| /* |
| * 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 CONCLCTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| * SOFTWARE. |
| */ |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| #include "arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h" |
| #include "arm_compute/runtime/Tensor.h" |
| #include "arm_compute/runtime/TensorAllocator.h" |
| #include "tests/NEON/Accessor.h" |
| #include "tests/PaddingCalculator.h" |
| #include "tests/datasets/DepthwiseConvolutionLayerDataset.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/DepthwiseConvolutionLayerFixture.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| using namespace arm_compute::misc::shape_calculator; |
| |
| namespace |
| { |
| constexpr RelativeTolerance<float> tolerance_f32(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */ |
| constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QASYMM8 */ |
| |
| const auto depth_multipliers = framework::dataset::make("DepthMultiplier", { 1, 2, 3 }); |
| } // namespace |
| |
| TEST_SUITE(NEON) |
| TEST_SUITE(DepthwiseConvLayer) |
| |
| DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallDepthwiseConvolutionLayerDataset3x3(), |
| datasets::LargeDepthwiseConvolutionLayerDataset3x3()), |
| depth_multipliers), |
| framework::dataset::make("DataType", DataType::F32)), |
| input_shape, kernel_size, info, depth_multiplier, data_type) |
| { |
| // Get shapes |
| TensorShape weights_shape(kernel_size.width, kernel_size.height); |
| |
| const TensorInfo in_info(input_shape, 1, data_type); |
| const TensorInfo we_info(weights_shape, 1, data_type); |
| const TensorShape output_shape = compute_depthwise_convolution_shape(in_info, we_info, info, depth_multiplier); |
| |
| weights_shape.set(2, output_shape.z()); |
| |
| // Create tensors |
| Tensor src = create_tensor<Tensor>(input_shape, data_type); |
| Tensor dst = create_tensor<Tensor>(output_shape, data_type); |
| Tensor weights = create_tensor<Tensor>(weights_shape, data_type); |
| const TensorShape bias_shape(weights_shape[2]); |
| Tensor bias = create_tensor<Tensor>(bias_shape, data_type); |
| |
| ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(dst.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); |
| |
| // Create and configure function |
| NEDepthwiseConvolutionLayer3x3 depthwise_layer; |
| depthwise_layer.configure(&src, &weights, &bias, &dst, info, depth_multiplier); |
| |
| // Validate valid region |
| const ValidRegion input_valid_region = shape_to_valid_region(input_shape); |
| const ValidRegion output_valid_region = shape_to_valid_region(output_shape); |
| const ValidRegion weights_valid_region = shape_to_valid_region(weights_shape); |
| const ValidRegion bias_valid_region = shape_to_valid_region(bias_shape); |
| |
| validate(src.info()->valid_region(), input_valid_region); |
| validate(dst.info()->valid_region(), output_valid_region); |
| validate(weights.info()->valid_region(), weights_valid_region); |
| validate(bias.info()->valid_region(), bias_valid_region); |
| |
| // Validate padding |
| bool is_optimized_run = NEDepthwiseConvolutionLayer3x3Kernel::is_optimized_execution_possible(input_shape, info, data_type, depth_multiplier, DataLayout::NCHW); |
| const int step_non_opt_dwc = 16 >> info.stride().first; |
| const int step_bias_add = 16 / src.info()->element_size(); |
| const int step = is_optimized_run ? step_bias_add : std::max(step_non_opt_dwc, step_bias_add); |
| const PaddingSize padding = PaddingCalculator(output_shape.x(), step).required_padding(); |
| validate(dst.info()->padding(), padding); |
| } |
| |
| TEST_SUITE(Float) |
| TEST_SUITE(F32) |
| TEST_SUITE(Generic) |
| template <typename T> |
| using NEDepthwiseConvolutionLayerFixture = DepthwiseConvolutionLayerValidationFixture<Tensor, Accessor, NEDepthwiseConvolutionLayer, T>; |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEDepthwiseConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset(), |
| depth_multipliers), |
