| /* |
| * 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/core/utils/misc/ShapeCalculator.h" |
| #include "arm_compute/runtime/CL/CLTensor.h" |
| #include "arm_compute/runtime/CL/CLTensorAllocator.h" |
| #include "arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h" |
| #include "tests/CL/CLAccessor.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 */ |
| RelativeTolerance<half_float::half> tolerance_f16(half_float::half(0.2)); /**< Tolerance value for comparing reference's for DataType::F16 */ |
| constexpr AbsoluteTolerance<float> tolerance_qasymm8(1.0); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */ |
| constexpr float tolerance_num = 0.07f; /**< Tolerance number */ |
| |
| const auto data9x9_small_asymm = framework::dataset::make("InputShape", TensorShape{ 10U, 10U, 1U, 1U }) *framework::dataset::make("StrideX", 2) *framework::dataset::make("StrideY", |
| 2) |
| *framework::dataset::make("PadLeft", 3) |
| *framework::dataset::make("PadRight", 4) *framework::dataset::make("PadTop", 3) *framework::dataset::make("PadBottom", 4) *framework::dataset::make("NumKernels", { 1 }); |
| |
| const auto data9x9_large_asymm = framework::dataset::make("InputShape", TensorShape{ 640U, 360U, 56U, 1U }) *framework::dataset::make("StrideX", 2) *framework::dataset::make("StrideY", |
| 2) |
| *framework::dataset::make("PadLeft", 3) |
| *framework::dataset::make("PadRight", 4) *framework::dataset::make("PadTop", 3) *framework::dataset::make("PadBottom", 4) *framework::dataset::make("NumKernels", { 1 }); |
| |
| 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_asymm = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 2) * framework::dataset::make("StrideY", 1, 2) * framework::dataset::make("PadLeft", 0, 1) |
| * framework::dataset::make("PadRight", 0, 1) * framework::dataset::make("PadTop", 0, 1) * framework::dataset::make("PadBottom", 0, 1) * 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 data2x2_precommit = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 2) * framework::dataset::make("StrideY", 2) * framework::dataset::make("PadX", 1) |
| * framework::dataset::make("PadY", 1) * 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, DataLayout::NHWC }); |
| |
| const auto add_bias_dataset = framework::dataset::make("AddBias", { true, false }); |
| } // namespace |
| |
| TEST_SUITE(CL) |
| TEST_SUITE(DeconvolutionLayer) |
| |
| // *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(CLDeconvolutionLayer::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 CLDeconvolutionLayerFixture4x4 = DeconvolutionValidationFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 4, 4>; |
| |
| template <typename T> |
| using CLDeconvolutionLayerFixture3x3 = DeconvolutionValidationFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 3, 3>; |
| |
| template <typename T> |
| using CLDeconvolutionLayerAsymmFixture3x3 = DeconvolutionValidationAsymmFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 3, 3>; |
| |
| template <typename T> |
| using CLDeconvolutionLayerFixture2x2 = DeconvolutionValidationFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 2, 2>; |
| |
| template <typename T> |
| using CLDeconvolutionLayerFixture1x1 = DeconvolutionValidationFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 1, 1>; |
| |
| template <typename T> |
| using CLDeconvolutionLayerAsymmFixture9x9 = DeconvolutionValidationAsymmFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 9, 9>; |
| |
| TEST_SUITE(Float) |
| TEST_SUITE(FP32) |
| |
| TEST_SUITE(W4x4) |
| FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture4x4<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data4x4, framework::dataset::make("DataType", DataType::F32)), |
| data_layouts_dataset), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_fp32); |
| } |
| TEST_SUITE_END() // W4x4 |
| |
| TEST_SUITE(W3x3) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerFixture3x3<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data3x3_precommit, framework::dataset::make("DataType", |
| DataType::F32)), |
| data_layouts_dataset), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_fp32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunAsymm, CLDeconvolutionLayerAsymmFixture3x3<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data3x3_asymm, framework::dataset::make("DataType", |
| DataType::F32)), |
| data_layouts_dataset), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_fp32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLDeconvolutionLayerFixture3x3<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data3x3, framework::dataset::make("DataType", DataType::F32)), |
| data_layouts_dataset), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_fp32); |
| } |
