| /* | |
| * 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<float> tolerance_f32(0.001f); | |
| RelativeTolerance<float> rel_tolerance_f32(0.00001f); | |
| AbsoluteTolerance<float> tolerance_f16(0.5f); | |
| RelativeTolerance<float> rel_tolerance_f16(0.2f); | |
| /** Tolerance for quantized operations */ | |
| RelativeTolerance<float> 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<unsigned int>(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 <typename T> | |
| using CLReductionOperationFixture = ReductionOperationFixture<CLTensor, CLAccessor, CLReductionOperation, T>; | |
| TEST_SUITE(Float) | |
| TEST_SUITE(FP16) | |
| FIXTURE_DATA_TEST_CASE(RunSmall4D, CLReductionOperationFixture<half>, 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<half>, 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<float>, 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<float>, 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 <typename T> | |
| using CLReductionOperationQuantizedFixture = ReductionOperationQuantizedFixture<CLTensor, CLAccessor, CLReductionOperation, T>; | |
| TEST_SUITE(Quantized) | |
| TEST_SUITE(QASYMM8) | |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLReductionOperationQuantizedFixture<uint8_t>, 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<uint8_t>, 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<int8_t>, 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<int8_t>, 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 |