| framework::dataset::make("DataType", |
| DataType::F32)), |
| framework::dataset::make("DataLayout", DataLayout::NCHW))) |
| { |
| validate(Accessor(_target), _reference, tolerance_f32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, NEDepthwiseConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset(), |
| depth_multipliers), |
| framework::dataset::make("DataType", |
| DataType::F32)), |
| framework::dataset::make("DataLayout", DataLayout::NCHW))) |
| { |
| validate(Accessor(_target), _reference, tolerance_f32); |
| } |
| TEST_SUITE_END() |
| |
| TEST_SUITE(W3x3) |
| template <typename T> |
| using NEDepthwiseConvolutionLayerFixture3x3 = DepthwiseConvolutionLayerValidationFixture<Tensor, Accessor, NEDepthwiseConvolutionLayer3x3, T>; |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEDepthwiseConvolutionLayerFixture3x3<float>, framework::DatasetMode::ALL, combine(combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset3x3(), |
| depth_multipliers), |
| framework::dataset::make("DataType", |
| DataType::F32)), |
| framework::dataset::make("DataLayout", DataLayout::NCHW))) |
| { |
| validate(Accessor(_target), _reference, tolerance_f32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, NEDepthwiseConvolutionLayerFixture3x3<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset3x3(), |
| depth_multipliers), |
| framework::dataset::make("DataType", |
| DataType::F32)), |
| framework::dataset::make("DataLayout", DataLayout::NCHW))) |
| { |
| validate(Accessor(_target), _reference, tolerance_f32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunOptimized, NEDepthwiseConvolutionLayerFixture3x3<float>, framework::DatasetMode::ALL, combine(combine(combine(datasets::OptimizedDepthwiseConvolutionLayerDataset3x3(), |
| framework::dataset::make("DepthMultiplier", 1)), |
| framework::dataset::make("DataType", |
| DataType::F32)), |
| framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) |
| { |
| validate(Accessor(_target), _reference, tolerance_f32); |
| } |
| TEST_SUITE_END() |
| TEST_SUITE_END() |
| |
| TEST_SUITE_END() |
| |
| template <typename T> |
| using NEDepthwiseConvolutionLayerQuantizedFixture3x3 = DepthwiseConvolutionLayerValidationQuantizedFixture<Tensor, Accessor, NEDepthwiseConvolutionLayer3x3, T>; |
| template <typename T> |
| using NEDepthwiseConvolutionLayerQuantizedFixture = DepthwiseConvolutionLayerValidationQuantizedFixture<Tensor, Accessor, NEDepthwiseConvolutionLayer, T>; |
| |
| TEST_SUITE(Quantized) |
| TEST_SUITE(QASYMM8) |
| TEST_SUITE(Generic) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEDepthwiseConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, |
| combine(combine(combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset(), |
| depth_multipliers), |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10) })), |
| framework::dataset::make("DataLayout", DataLayout::NCHW))) |
| { |
| validate(Accessor(_target), _reference, tolerance_qasymm8); |
| } |
| TEST_SUITE_END() |
| TEST_SUITE(W3x3) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEDepthwiseConvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::PRECOMMIT, |
| combine(combine(combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset3x3(), depth_multipliers), |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10) })), |
| framework::dataset::make("DataLayout", DataLayout::NCHW))) |
| { |
| validate(Accessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, NEDepthwiseConvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::NIGHTLY, |
| combine(combine(combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset3x3(), |
| depth_multipliers), |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10) })), |
| framework::dataset::make("DataLayout", DataLayout::NCHW))) |
| { |
| validate(Accessor(_target), _reference, tolerance_qasymm8); |
| } |
| TEST_SUITE_END() |
| TEST_SUITE_END() |
| TEST_SUITE_END() |
| |
| TEST_SUITE_END() |
| TEST_SUITE_END() |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |