| /* |
| * Copyright (c) 2017-2019 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/core/utils/misc/ShapeCalculator.h" |
| #include "arm_compute/runtime/NEON/functions/NEDeconvolutionLayer.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/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/DeconvolutionLayerFixture.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace |
| { |
| constexpr AbsoluteTolerance<float> tolerance_fp32(0.001f); /**< Tolerance for floating point tests */ |
| constexpr AbsoluteTolerance<float> tolerance_qasymm8(0.0); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */ |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| const RelativeTolerance<half_float::half> tolerance_fp16(half_float::half(0.2f)); /**< Relative tolerance value for comparing reference's output against implementation's output for DataType::F16 */ |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC*/ |
| constexpr float tolerance_num = 0.07f; /**< Tolerance number */ |
| |
| const auto data4x4 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 3) |
| * framework::dataset::make("PadY", 0, 3) * framework::dataset::make("NumKernels", { 3 }); |
| |
| const auto data3x3 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 2) |
| * framework::dataset::make("PadY", 0, 2) * framework::dataset::make("NumKernels", { 3 }); |
| |
| const auto data3x3_precommit = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 2) * framework::dataset::make("StrideY", 1, 2) * framework::dataset::make("PadX", 0, 2) |
| * framework::dataset::make("PadY", 0, 2) * framework::dataset::make("NumKernels", { 3 }); |
| |
| const auto data1x1 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 1) |
| * framework::dataset::make("PadY", 0, 1) * framework::dataset::make("NumKernels", { 3 }); |
| |
| const auto data_layouts_dataset = framework::dataset::make("DataLayout", { DataLayout::NCHW }); |
| } // namespace |
| |
| TEST_SUITE(NEON) |
| TEST_SUITE(DeconvolutionLayer) |
| |
| DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, (combine(datasets::SmallDeconvolutionShapes(), framework::dataset::make("DataType", DataType::F32))), |
| input_shape, data_type) |
| { |
| // Create shapes |
| const unsigned int kernel_size_x = 3; |
| const unsigned int kernel_size_y = 3; |
| const unsigned int num_kernels = 1; |
| const TensorShape weights_shape(kernel_size_x, kernel_size_y, input_shape.z(), num_kernels); |
| const TensorShape bias_shape(num_kernels); |
| auto out_dim = deconvolution_output_dimensions(input_shape.x(), input_shape.y(), kernel_size_x, kernel_size_y, 1, 1, 1, 1); |
| TensorShape output_shape = compute_deconvolution_output_shape(out_dim, TensorInfo(input_shape, 1, data_type), TensorInfo(weights_shape, 1, data_type)); |
| |
| // Create tensors |
| Tensor src = create_tensor<Tensor>(input_shape, data_type, 1); |
| Tensor weights = create_tensor<Tensor>(weights_shape, data_type, 1); |
| Tensor bias = create_tensor<Tensor>(bias_shape, data_type, 1); |
| Tensor dst = create_tensor<Tensor>(output_shape, data_type, 1); |
| |
| 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); |
| |
| // Create and configure function |
| NEDeconvolutionLayer deconv; |
| deconv.configure(&src, &weights, &bias, &dst, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL)); |
| |
| // Validate valid region |
| const ValidRegion src_valid_region = shape_to_valid_region(input_shape); |
| const ValidRegion weights_valid_region = shape_to_valid_region(weights_shape); |
| const ValidRegion bias_valid_region = shape_to_valid_region(bias_shape); |
| const ValidRegion dst_valid_region = shape_to_valid_region(output_shape); |
| |
| validate(src.info()->valid_region(), src_valid_region); |
| validate(weights.info()->valid_region(), weights_valid_region); |
| validate(bias.info()->valid_region(), bias_valid_region); |
| validate(dst.info()->valid_region(), dst_valid_region); |
