/* * Copyright (c) 2018-2020 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/CLConvolutionLayer.h" #include "arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h" #include "tests/CL/CLAccessor.h" #include "tests/PaddingCalculator.h" #include "tests/datasets/DilatedConvolutionLayerDataset.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/ConvolutionLayerFixture.h" namespace arm_compute { namespace test { namespace validation { namespace { RelativeTolerance rel_tolerance_f32(0.05f); /**< Relative tolerance value for comparing reference's output against implementation's output for DataType::F32 */ RelativeTolerance rel_tolerance_f16(half_float::half(0.2)); /**< Relative tolerance value for comparing reference's output against implementation's output for DataType::F16 */ constexpr AbsoluteTolerance abs_tolerance_qasymm8(1); /**< Relative tolerance value for comparing reference's output against implementation's output for quantized data types */ constexpr float abs_tolerance_f32 = 0.001f; /**< Absolute tolerance value for comparing reference's output against implementation's output for DataType::F32 */ constexpr float abs_tolerance_f16 = 0.3f; /**< Absolute tolerance value for comparing reference's output against implementation's output for DataType::F16 */ constexpr float tolerance_num_f16 = 0.07f; /**< Tolerance number for FP16 */ /** CNN data types */ const auto CNNDataTypes = framework::dataset::make("DataType", { DataType::F16, DataType::F32, DataType::QASYMM8, }); } // namespace TEST_SUITE(CL) TEST_SUITE(DilatedConvolutionLayer) DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( framework::dataset::make("InputInfo", { TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32), TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32), TensorInfo(TensorShape(23U, 27U, 23U, 4U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32), TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32) }), framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32), TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U, 23U, 21U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32), TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16) })), framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32), TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32), TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32), TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32), TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32) })), framework::dataset::make("ConvInfo", { PadStrideInfo(1, 2, 1, 1), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(3, 2, 1, 0) })), framework::dataset::make("GpuTarget", { GPUTarget::BIFROST, GPUTarget::MIDGARD, GPUTarget::G71, GPUTarget::MIDGARD, GPUTarget::BIFROST })), framework::dataset::make("Dilation", { Size2D(1U, 1U), Size2D(1U, 1U), Size2D(1U, 1U), Size2D(2U, 2U), Size2D(3U, 3U) })), framework::dataset::make("Expected", { ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })), input_info, weights_info, output_info, conv_info, gpu_target, dilation, expected) { ConvolutionMethod is_valid = CLConvolutionLayer::get_convolution_method(&input_info.clone()->set_is_resizable(true), &weights_info.clone()->set_is_resizable(true), &output_info.clone()->set_is_resizable(true), conv_info, WeightsInfo(), ActivationLayerInfo(), gpu_target, dilation); ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); } TEST_SUITE_END() TEST_SUITE(GEMMDilatedConvolutionLayer) template using CLGEMMDilatedConvolutionLayerFixture = ConvolutionValidationFixture; TEST_SUITE(Float) TEST_SUITE(FP16) FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.0f, abs_tolerance_f16); } FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMDilatedConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16); } TEST_SUITE_END() TEST_SUITE(FP32) FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(CLAccessor(_target), _reference, rel_tolerance_f32); } FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMDilatedConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); } TEST_SUITE_END() TEST_SUITE_END() template using CLGEMMDilatedConvolutionLayerQuantizedFixture = ConvolutionValidationQuantizedFixture; TEST_SUITE(Quantized) TEST_SUITE(QASYMM8) FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QASYMM8)), framework::dataset::make("DataLayout", { DataLayout::NCHW })), framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), framework::dataset::make("ActivationLayerInfo", { ActivationLayerInfo() }))) { // Validate output validate(CLAccessor(_target), _reference, abs_tolerance_qasymm8); } FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMDilatedConvolutionLayerQuantizedFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QASYMM8)), framework::dataset::make("DataLayout", { DataLayout::NCHW })), framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 0) })), framework::dataset::make("ActivationLayerInfo", { ActivationLayerInfo() }))) { // Validate output validate(CLAccessor(_target), _reference, abs_tolerance_qasymm8); } TEST_SUITE_END() TEST_SUITE_END() TEST_SUITE_END() TEST_SUITE_END() } // namespace validation } // namespace test } // namespace arm_compute