/* * Copyright (c) 2017-2020, 2022 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 "arm_compute/core/Types.h" #include "arm_compute/runtime/NEON/functions/NESoftmaxLayer.h" #include "arm_compute/runtime/Tensor.h" #include "arm_compute/runtime/TensorAllocator.h" #include "src/common/cpuinfo/CpuIsaInfo.h" #include "src/cpu/kernels/CpuSoftmaxKernel.h" #include "tests/NEON/Accessor.h" #include "tests/PaddingCalculator.h" #include "tests/datasets/ShapeDatasets.h" #include "tests/framework/Asserts.h" #include "tests/framework/Macros.h" #include "tests/framework/datasets/Datasets.h" #include "tests/validation/Validation.h" #include "tests/validation/fixtures/SoftmaxLayerFixture.h" namespace arm_compute { namespace test { namespace validation { namespace { /** Tolerance for float operations */ constexpr AbsoluteTolerance tolerance_f32(0.000001f); RelativeTolerance tolerance_f16(half(0.2)); /** Tolerance for quantized operations */ constexpr AbsoluteTolerance tolerance_qasymm8(1); constexpr AbsoluteTolerance tolerance_qasymm8_signed(1); /** CNN data types */ const auto CNNDataTypes = framework::dataset::make("DataType", { #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC DataType::F16, #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ DataType::F32, }); } // namespace TEST_SUITE(NEON) TEST_SUITE(SoftmaxLayer) // *INDENT-OFF* // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U), 1, DataType::F32), // Mismatching data types TensorInfo(TensorShape(27U, 13U), 1, DataType::F32), // Mismatching shapes TensorInfo(TensorShape(27U, 13U), 1, DataType::QASYMM8, // Invalid output quantization info QuantizationInfo(1.f/256, 12)), TensorInfo(TensorShape(32U, 13U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U), 1, DataType::QASYMM8, QuantizationInfo(1.f/256, 12)), TensorInfo(TensorShape(32U, 13U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U), 1, DataType::QASYMM8, //Invalid axis high QuantizationInfo(1.f/256, 12)), TensorInfo(TensorShape(32U, 13U), 1, DataType::QASYMM8, //Invalid axis low QuantizationInfo(1.f/256, 12)), }), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U), 1, DataType::F16), TensorInfo(TensorShape(27U, 11U), 1, DataType::F32), TensorInfo(TensorShape(27U, 13U), 1, DataType::QASYMM8, QuantizationInfo(1.f/256, 12)), TensorInfo(TensorShape(32U, 13U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U), 1, DataType::QASYMM8, QuantizationInfo(1.f/256, 0)), TensorInfo(TensorShape(32U, 13U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U), 1, DataType::QASYMM8, QuantizationInfo(1.f/256, 0)), TensorInfo(TensorShape(32U, 13U), 1, DataType::QASYMM8, QuantizationInfo(1.f/256, 0)), })), framework::dataset::make("beta", { 1.0, 2.0, 1.0, 2.0, 1.0, 1.0, 2.0, 1.0, })), framework::dataset::make("axis", { 0, 0, 0, 1, 0, -1, 2, -3, })), framework::dataset::make("Expected", { false, false, false, true, true, true, false, false })), input_info, output_info, beta, axis, expected) { ARM_COMPUTE_EXPECT(bool(NESoftmaxLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), beta, axis)) == expected, framework::LogLevel::ERRORS); } // clang-format on // *INDENT-ON* template using NESoftmaxLayerFixture = SoftmaxValidationFixture; DATA_TEST_CASE(KernelSelection_max_logits, framework::DatasetMode::ALL, concat( combine(framework::dataset::make("CpuExt", std::string("NEON")), framework::dataset::make("DataType", { DataType::F32, DataType::F16, DataType::QASYMM8, DataType::QASYMM8_SIGNED })), combine(framework::dataset::make("CpuExt", std::string("SVE")), framework::dataset::make("DataType", { DataType::F32, DataType::F16, DataType::QASYMM8, DataType::QASYMM8_SIGNED }))), 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.fp16 = (data_type == DataType::F16); const auto *selected_impl = CpuLogits1DMaxKernel::get_implementation(DataTypeISASelectorData{ data_type, cpu_isa }, cpu::KernelSelectionType::Preferred); ARM_COMPUTE_ERROR_ON_NULLPTR(selected_impl); std::string expected = lower_string(cpu_ext) + "_" + cpu_impl_dt(data_type) + "_logits_1d_max"; std::string actual = selected_impl->name; ARM_COMPUTE_EXPECT_EQUAL(expected, actual, framework::LogLevel::ERRORS); } DATA_TEST_CASE(KernelSelection_logits, 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 })), 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 }))), 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 = CpuLogits1DSoftmaxKernel::get_implementation(DataTypeISASelectorData{ data_type, cpu_isa }, cpu::KernelSelectionType::Preferred); ARM_COMPUTE_ERROR_ON_NULLPTR(selected_impl); std::string expected = lower_string(cpu_ext) + "_" + cpu_impl_dt(data_type) + "_softmax_logits_1d"; std::string actual = selected_impl->name; ARM_COMPUTE_EXPECT_EQUAL(expected, actual, framework::LogLevel::ERRORS); } TEST_SUITE(Float) #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC TEST_SUITE(FP16) FIXTURE_DATA_TEST_CASE(RunSmall, NESoftmaxLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("Beta", { 1.0f, 2.0f })), framework::dataset::make("Axis", { 0, 1 }))) { // Validate output validate(Accessor(_target), _reference, tolerance_f16); } FIXTURE_DATA_TEST_CASE(RunSmall4D, NESoftmaxLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("Beta", { 1.0f, 2.0f })), framework::dataset::make("Axis", { 0, 2, -1 }))) { // Validate output validate(Accessor(_target), _reference, tolerance_f16); } FIXTURE_DATA_TEST_CASE(RunLarge, NESoftmaxLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SoftmaxLayerLargeShapes(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("Beta", { 1.0f, 2.0f })), framework::dataset::make("Axis", { 0 }))) { // Validate output validate(Accessor(_target), _reference, tolerance_f16); } TEST_SUITE_END() //FP16 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ TEST_SUITE(FP32) FIXTURE_DATA_TEST_CASE(RunSmall2D, NESoftmaxLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SoftmaxLayerSmallShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Beta", { 1.0f, 2.0f })), framework::dataset::make("Axis", { 0, -1 }))) { // Validate output validate(Accessor(_target), _reference, tolerance_f32); } FIXTURE_DATA_TEST_CASE(RunSmall4D, NESoftmaxLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Beta", { 1.0f, 2.0f })), framework::dataset::make("Axis", { 0, -2, 3 }))) { // Validate output validate(Accessor(_target), _reference, tolerance_f32); } FIXTURE_DATA_TEST_CASE(RunLarge, NESoftmaxLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SoftmaxLayerLargeShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Beta", { 1.0f, 2.0f })), framework::dataset::make("Axis", { 0 }))) { // Validate output validate(Accessor(_target), _reference, tolerance_f32); } TEST_SUITE_END() //FP32 TEST_SUITE_END() //Float template using NESoftmaxLayerQuantizedFixture = SoftmaxValidationQuantizedFixture; TEST_SUITE(Quantized) TEST_SUITE(QASYMM8) FIXTURE_DATA_TEST_CASE(RunSmall2D, NESoftmaxLayerQuantizedFixture, framework::DatasetMode::ALL, combine(combine(combine(datasets::SoftmaxLayerSmallShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), combine(framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, -10) }), framework::dataset::make("Beta", { 1.0f, 2.f }))), framework::dataset::make("Axis", { 0, -1 }))) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); } FIXTURE_DATA_TEST_CASE(RunSmall4D, NESoftmaxLayerQuantizedFixture, framework::DatasetMode::ALL, combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), combine(framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, -10) }), framework::dataset::make("Beta", { 1.0f, 2.f }))), framework::dataset::make("Axis", { 0, 1, -2 }))) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); } FIXTURE_DATA_TEST_CASE(RunLarge, NESoftmaxLayerQuantizedFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SoftmaxLayerLargeShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), combine(framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, -10) }), framework::dataset::make("Beta", { 1.0f, 2.0f }))), framework::dataset::make("Axis", { 0 }))) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); } TEST_SUITE_END() //QASYMM8 TEST_SUITE(QASYMM8_SIGNED) FIXTURE_DATA_TEST_CASE(RunSmall2D, NESoftmaxLayerQuantizedFixture, framework::DatasetMode::ALL, combine(combine(combine(datasets::SoftmaxLayerSmallShapes(), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), combine(framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, -10) }), framework::dataset::make("Beta", { 1.0f, 2.f }))), framework::dataset::make("Axis", { 0, -1 }))) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8_signed); } FIXTURE_DATA_TEST_CASE(RunSmall4D, NESoftmaxLayerQuantizedFixture, framework::DatasetMode::ALL, combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), combine(framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, -10) }), framework::dataset::make("Beta", { 1.0f, 2.f }))), framework::dataset::make("Axis", { 0, 1, -1 }))) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8_signed); } TEST_SUITE_END() //QASYMM8_SIGNED TEST_SUITE_END() //Quantized TEST_SUITE_END() //SoftmaxLayer TEST_SUITE_END() //NEON } // namespace validation } // namespace test } // namespace arm_compute