| TEST_SUITE_END() // W3x3 |
| |
| TEST_SUITE(W2x2) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerFixture2x2<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data2x2_precommit, framework::dataset::make("DataType", |
| DataType::F32)), |
| data_layouts_dataset), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_fp32); |
| } |
| TEST_SUITE_END() // W2x2 |
| |
| TEST_SUITE(W1x1) |
| FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture1x1<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data1x1, framework::dataset::make("DataType", DataType::F32)), |
| data_layouts_dataset), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_fp32); |
| } |
| TEST_SUITE_END() // W1x1 |
| TEST_SUITE(W9x9) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerAsymmFixture9x9<float>, framework::DatasetMode::ALL, combine(combine(combine(data9x9_small_asymm, framework::dataset::make("DataType", |
| DataType::F32)), |
| framework::dataset::make("DataLayout", { DataLayout::NHWC })), |
| framework::dataset::make("AddBias", { false }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_fp32); |
| } |
| TEST_SUITE_END() // W9x9 |
| TEST_SUITE_END() // FP32 |
| |
| TEST_SUITE(FP16) |
| |
| TEST_SUITE(W4x4) |
| FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture4x4<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data4x4, framework::dataset::make("DataType", DataType::F16)), |
| data_layouts_dataset), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); |
| } |
| TEST_SUITE_END() // W4x4 |
| |
| TEST_SUITE(W3x3) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerFixture3x3<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data3x3_precommit, framework::dataset::make("DataType", |
| DataType::F16)), |
| data_layouts_dataset), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLDeconvolutionLayerFixture3x3<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data3x3, framework::dataset::make("DataType", DataType::F16)), |
| data_layouts_dataset), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); |
| } |
| TEST_SUITE_END() // W3x3 |
| |
| TEST_SUITE(W2x2) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerFixture2x2<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data2x2_precommit, framework::dataset::make("DataType", |
| DataType::F16)), |
| data_layouts_dataset), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_f16); |
| } |
| TEST_SUITE_END() // W2x2 |
| |
| TEST_SUITE(W1x1) |
| FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture1x1<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data1x1, framework::dataset::make("DataType", DataType::F16)), |
| data_layouts_dataset), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); |
| } |
| TEST_SUITE_END() // W1x1 |
| |
| TEST_SUITE_END() // FP16 |
| TEST_SUITE_END() // Float |
| |
| template <typename T> |
| using CLDeconvolutionLayerQuantizedFixture4x4 = DeconvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 4, 4>; |
| |
| template <typename T> |
| using CLDeconvolutionLayerQuantizedFixture3x3 = DeconvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 3, 3>; |
| |
| template <typename T> |
| using CLDeconvolutionLayerQuantizedFixture2x2 = DeconvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 2, 2>; |
| |
| template <typename T> |
| using CLDeconvolutionLayerQuantizedFixture1x1 = DeconvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 1, 1>; |
| |
| TEST_SUITE(Quantized) |
| TEST_SUITE(QASYMM8) |
| |
| TEST_SUITE(W4x4) |
| FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerQuantizedFixture4x4<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(data4x4, framework::dataset::make("DataType", |
| DataType::QASYMM8)), |
| data_layouts_dataset), |
| framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, 10), QuantizationInfo(2.f / 255.f, 5) })), |
| framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(3.f / 255.f, 5), QuantizationInfo(4.f / 255.f, 10) })), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num); |
| } |
| TEST_SUITE_END() // W4x4 |
| |
| TEST_SUITE(W3x3) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(combine(data3x3_precommit, |
| framework::dataset::make("DataType", |
| DataType::QASYMM8)), |
| data_layouts_dataset), |
| framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, 10), QuantizationInfo(2.f / 255.f, 4) })), |
| framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(3.f / 255.f, 10), QuantizationInfo(4.f / 255.f, 5) })), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLDeconvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(data3x3, |
| framework::dataset::make("DataType", |
| DataType::QASYMM8)), |
| data_layouts_dataset), |
| framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, 10), QuantizationInfo(2.f / 255.f, 128) })), |
| framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(3.f / 255.f, 128), QuantizationInfo(4.f / 255.f, 128) })), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num); |
| } |
| TEST_SUITE_END() // W3x3 |
| |
| TEST_SUITE(W2x2) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerQuantizedFixture2x2<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(combine(data2x2_precommit, |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| data_layouts_dataset), |
| framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, 128), QuantizationInfo(2.f / 255.f, 128) })), |
| framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(3.f / 255.f, 64), QuantizationInfo(4.f / 255.f, 128) })), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num); |
| } |
| TEST_SUITE_END() // W2x2 |
| |
| TEST_SUITE(W1x1) |
| FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerQuantizedFixture1x1<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(data1x1, framework::dataset::make("DataType", |
| DataType::QASYMM8)), |
| data_layouts_dataset), |
| framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, 0), QuantizationInfo(2.f / 255.f, 0) })), |
| framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(3.f / 255.f, 0), QuantizationInfo(4.f / 255.f, 0) })), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num); |
| } |
| TEST_SUITE_END() // W1x1 |
| |
| TEST_SUITE_END() // QASYMM8 |
| |
| TEST_SUITE(QASYMM8_SIGNED) |
| |
| // QASYMM8_SIGNED: zero-point in range [-128, 127] |
| // QASYMM8 : zero-point in range [0 , 255] |
| |
| TEST_SUITE(W4x4) |
| FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerQuantizedFixture4x4<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(data4x4, framework::dataset::make("DataType", |
| DataType::QASYMM8_SIGNED)), |
| data_layouts_dataset), |
| framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, 10), QuantizationInfo(2.f / 255.f, 5) })), |
| framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(3.f / 255.f, 5), QuantizationInfo(4.f / 255.f, 10) })), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num); |
| } |
| TEST_SUITE_END() // W4x4 |
| |
| TEST_SUITE(W3x3) |
| // DirectDeconvolution |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerQuantizedFixture3x3<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(combine(data3x3_precommit, |
| framework::dataset::make("DataType", |
| DataType::QASYMM8_SIGNED)), |
| data_layouts_dataset), |
| framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, 10), QuantizationInfo(2.f / 255.f, 4) })), |
| framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(3.f / 255.f, 10), QuantizationInfo(4.f / 255.f, 5) })), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLDeconvolutionLayerQuantizedFixture3x3<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(data3x3, |
| framework::dataset::make("DataType", |
| DataType::QASYMM8_SIGNED)), |
| data_layouts_dataset), |
| framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, -10), QuantizationInfo(2.f / 255.f, 127) })), |
| framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(3.f / 255.f, 64), QuantizationInfo(4.f / 255.f, -128) })), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num); |
| } |
| TEST_SUITE_END() // W3x3 |
| |
| TEST_SUITE(W2x2) // GEMMDeconvolution |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerQuantizedFixture2x2<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(combine(data2x2_precommit, |
| framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), |
| data_layouts_dataset), |
| framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, 127), QuantizationInfo(2.f / 255.f, -128) })), |
| framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(3.f / 255.f, -10), QuantizationInfo(4.f / 255.f, 64) })), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num); |
| } |
| TEST_SUITE_END() // W2x2 |
| |
| TEST_SUITE(W1x1) // DirectDeconvolution and GEMMDeconvolution |
| FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerQuantizedFixture1x1<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(data1x1, framework::dataset::make("DataType", |
| DataType::QASYMM8_SIGNED)), |
| data_layouts_dataset), |
| framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, 0), QuantizationInfo(2.f / 255.f, 0) })), |
| framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(3.f / 255.f, 0), QuantizationInfo(4.f / 255.f, 0) })), |
| add_bias_dataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num); |
| } |
| TEST_SUITE_END() // W1x1 |
| |
| TEST_SUITE_END() // QASYMM8_SIGNED |
| |
| TEST_SUITE_END() // Quantized |
| |
| TEST_SUITE_END() // DeconvolutionLayer |
| TEST_SUITE_END() // CL |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |