/* * Copyright (c) 2017-2020 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/CLFullyConnectedLayer.h" #include "tests/CL/CLAccessor.h" #include "tests/PaddingCalculator.h" #include "tests/datasets/FullyConnectedLayerDataset.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/FullyConnectedLayerFixture.h" namespace arm_compute { namespace test { namespace validation { namespace { /** Tolerance for float operations */ constexpr RelativeTolerance rel_tolerance_f32(0.05f); /**< Relative tolerance value for comparing reference's output against implementation's output for DataType:F32 */ constexpr AbsoluteTolerance abs_tolerance_f32(0.0001f); /**< Absolute tolerance value for comparing reference's output against implementation's output for DataType::F32 */ RelativeTolerance tolerance_f16(half(0.2)); /**< Relative tolerance value for comparing reference's output against implementation's output for DataType::F16 */ constexpr float tolerance_num = 0.07f; /**< Tolerance number */ /** Tolerance for quantized asymmetric operations */ constexpr AbsoluteTolerance tolerance_qasymm8(1); /** CNN data types */ const auto CNNDataTypes = framework::dataset::make("DataType", { DataType::F16, DataType::F32, DataType::QASYMM8, DataType::QASYMM8_SIGNED, }); const auto FullyConnectedParameters = combine(framework::dataset::make("TransposeWeights", { false, true }), framework::dataset::make("ReshapeWeights", { false, true })); const auto QuantizationData = framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255.f, 10), QuantizationInfo(1.1f, 10), }); const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.75f, 0.25f), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH) }); const auto ActivationFunctionsQuantizedDataset = framework::dataset::make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.75f, 0.25f) }); } // namespace TEST_SUITE(CL) TEST_SUITE(FullyConnectedLayer) // *INDENT-OFF* // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( framework::dataset::make("InputInfo", { TensorInfo(TensorShape(9U, 5U, 7U, 3U), 1, DataType::F32), // Mismatching data types TensorInfo(TensorShape(8U, 4U, 6U, 4U), 1, DataType::F32), TensorInfo(TensorShape(8U, 4U, 6U, 4U), 1, DataType::F32), TensorInfo(TensorShape(9U, 5U, 7U, 3U), 1, DataType::F32), // Invalid weights dimensions TensorInfo(TensorShape(9U, 5U, 7U, 3U), 1, DataType::F32), // Wrongly reshaped weights }), framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(315U, 271U), 1, DataType::F16), TensorInfo(TensorShape(192U, 192U), 1, DataType::F32), TensorInfo(TensorShape(192U, 192U), 1, DataType::F32), TensorInfo(TensorShape(217U, 231U), 1, DataType::F32), TensorInfo(TensorShape(217U, 315U), 1, DataType::F32), })), framework::dataset::make("BiasInfo",{ TensorInfo(TensorShape(271U), 1, DataType::F32), TensorInfo(TensorShape(192U), 1, DataType::F32), TensorInfo(TensorShape(192U), 1, DataType::F32), TensorInfo(TensorShape(271U), 1, DataType::F32), TensorInfo(TensorShape(271U), 1, DataType::F32), })), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(271U, 3U), 1, DataType::F32), TensorInfo(TensorShape(192U, 4U), 1, DataType::F32), TensorInfo(TensorShape(192U, 4U), 1, DataType::F32), TensorInfo(TensorShape(271U, 3U), 1, DataType::F32), TensorInfo(TensorShape(271U, 3U), 1, DataType::F32), })), framework::dataset::make("TransposeWeights",{ true, true, false, true, true })), framework::dataset::make("ReshapedWeights",{ false, false, false, false, false})), framework::dataset::make("Expected", { false, true, true, false, false })), input_info, weights_info, bias_info, output_info, transpose_weights, reshaped_weights, expected) { // Create Fully Connected layer info FullyConnectedLayerInfo fc_info; fc_info.transpose_weights = transpose_weights; fc_info.are_weights_reshaped = reshaped_weights; Status status = CLFullyConnectedLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &bias_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), fc_info); ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS); } // clang-format on // *INDENT-ON* template using CLFullyConnectedLayerFixture = FullyConnectedLayerValidationFixture; TEST_SUITE(Float) TEST_SUITE(FP16) FIXTURE_DATA_TEST_CASE(RunSmall, CLFullyConnectedLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallFullyConnectedLayerDataset(), FullyConnectedParameters), framework::dataset::make("DataType", DataType::F16)), ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); } FIXTURE_DATA_TEST_CASE(RunLarge, CLFullyConnectedLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeFullyConnectedLayerDataset(), FullyConnectedParameters), framework::dataset::make("DataType", DataType::F16)), ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); } TEST_SUITE_END() TEST_SUITE(FP32) FIXTURE_DATA_TEST_CASE(RunSmall, CLFullyConnectedLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallFullyConnectedLayerDataset(), FullyConnectedParameters), framework::dataset::make("DataType", DataType::F32)), ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0, abs_tolerance_f32); } FIXTURE_DATA_TEST_CASE(RunLarge, CLFullyConnectedLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeFullyConnectedLayerDataset(), FullyConnectedParameters), framework::dataset::make("DataType", DataType::F32)), ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0, abs_tolerance_f32); } TEST_SUITE_END() TEST_SUITE_END() template using CLFullyConnectedLayerQuantizedFixture = FullyConnectedLayerValidationQuantizedFixture; TEST_SUITE(Quantized) TEST_SUITE(QASYMM8) FIXTURE_DATA_TEST_CASE(RunSmall, CLFullyConnectedLayerQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallFullyConnectedLayerDataset(), FullyConnectedParameters), framework::dataset::make("DataType", DataType::QASYMM8)), QuantizationData), ActivationFunctionsQuantizedDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8); } FIXTURE_DATA_TEST_CASE(RunLarge, CLFullyConnectedLayerQuantizedFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeFullyConnectedLayerDataset(), FullyConnectedParameters), framework::dataset::make("DataType", DataType::QASYMM8)), QuantizationData), ActivationFunctionsQuantizedDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8); } TEST_SUITE_END() /* QASYMM8 */ TEST_SUITE(QASYMM8_SIGNED) FIXTURE_DATA_TEST_CASE(RunSmall, CLFullyConnectedLayerQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallFullyConnectedLayerDataset(), FullyConnectedParameters), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), QuantizationData), ActivationFunctionsQuantizedDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8); } TEST_SUITE_END() /* QASYMM8_SIGNED */ TEST_SUITE_END() /* Quantized */ TEST_SUITE_END() TEST_SUITE_END() } // namespace validation } // namespace test } // namespace arm_compute