16: return 11.f; + case DataType::F16: + return 0.01f; default: return 0.00001f; } @@ -119,30 +121,44 @@ Tensor compute_activation_layer(bool in_place, const TensorShape &shape, DataTyp 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(NEAccessor(src), distribution, 0); - } - else + switch(dt) { - int min_bound = 0; - int max_bound = 0; - if(dt == DataType::QS8) + 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(NEAccessor(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(NEAccessor(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(NEAccessor(src), distribution, 0); + break; + } +#endif /* ARM_COMPUTE_ENABLE_FP16 */ + case DataType::F32: { - std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<int8_t>(act_info.activation(), fixed_point_position); + 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(NEAccessor(src), distribution, 0); + break; } - else + default: { - std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<int16_t>(act_info.activation(), fixed_point_position); + ARM_COMPUTE_ERROR("Not supported"); + break; } - std::uniform_int_distribution<> distribution(min_bound, max_bound); - library->fill(NEAccessor(src), distribution, 0); } // Compute function @@ -207,6 +223,27 @@ BOOST_DATA_TEST_CASE(Configuration, boost::unit_test::data::make({ false, true } } } +#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(NEAccessor(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 }), diff --git a/tests/validation/Reference.cpp b/tests/validation/Reference.cpp index 3b429c1ee6..0ce25c5567 100644 --- a/tests/validation/Reference.cpp +++ b/tests/validation/Reference.cpp @@ -459,29 +459,44 @@ RawTensor Reference::compute_reference_activation_layer(const TensorShape &shape RawTensor ref_src = library->get(shape, dt, 1, fixed_point_position); RawTensor ref_dst = library->get(shape, dt, 1, fixed_point_position); - // Fill reference - 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(ref_src, distribution, 0); - } - else + // Fill tensors + switch(dt) { - int min_bound = 0; - int max_bound = 0; - if(dt == DataType::QS8) + case DataType::QS8: { - std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<int8_t>(act_info.activation(), fixed_point_position); + 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; } - else + case DataType::QS16: { - std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<int16_t>(act_info.activation(), fixed_point_position); + 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; + } +#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(ref_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(ref_src, distribution, 0); + break; + } + default: + { + ARM_COMPUTE_ERROR("Not supported"); + break; } - std::uniform_int_distribution<> distribution(min_bound, max_bound); - library->fill(ref_src, distribution, 0); } // Compute reference diff --git a/tests/validation/TensorOperations.h b/tests/validation/TensorOperations.h index 9e201e2f04..67dadd6da3 100644 --- a/tests/validation/TensorOperations.h +++ b/tests/validation/TensorOperations.h @@ -569,7 +569,7 @@ void box3x3(const Tensor<T> &in, Tensor<T> &out, BorderMode border_mode, T const } // Depth conversion -template < typename T1, typename T2, typename std::enable_if < std::is_integral<T1>::value &&std::is_floating_point<T2>::value, int >::type = 0 > +template < typename T1, typename T2, typename std::enable_if < std::is_integral<T1>::value &&is_floating_point<T2>::value, int >::type = 0 > void depth_convert(const Tensor<T1> &in, Tensor<T2> &out, ConvertPolicy policy, uint32_t shift) { using namespace fixed_point_arithmetic; @@ -581,7 +581,7 @@ void depth_convert(const Tensor<T1> &in, Tensor<T2> &out, ConvertPolicy policy, } } -template < typename T1, typename T2, typename std::enable_if < std::is_floating_point<T1>::value &&std::is_integral<T2>::value, int >::type = 0 > +template < typename T1, typename T2, typename std::enable_if < is_floating_point<T1>::value &&std::is_integral<T2>::value, int >::type = 0 > void depth_convert(const Tensor<T1> &in, Tensor<T2> &out, ConvertPolicy policy, uint32_t shift) { using namespace fixed_point_arithmetic; |