/* * Copyright (c) 2017-2021 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/CL/CLTensor.h" #include "arm_compute/runtime/CL/CLTensorAllocator.h" #include "arm_compute/runtime/CL/functions/CLReductionOperation.h" #include "tests/CL/CLAccessor.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/ReductionOperationFixture.h" namespace arm_compute { namespace test { namespace validation { namespace { /** Tolerance for float operations */ AbsoluteTolerance tolerance_f32(0.001f); RelativeTolerance rel_tolerance_f32(0.00001f); AbsoluteTolerance tolerance_f16(0.5f); RelativeTolerance rel_tolerance_f16(0.2f); /** Tolerance for quantized operations */ RelativeTolerance tolerance_qasymm8(1); const auto ReductionOperationsSumProdMean = framework::dataset::make("ReductionOperationsSumProdMean", { ReductionOperation::SUM, ReductionOperation::PROD, ReductionOperation::MEAN_SUM }); const auto ReductionOperationsMinMax = framework::dataset::make("ReductionMinMax", { ReductionOperation::MIN, ReductionOperation::MAX, }); const auto KeepDimensions = framework::dataset::make("KeepDims", { true, false }); } // namespace TEST_SUITE(CL) TEST_SUITE(ReductionOperation) // *INDENT-OFF* // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( framework::dataset::make("InputInfo", { TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Mismatching data type input/output TensorInfo(TensorShape(128U, 64U), 3, DataType::F32), // Number of Input channels != 1 TensorInfo(TensorShape(128U, 64U), 1, DataType::S16), // DataType != QASYMM8/F16/F32 TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Axis >= num_max_dimensions TensorInfo(TensorShape(128U, 64U), 1, DataType::QASYMM8), // Axis == 0 and SUM_SQUARE and QASYMM8 TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), TensorInfo(TensorShape(128U, 64U), 1, DataType::F32) // Kept Dimension when keep_dims = false }), framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(1U, 64U), 1, DataType::F16), TensorInfo(TensorShape(1U, 64U), 1, DataType::F32), TensorInfo(TensorShape(1U, 64U), 1, DataType::S16), TensorInfo(TensorShape(1U, 64U), 1, DataType::F32), TensorInfo(TensorShape(1U, 64U), 1, DataType::QASYMM8), TensorInfo(TensorShape(1U, 64U), 1, DataType::F32), TensorInfo(TensorShape(1U, 64U), 1, DataType::F32) })), framework::dataset::make("Axis", { 0U, 0U, 0U, static_cast(TensorShape::num_max_dimensions), 1U, 0U, 0U })), framework::dataset::make("KeepDims", { true, true, true, true, true, true, false })), framework::dataset::make("Expected", { false, false, false, false, false, true , false })), input_info, output_info, axis, keep_dims, expected) { bool is_valid = bool(CLReductionOperation::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(true), axis, ReductionOperation::SUM_SQUARE, keep_dims)); ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); } // clang-format on // *INDENT-ON* template using CLReductionOperationFixture = ReductionOperationFixture; TEST_SUITE(Float) TEST_SUITE(FP16) FIXTURE_DATA_TEST_CASE(RunSmall4D, CLReductionOperationFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), concat(ReductionOperationsSumProdMean, ReductionOperationsMinMax)), KeepDimensions)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f16); } FIXTURE_DATA_TEST_CASE(RunLarge, CLReductionOperationFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), concat(ReductionOperationsSumProdMean, ReductionOperationsMinMax)), KeepDimensions)) { // Validate output validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0, tolerance_f16); } TEST_SUITE_END() // F16 TEST_SUITE(FP32) FIXTURE_DATA_TEST_CASE(RunSmall4D, CLReductionOperationFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), concat(ReductionOperationsSumProdMean, ReductionOperationsMinMax)), KeepDimensions)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); } FIXTURE_DATA_TEST_CASE(RunLarge, CLReductionOperationFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), concat(ReductionOperationsSumProdMean, ReductionOperationsMinMax)), KeepDimensions)) { // Validate output validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0, tolerance_f32); } TEST_SUITE_END() // F32 TEST_SUITE_END() // Float template using CLReductionOperationQuantizedFixture = ReductionOperationQuantizedFixture; TEST_SUITE(Quantized) TEST_SUITE(QASYMM8) FIXTURE_DATA_TEST_CASE(RunSmall, CLReductionOperationQuantizedFixture, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), ReductionOperationsSumProdMean), framework::dataset::make("QuantizationInfo", QuantizationInfo(1.f / 64, 2))), KeepDimensions)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8); } FIXTURE_DATA_TEST_CASE(RunSmallMinMax, CLReductionOperationQuantizedFixture, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), ReductionOperationsMinMax), framework::dataset::make("QuantizationInfo", QuantizationInfo(1.f / 64, 2))), KeepDimensions)) { // Validate output validate(CLAccessor(_target), _reference); } TEST_SUITE_END() // QASYMM8 TEST_SUITE(QASYMM8_SIGNED) FIXTURE_DATA_TEST_CASE(RunSmall, CLReductionOperationQuantizedFixture, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), ReductionOperationsSumProdMean), framework::dataset::make("QuantizationInfo", QuantizationInfo(1.f / 64, 2))), KeepDimensions)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8); } FIXTURE_DATA_TEST_CASE(RunSmallMinMax, CLReductionOperationQuantizedFixture, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), ReductionOperationsMinMax), framework::dataset::make("QuantizationInfo", QuantizationInfo(1.f / 64, 2))), KeepDimensions)) { // Validate output validate(CLAccessor(_target), _reference); } TEST_SUITE_END() // QASYMM8_SIGNED TEST_SUITE_END() // Quantized TEST_SUITE_END() // Reduction TEST_SUITE_END() // CL } // namespace validation } // namespace test } // namespace arm_compute