| } |
| |
| // *INDENT-OFF* |
| // clang-format off |
| DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( |
| framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching data type |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid weights shape |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16), // Non supported data type |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid bias shape |
| TensorInfo(TensorShape(13U, 11U, 4U, 3U), 1, DataType::F32), // Window shrink |
| TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32), |
| }), |
| framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(3U, 2U, 2U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U, 3U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(1U, 1U, 2U, 4U), 1, DataType::F32), |
| })), |
| framework::dataset::make("BiasInfo", { TensorInfo(TensorShape(1U), 1, DataType::F16), |
| TensorInfo(TensorShape(1U), 1, DataType::F32), |
| TensorInfo(TensorShape(1U), 1, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U), 1, DataType::F32), |
| TensorInfo(TensorShape(1U), 1, DataType::F32), |
| TensorInfo(TensorShape(4U), 1, DataType::F32), |
| })), |
| framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(25U, 10U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(13U, 13U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(11U, 9U, 1U, 3U), 1, DataType::F32), |
| TensorInfo(TensorShape(32U, 16U, 4U), 1, DataType::F32), |
| })), |
| framework::dataset::make("PadStrideInfo", { PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 1, 1), |
| PadStrideInfo(1, 1, 0, 0), |
| })), |
| framework::dataset::make("Expected", { false, false, false, false, false, true })), |
| input_info, weights_info, bias_info, output_info, pad_info, expected) |
| { |
| bool is_valid = bool(NEDeconvolutionLayer::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), pad_info)); |
| ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); |
| } |
| // clang-format on |
| // *INDENT-ON* |
| |
| template <typename T> |
| using NEDeconvolutionLayerFixture4x4 = DeconvolutionValidationFixture<Tensor, Accessor, NEDeconvolutionLayer, T, 4, 4>; |
| |
| template <typename T> |
| using NEDeconvolutionLayerFixture3x3 = DeconvolutionValidationFixture<Tensor, Accessor, NEDeconvolutionLayer, T, 3, 3>; |
| |
| template <typename T> |
| using NEDeconvolutionLayerFixture1x1 = DeconvolutionValidationFixture<Tensor, Accessor, NEDeconvolutionLayer, T, 1, 1>; |
| |
| TEST_SUITE(Float) |
| TEST_SUITE(FP32) |
| TEST_SUITE(W4x4) |
| FIXTURE_DATA_TEST_CASE(Run, NEDeconvolutionLayerFixture4x4<float>, framework::DatasetMode::NIGHTLY, combine(combine(data4x4, framework::dataset::make("DataType", DataType::F32)), |
| data_layouts_dataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_fp32); |
| } |
| TEST_SUITE_END() // W4x4 |
| TEST_SUITE(W3x3) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEDeconvolutionLayerFixture3x3<float>, framework::DatasetMode::PRECOMMIT, combine(combine(data3x3_precommit, framework::dataset::make("DataType", DataType::F32)), |
| data_layouts_dataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_fp32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, NEDeconvolutionLayerFixture3x3<float>, framework::DatasetMode::NIGHTLY, combine(combine(data3x3, framework::dataset::make("DataType", DataType::F32)), |
| data_layouts_dataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_fp32); |
| } |
| TEST_SUITE_END() // W3x3 |
| TEST_SUITE(W1x1) |
| FIXTURE_DATA_TEST_CASE(Run, NEDeconvolutionLayerFixture1x1<float>, framework::DatasetMode::NIGHTLY, combine(combine(data1x1, framework::dataset::make("DataType", DataType::F32)), |
| data_layouts_dataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_fp32); |
| } |
| TEST_SUITE_END() // W1x1 |
| TEST_SUITE_END() // FP32 |
| |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| TEST_SUITE(FP16) |
