/* * Copyright (c) 2019-2021 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/CLPReluLayer.h" #include "tests/CL/CLAccessor.h" #include "tests/PaddingCalculator.h" #include "tests/datasets/ConvertPolicyDataset.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/ElementwiseOperationsFixture.h" namespace arm_compute { namespace test { namespace validation { namespace { RelativeTolerance tolerance_fp32(0.000001f); RelativeTolerance tolerance_fp16(0.001f); /** Input data sets **/ const auto PReluLayerU8Dataset = combine(combine(framework::dataset::make("DataType", DataType::U8), framework::dataset::make("DataType", DataType::U8)), framework::dataset::make("DataType", DataType::U8)); const auto PReluLayerQASYMM8Dataset = combine(combine(framework::dataset::make("DataType", DataType::QASYMM8), framework::dataset::make("DataType", DataType::QASYMM8)), framework::dataset::make("DataType", DataType::QASYMM8)); const auto PReluLayerQASYMM8SIGNEDDataset = combine(combine(framework::dataset::make("DataType", DataType::QASYMM8_SIGNED), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)); const auto PReluLayerS16Dataset = combine(combine(framework::dataset::make("DataType", { DataType::U8, DataType::S16 }), framework::dataset::make("DataType", DataType::S16)), framework::dataset::make("DataType", DataType::S16)); const auto PReluLayerFP16Dataset = combine(combine(framework::dataset::make("DataType", DataType::F16), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("DataType", DataType::F16)); const auto PReluLayerFP32Dataset = combine(combine(framework::dataset::make("DataType", DataType::F32), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("DataType", DataType::F32)); } // namespace TEST_SUITE(CL) TEST_SUITE(PReluLayer) // *INDENT-OFF* // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( framework::dataset::make("Input1Info", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), // Invalid data type combination TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching shapes }), framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), })), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), })), framework::dataset::make("Expected", { true, true, false, false})), input1_info, input2_info, output_info, expected) { ARM_COMPUTE_EXPECT(bool(CLPReluLayer::validate(&input1_info.clone()->set_is_resizable(false), &input2_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS); } // clang-format on // *INDENT-ON* TEST_SUITE(InPlace) TEST_CASE(Validate, framework::DatasetMode::ALL) { // PRelu operaotr should be able to take nullptr as output and do the in-place computation. // Shape and data type are selected randomly since they shouldn't matter const auto tensor_info = TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32); const auto result = arm_compute::CLPReluLayer::validate(&tensor_info, &tensor_info, nullptr); ARM_COMPUTE_EXPECT(bool(result) == true, framework::LogLevel::ERRORS); } SimpleTensor compute_float_reference(const TensorInfo &tensor_info) { SimpleTensor ref_src1{ tensor_info.tensor_shape(), tensor_info.data_type() }; SimpleTensor ref_src2{ tensor_info.tensor_shape(), tensor_info.data_type() }; SimpleTensor ref_dst{ tensor_info.tensor_shape(), tensor_info.data_type() }; library->fill_tensor_uniform(ref_src1, 0); library->fill_tensor_uniform(ref_src2, 1); return reference::arithmetic_operation(ArithmeticOperation::PRELU, ref_src1, ref_src2, ref_dst); } void compute_float_target_in_place(CLTensor &src1, CLTensor &src2, bool use_nullptr_output) { auto fn = arm_compute::CLPReluLayer{}; fn.configure(&src1, &src2, use_nullptr_output ? nullptr : &src1); src1.allocator()->allocate(); src2.allocator()->allocate(); library->fill_tensor_uniform(CLAccessor(src1), 0); library->fill_tensor_uniform(CLAccessor(src2), 1); fn.run(); } TEST_CASE(ComputeWithNullPtr, framework::DatasetMode::ALL) { const auto tensor_info = TensorInfo(TensorShape(33U, 13U, 2U), 1, DataType::F32); auto src1 = create_tensor(tensor_info); auto src2 = create_tensor(tensor_info); compute_float_target_in_place(src1, src2, true); validate(CLAccessor(src1), compute_float_reference(tensor_info)); } TEST_CASE(ComputeWithSameTensor, framework::DatasetMode::ALL) { const auto tensor_info = TensorInfo(TensorShape(33U, 13U, 2U), 1, DataType::F32); auto src1 = create_tensor(tensor_info); auto src2 = create_tensor(tensor_info); compute_float_target_in_place(src1, src2, false); validate(CLAccessor(src1), compute_float_reference(tensor_info)); } TEST_SUITE_END() // InPlace template using CLPReluLayerFixture = PReluLayerValidationFixture; TEST_SUITE(U8) FIXTURE_DATA_TEST_CASE(RunSmall, CLPReluLayerFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), PReluLayerU8Dataset)) { // Validate output validate(CLAccessor(_target), _reference); } TEST_SUITE_END() template using CLPReluLayerQuantizedFixture = PReluLayerValidationQuantizedFixture; TEST_SUITE(Quantized) TEST_SUITE(QASYMM8) FIXTURE_DATA_TEST_CASE(RunSmall, CLPReluLayerQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapes(), PReluLayerQASYMM8Dataset), framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) })), framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255.f, 5) })) ) { // Validate output validate(CLAccessor(_target), _reference); } TEST_SUITE_END() TEST_SUITE(QASYMM8_SIGNED) FIXTURE_DATA_TEST_CASE(RunSmall, CLPReluLayerQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapes(), PReluLayerQASYMM8SIGNEDDataset), framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 127.f, 20) })), framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 127.f, 10) })), framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 127.f, 5) })) ) { // Validate output validate(CLAccessor(_target), _reference); } TEST_SUITE_END() TEST_SUITE_END() TEST_SUITE(S16) FIXTURE_DATA_TEST_CASE(RunSmall, CLPReluLayerFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), PReluLayerS16Dataset)) { // Validate output validate(CLAccessor(_target), _reference); } FIXTURE_DATA_TEST_CASE(RunOneDimensional, CLPReluLayerFixture, framework::DatasetMode::ALL, combine(framework::dataset::make("Shape", TensorShape(1U, 16U)), PReluLayerS16Dataset)) { // Validate output validate(CLAccessor(_target), _reference); } TEST_SUITE_END() TEST_SUITE(Float) TEST_SUITE(FP16) FIXTURE_DATA_TEST_CASE(RunSmall, CLPReluLayerFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), PReluLayerFP16Dataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fp16, 0.01); } TEST_SUITE_END() TEST_SUITE(FP32) FIXTURE_DATA_TEST_CASE(RunSmall, CLPReluLayerFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), PReluLayerFP32Dataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fp32); } template using CLPReluLayerBroadcastFixture = PReluLayerBroadcastValidationFixture; FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, CLPReluLayerBroadcastFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapesBroadcast(), PReluLayerFP32Dataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fp32); } TEST_SUITE_END() TEST_SUITE_END() TEST_SUITE_END() TEST_SUITE_END() } // namespace validation } // namespace test } // namespace arm_compute