diff options
Diffstat (limited to 'tests/validation/NEON/ActivationLayer.cpp')
| -rw-r--r-- | tests/validation/NEON/ActivationLayer.cpp | 132 |
1 files changed, 114 insertions, 18 deletions
diff --git a/tests/validation/NEON/ActivationLayer.cpp b/tests/validation/NEON/ActivationLayer.cpp index 577603d07d..73f5de68ac 100644 --- a/tests/validation/NEON/ActivationLayer.cpp +++ b/tests/validation/NEON/ActivationLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2021 Arm Limited. + * Copyright (c) 2017-2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -23,10 +23,13 @@ */ #include "arm_compute/core/Types.h" #include "arm_compute/core/utils/misc/Traits.h" +#include "arm_compute/core/utils/StringUtils.h" #include "arm_compute/runtime/NEON/functions/NEActivationLayer.h" #include "arm_compute/runtime/RuntimeContext.h" #include "arm_compute/runtime/Tensor.h" #include "arm_compute/runtime/TensorAllocator.h" +#include "src/common/cpuinfo/CpuIsaInfo.h" +#include "src/cpu/kernels/CpuActivationKernel.h" #include "tests/NEON/Accessor.h" #include "tests/PaddingCalculator.h" #include "tests/datasets/ActivationFunctionsDataset.h" @@ -37,7 +40,8 @@ #include "tests/validation/Validation.h" #include "tests/validation/fixtures/ActivationLayerFixture.h" -#include "support/Requires.h" +#include "arm_compute/Acl.hpp" +#include "support/AclRequires.h" namespace arm_compute { @@ -65,14 +69,16 @@ RelativeTolerance<float> relative_tolerance(DataType data_type, ActivationLayerI case ActivationLayerInfo::ActivationFunction::SQRT: case ActivationLayerInfo::ActivationFunction::TANH: case ActivationLayerInfo::ActivationFunction::HARD_SWISH: + case ActivationLayerInfo::ActivationFunction::SWISH: + case ActivationLayerInfo::ActivationFunction::GELU: switch(data_type) { case DataType::F16: -#if defined(__ARM_FEATURE_SVE) +#if defined(ENABLE_SVE) return RelativeTolerance<float>(0.25f); -#else // !defined(__ARM_FEATURE_SVE) +#else // !defined(ENABLE_SVE) return RelativeTolerance<float>(0.1f); -#endif // defined(__ARM_FEATURE_SVE) +#endif // defined(ENABLE_SVE) default: return RelativeTolerance<float>(0.05f); } @@ -80,11 +86,11 @@ RelativeTolerance<float> relative_tolerance(DataType data_type, ActivationLayerI switch(data_type) { case DataType::F16: -#if defined(__ARM_FEATURE_SVE) +#if defined(ENABLE_SVE) return RelativeTolerance<float>(0.9f); -#else // !defined(__ARM_FEATURE_SVE) +#else // !defined(ENABLE_SVE) return RelativeTolerance<float>(0.01f); -#endif // defined(__ARM_FEATURE_SVE) +#endif // defined(ENABLE_SVE) default: return RelativeTolerance<float>(0.00001f); } @@ -107,15 +113,16 @@ AbsoluteTolerance<float> absolute_tolerance(DataType data_type, ActivationLayerI case ActivationLayerInfo::ActivationFunction::LOGISTIC: case ActivationLayerInfo::ActivationFunction::SQRT: case ActivationLayerInfo::ActivationFunction::TANH: + case ActivationLayerInfo::ActivationFunction::SWISH: case ActivationLayerInfo::ActivationFunction::HARD_SWISH: switch(data_type) { case DataType::F16: -#if defined(__ARM_FEATURE_SVE) +#if defined(ENABLE_SVE) return AbsoluteTolerance<float>(0.25f); -#else // !defined(__ARM_FEATURE_SVE) +#else // !defined(ENABLE_SVE) return AbsoluteTolerance<float>(0.01f); -#endif // defined(__ARM_FEATURE_SVE) +#endif // defined(ENABLE_SVE) default: return AbsoluteTolerance<float>(0.00001f); } @@ -123,11 +130,11 @@ AbsoluteTolerance<float> absolute_tolerance(DataType data_type, ActivationLayerI switch(data_type) { case DataType::F16: -#if defined(__ARM_FEATURE_SVE) +#if defined(ENABLE_SVE) return AbsoluteTolerance<float>(0.9f); -#else // !defined(__ARM_FEATURE_SVE) +#else // !defined(ENABLE_SVE) return AbsoluteTolerance<float>(0.01f); -#endif // defined(__ARM_FEATURE_SVE) +#endif // defined(ENABLE_SVE) default: return AbsoluteTolerance<float>(0.00001f); } @@ -169,7 +176,8 @@ const auto CNNDataTypes = framework::dataset::make("DataType", DataType::F32, }); -const auto NeonActivationFunctionsDataset = concat(datasets::ActivationFunctions(), framework::dataset::make("ActivationFunction", ActivationLayerInfo::ActivationFunction::HARD_SWISH)); +const auto NeonActivationFunctionsDataset = concat(datasets::ActivationFunctions(), + framework::dataset::make("ActivationFunction", { ActivationLayerInfo::ActivationFunction::HARD_SWISH, ActivationLayerInfo::ActivationFunction::SWISH })); /** Input data sets. */ const auto ActivationDataset = combine(combine(framework::dataset::make("InPlace", { false, true }), NeonActivationFunctionsDataset), framework::dataset::make("AlphaBeta", { 0.5f, 1.f })); @@ -215,6 +223,48 @@ void test_float_sqrt_boundary_value() TEST_SUITE(NEON) TEST_SUITE(ActivationLayer) +/** Test case for memory injection in @ref cpu::CpuWinogradConv2d. + * + * Configure the operator once and inject memory at run-time in multiple executions. + * + * Checks performed in order: + * - Both runs compute the same output + */ +TEST_CASE(ActivationAPI, framework::DatasetMode::ALL) +{ + acl::StatusCode err = acl::StatusCode::Success; + + // Create context & Queue + acl::Context ctx(acl::Target::Cpu, &err); + ARM_COMPUTE_ASSERT(err == acl::StatusCode::Success); + + acl::Queue queue(ctx, &err); + ARM_COMPUTE_ASSERT(err == acl::StatusCode::Success); + + // Create activation operator + acl::TensorDescriptor src_info({ 2, 3 }, acl::DataType::Float32); + acl::TensorDescriptor dst_info({ 2, 3 }, acl::DataType::Float32); + acl::ActivationDesc desc{ AclRelu, 6.f, 0.f, false }; + + acl::Activation act(ctx, src_info, dst_info, desc, &err); + ARM_COMPUTE_ASSERT(err == acl::StatusCode::Success); + + // Create tensors and feed + acl::Tensor src(ctx, src_info, &err); + ARM_COMPUTE_ASSERT(err == acl::StatusCode::Success); + acl::Tensor dst(ctx, dst_info, &err); + ARM_COMPUTE_ASSERT(err == acl::StatusCode::Success); + + acl::TensorPack pack(ctx); + err = pack.add(src, ACL_SRC); + err = pack.add(dst, ACL_DST); + ARM_COMPUTE_ASSERT(err == acl::StatusCode::Success); + + // Execute operator + err = act.run(queue, pack); + ARM_COMPUTE_ASSERT(err == acl::StatusCode::Success); +} + // *INDENT-OFF* // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( @@ -236,6 +286,49 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( bool is_valid = bool(NEActivationLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), act_info)); ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); } + +DATA_TEST_CASE(KernelSelection, framework::DatasetMode::ALL, concat(concat( + combine(framework::dataset::make("CpuExt", std::string("NEON")), + framework::dataset::make("DataType", { DataType::F32, + DataType::F16, + DataType::QASYMM8, + DataType::QASYMM8_SIGNED, + DataType::QSYMM16 + })), + combine(framework::dataset::make("CpuExt", std::string("SVE")), + framework::dataset::make("DataType", { DataType::F32, + DataType::F16, + }))), + combine(framework::dataset::make("CpuExt", std::string("SVE2")), + framework::dataset::make("DataType", { DataType::QASYMM8, + DataType::QASYMM8_SIGNED, + DataType::QSYMM16 + }))), + cpu_ext, data_type) +{ + using namespace cpu::kernels; + + cpuinfo::CpuIsaInfo cpu_isa{}; + cpu_isa.neon = (cpu_ext == "NEON"); + cpu_isa.sve = (cpu_ext == "SVE"); + cpu_isa.sve2 = (cpu_ext == "SVE2"); + cpu_isa.fp16 = (data_type == DataType::F16); + + const auto *selected_impl = CpuActivationKernel::get_implementation(ActivationDataTypeISASelectorData{data_type, CPUModel::GENERIC, cpu_isa,ActivationLayerInfo::ActivationFunction::BOUNDED_RELU}, cpu::KernelSelectionType::Preferred); + + ARM_COMPUTE_ERROR_ON_NULLPTR(selected_impl); + std::string expected = lower_string(cpu_ext) + "_" + cpu_impl_dt(data_type) + "_activation"; + if( data_type == DataType::QASYMM8 || data_type == DataType::QASYMM8_SIGNED) + { +#ifdef __aarch64__ + expected = "neon_q8_activation_lut"; +#else // __aarch64__ + expected = lower_string(cpu_ext) + "_" + cpu_impl_dt(data_type) + "_activation"; +#endif // __aarch64__ + } + std::string actual = selected_impl->name; + ARM_COMPUTE_EXPECT_EQUAL(expected, actual, framework::LogLevel::ERRORS); +} // clang-format on // *INDENT-ON* @@ -316,9 +409,12 @@ FIXTURE_DATA_TEST_CASE(RunSmall, NEActivationLayerQuantizedFixture<int8_t>, fram TEST_SUITE_END() // QASYMM8_SIGNED /** Input data sets. */ -const auto Int16QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationFunction", { ActivationLayerInfo::ActivationFunction::LOGISTIC, - ActivationLayerInfo::ActivationFunction::TANH - }); +const auto Int16QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationFunction", +{ + ActivationLayerInfo::ActivationFunction::LOGISTIC, + ActivationLayerInfo::ActivationFunction::TANH, + ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, +}); const auto Int16QuantizedActivationDataset = combine(combine(framework::dataset::make("InPlace", { false }), Int16QuantizedActivationFunctionsDataset), framework::dataset::make("AlphaBeta", { 0.5f, 1.f })); |