| TEST_SUITE(W4x4) |
| FIXTURE_DATA_TEST_CASE(Run, NEDeconvolutionLayerFixture4x4<half>, framework::DatasetMode::NIGHTLY, combine(combine(data4x4, framework::dataset::make("DataType", DataType::F16)), |
| data_layouts_dataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_fp16); |
| } |
| TEST_SUITE_END() // W4x4 |
| TEST_SUITE(W3x3) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEDeconvolutionLayerFixture3x3<half>, framework::DatasetMode::PRECOMMIT, combine(combine(data3x3_precommit, framework::dataset::make("DataType", DataType::F16)), |
| data_layouts_dataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_fp16); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, NEDeconvolutionLayerFixture3x3<half>, framework::DatasetMode::NIGHTLY, combine(combine(data3x3, framework::dataset::make("DataType", DataType::F16)), |
| data_layouts_dataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_fp16); |
| } |
| TEST_SUITE_END() // W3x3 |
| TEST_SUITE(W1x1) |
| FIXTURE_DATA_TEST_CASE(Run, NEDeconvolutionLayerFixture1x1<half>, framework::DatasetMode::NIGHTLY, combine(combine(data1x1, framework::dataset::make("DataType", DataType::F16)), |
| data_layouts_dataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_fp16); |
| } |
| TEST_SUITE_END() // W1x1 |
| TEST_SUITE_END() // FP16 |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| |
| TEST_SUITE_END() // Float |
| |
| template <typename T> |
| using NEDeconvolutionLayerQuantizedFixture4x4 = DeconvolutionValidationQuantizedFixture<Tensor, Accessor, NEDeconvolutionLayer, T, 4, 4>; |
| |
| template <typename T> |
| using NEDeconvolutionLayerQuantizedFixture3x3 = DeconvolutionValidationQuantizedFixture<Tensor, Accessor, NEDeconvolutionLayer, T, 3, 3>; |
| |
| template <typename T> |
| using NEDeconvolutionLayerQuantizedFixture1x1 = DeconvolutionValidationQuantizedFixture<Tensor, Accessor, NEDeconvolutionLayer, T, 1, 1>; |
| |
| TEST_SUITE(Quantized) |
| TEST_SUITE(QASYMM8) |
| |
| TEST_SUITE(W4x4) |
| FIXTURE_DATA_TEST_CASE(Run, NEDeconvolutionLayerQuantizedFixture4x4<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data4x4, framework::dataset::make("DataType", |
| DataType::QASYMM8)), |
| data_layouts_dataset), |
| framework::dataset::make("QuantizationInfo", QuantizationInfo(2.f / 255.f, 0)))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_qasymm8, tolerance_num); |
| } |
| TEST_SUITE_END() // W4x4 |
| |
| TEST_SUITE(W3x3) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEDeconvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data3x3_precommit, framework::dataset::make("DataType", |
| DataType::QASYMM8)), |
| data_layouts_dataset), |
| framework::dataset::make("QuantizationInfo", QuantizationInfo(2.f / 255.f, 0)))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_qasymm8, tolerance_num); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, NEDeconvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data3x3, framework::dataset::make("DataType", |
| DataType::QASYMM8)), |
| data_layouts_dataset), |
| framework::dataset::make("QuantizationInfo", QuantizationInfo(2.f / 255.f, 0)))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_qasymm8, tolerance_num); |
| } |
| TEST_SUITE_END() // W3x3 |
| |
| TEST_SUITE(W1x1) |
| FIXTURE_DATA_TEST_CASE(Run, NEDeconvolutionLayerQuantizedFixture1x1<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data1x1, framework::dataset::make("DataType", |
| DataType::QASYMM8)), |
| data_layouts_dataset), |
| framework::dataset::make("QuantizationInfo", QuantizationInfo(2.f / 255.f, 0)))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_qasymm8, tolerance_num); |
| } |
| TEST_SUITE_END() // W1x1 |
| |
| TEST_SUITE_END() // QASYMM8 |
| TEST_SUITE_END() // Quantized |
| |
| TEST_SUITE_END() // DeconvolutionLayer |
| TEST_SUITE_END() // NEON |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |