| /* |
| * Copyright (c) 2017-2018 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 */ |
| RelativeTolerance<float> tolerance_f32(0.05f); |
| RelativeTolerance<half_float::half> tolerance_f16(half(0.2)); |
| constexpr float tolerance_num = 0.07f; /**< Tolerance number */ |
| |
| /** Tolerance for quantized asymmetric operations */ |
| constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); |
| |
| /** CNN data types */ |
| const auto CNNDataTypes = framework::dataset::make("DataType", |
| { |
| DataType::F16, |
| DataType::F32, |
| DataType::QASYMM8, |
| }); |
| |
| const auto FullyConnectedParameters = combine(framework::dataset::make("TransposeWeights", { false, true }), framework::dataset::make("ReshapeWeights", { false, true })); |
| } // namespace |
| |
| TEST_SUITE(CL) |
| TEST_SUITE(FullyConnectedLayer) |
| |
| DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallFullyConnectedLayerDataset(), datasets::LargeFullyConnectedLayerDataset()), |
| FullyConnectedParameters), |
| CNNDataTypes), |
| src_shape, weights_shape, bias_shape, dst_shape, transpose_weights, reshape_weights, data_type) |
| { |
| const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type; |
| const QuantizationInfo quantization_info = is_data_type_quantized_asymmetric(data_type) ? QuantizationInfo(2.f / 255.f, 127) : QuantizationInfo(); |
| |
| TensorShape ws(weights_shape); |
| |
| // Transpose weights if not done in the function |
| if(!reshape_weights || !transpose_weights) |
| { |
| const size_t shape_x = ws.x(); |
| ws.set(0, ws.y()); |
| ws.set(1, shape_x); |
| } |
| |
| // Create tensors |
| CLTensor src = create_tensor<CLTensor>(src_shape, data_type, 1, quantization_info); |
| CLTensor weights = create_tensor<CLTensor>(ws, data_type, 1, quantization_info); |
| CLTensor bias = create_tensor<CLTensor>(bias_shape, bias_data_type, 1, quantization_info); |
| CLTensor dst = create_tensor<CLTensor>(dst_shape, data_type, 1, quantization_info); |
| |
| ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); |
| |
| const QuantizationInfo src_quantization_info = src.info()->quantization_info(); |
| const QuantizationInfo weights_quantization_info = weights.info()->quantization_info(); |
| |
| // Create Fully Connected layer info |
| FullyConnectedLayerInfo fc_info; |
| fc_info.transpose_weights = transpose_weights; |
| fc_info.are_weights_reshaped = !reshape_weights; |
| |
| // Create and configure function. |
| CLFullyConnectedLayer fc; |
| fc.configure(&src, &weights, &bias, &dst, fc_info); |
| |
| // Validate valid region |
| const ValidRegion dst_valid_region = shape_to_valid_region(dst_shape); |
| validate(dst.info()->valid_region(), dst_valid_region); |
| |
| // Validate QuantizationInfo |
| ARM_COMPUTE_EXPECT(src.info()->quantization_info() == src_quantization_info, framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(weights.info()->quantization_info() == weights_quantization_info, framework::LogLevel::ERRORS); |
| } |
| |
| // *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 <typename T> |
| using CLFullyConnectedLayerFixture = FullyConnectedLayerValidationFixture<CLTensor, CLAccessor, CLFullyConnectedLayer, T, false>; |
| |
| TEST_SUITE(Float) |
| TEST_SUITE(FP16) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLFullyConnectedLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallFullyConnectedLayerDataset(), |
| FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::F16))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLFullyConnectedLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeFullyConnectedLayerDataset(), |
| FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::F16))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); |
| } |
| TEST_SUITE_END() |
| |
| TEST_SUITE(FP32) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLFullyConnectedLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallFullyConnectedLayerDataset(), FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::F32))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_f32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLFullyConnectedLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeFullyConnectedLayerDataset(), FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::F32))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_f32); |
| } |
| TEST_SUITE_END() |
| TEST_SUITE_END() |
| |
| template <typename T> |
| using CLFullyConnectedLayerQuantizedFixture = FullyConnectedLayerValidationQuantizedFixture<CLTensor, CLAccessor, CLFullyConnectedLayer, T, false>; |
| |
| TEST_SUITE(Quantized) |
| TEST_SUITE(QASYMM8) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLFullyConnectedLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine( |
| combine(datasets::SmallFullyConnectedLayerDataset(), |
| FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255.f, 10) }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLFullyConnectedLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine( |
| combine(datasets::LargeFullyConnectedLayerDataset(), |
| FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 256.f, 10) }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| TEST_SUITE_END() |
| TEST_SUITE_END() |
| |
| TEST_SUITE_END() |
| TEST_SUITE_END() |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |