| /* |
| * 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/Helpers.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/runtime/NEON/functions/NEScale.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/ScaleValidationDataset.h" |
| #include "tests/framework/Asserts.h" |
| #include "tests/framework/Macros.h" |
| #include "tests/validation/Helpers.h" |
| #include "tests/validation/Validation.h" |
| #include "tests/validation/fixtures/ScaleFixture.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace |
| { |
| using datasets::ScaleShapesBaseDataSet; |
| using datasets::ScaleInterpolationPolicySet; |
| using datasets::ScaleDataLayouts; |
| using datasets::ScaleSamplingPolicySet; |
| using datasets::ScaleAlignCornersSamplingPolicySet; |
| |
| /** We consider vector size in byte 64 since the maximum size of |
| * a vector used by @ref NEScaleKernel is currently 64-byte (float32x4x4). |
| * There are possibility to reduce test time further by using |
| * smaller vector sizes for different data types where applicable. |
| */ |
| constexpr uint32_t vector_byte = 64; |
| |
| template <typename T> |
| constexpr uint32_t num_elements_per_vector() |
| { |
| return vector_byte / sizeof(T); |
| } |
| |
| /** Scale data types */ |
| const auto ScaleDataTypes = framework::dataset::make("DataType", |
| { |
| DataType::U8, |
| DataType::S16, |
| DataType::F32, |
| }); |
| |
| /** Quantization information data set */ |
| const auto QuantizationInfoSet = framework::dataset::make("QuantizationInfo", |
| { |
| QuantizationInfo(0.5f, -10), |
| }); |
| |
| /** Tolerance */ |
| constexpr AbsoluteTolerance<uint8_t> tolerance_u8(1); |
| constexpr AbsoluteTolerance<int16_t> tolerance_s16(1); |
| RelativeTolerance<float> tolerance_f32(0.05); |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| RelativeTolerance<half> tolerance_f16(half(0.1)); |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| |
| constexpr float tolerance_num_s16 = 0.01f; |
| constexpr float tolerance_num_f32 = 0.01f; |
| } // namespace |
| |
| TEST_SUITE(NEON) |
| TEST_SUITE(Scale) |
| TEST_SUITE(Validate) |
| |
| /** Validate test suite is to test ARM_COMPUTE_RETURN_ON_* macros |
| * we use to check the validity of given arguments in @ref NEScale |
| * and subsequent call to @ref NEScaleKernel. |
| * Since this is using validate() of @ref NEScale, which pre-adjust |
| * arguments for @ref NEScaleKernel, the following conditions in |
| * the kernel are not currently tested. |
| * - The same input and output |
| * - Data type of offset, dx and dy |
| * This suite also tests two different validate() APIs - one is |
| * using @ref ScaleKernelInfo and the other one is more verbose |
| * one calls the other one - in the same test case. Even though |
| * there are possibility that it makes debugging for regression |
| * harder, belows are reasons of this test case implementation. |
| * - The more verbose one is just a wrapper function calls |
| * the other one without any additional logic. So we are |
| * safe to merge two tests into one. |
| * - A large amount of code duplication is test suite can be prevented. |
| */ |
| |
| const auto input_shape = TensorShape{ 2, 3, 3, 2 }; |
| const auto output_shape = TensorShape{ 4, 6, 3, 2 }; |
| |
| constexpr auto default_data_type = DataType::U8; |
| constexpr auto default_data_layout = DataLayout::NHWC; |
| constexpr auto default_interpolation_policy = InterpolationPolicy::NEAREST_NEIGHBOR; |
| constexpr auto default_border_mode = BorderMode::CONSTANT; |
| constexpr auto default_sampling_policy = SamplingPolicy::CENTER; |
| |
| TEST_CASE(NullPtr, framework::DatasetMode::ALL) |
| { |
| const auto input = TensorInfo{ input_shape, 1, default_data_type, default_data_layout }; |
| const auto output = TensorInfo{ output_shape, 1, default_data_type, default_data_layout }; |
| Status result{}; |
| |
| // nullptr is given as input |
| result = NEScale::validate(nullptr, &output, ScaleKernelInfo{ default_interpolation_policy, default_border_mode, PixelValue(), SamplingPolicy::CENTER, false }); |
| ARM_COMPUTE_EXPECT(bool(result) == false, framework::LogLevel::ERRORS); |
| |
| // nullptr is given as output |
| result = NEScale::validate(&input, nullptr, ScaleKernelInfo{ default_interpolation_policy, default_border_mode, PixelValue(), SamplingPolicy::CENTER, false }); |
| ARM_COMPUTE_EXPECT(bool(result) == false, framework::LogLevel::ERRORS); |
| } |
| |
| TEST_CASE(SupportDataType, framework::DatasetMode::ALL) |
| { |
| const std::map<DataType, bool> supported_data_types = |
| { |
| { DataType::U8, true }, |
| { DataType::S8, false }, |
| { DataType::QSYMM8, false }, |
| { DataType::QASYMM8, true }, |
| { DataType::QASYMM8_SIGNED, true }, |
| { DataType::QSYMM8_PER_CHANNEL, false }, |
| { DataType::U16, false }, |
| { DataType::S16, true }, |
| { DataType::QSYMM16, false }, |
| { DataType::QASYMM16, false }, |
| { DataType::U32, false }, |
| { DataType::S32, false }, |
| { DataType::U64, false }, |
| { DataType::S64, false }, |
| { DataType::BFLOAT16, false }, |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| { DataType::F16, true }, |
| #else // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| { DataType::F16, false }, |
| #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| { DataType::F32, true }, |
| { DataType::F64, false }, |
| { DataType::SIZET, false }, |
| }; |
| Status result{}; |
| for(auto &kv : supported_data_types) |
| { |
| const auto input = TensorInfo{ input_shape, 1, kv.first, default_data_layout }; |
| const auto output = TensorInfo{ output_shape, 1, kv.first, default_data_layout }; |
| |
| result = NEScale::validate(&input, &output, ScaleKernelInfo{ default_interpolation_policy, default_border_mode, PixelValue(), SamplingPolicy::CENTER, false }); |
| ARM_COMPUTE_EXPECT(bool(result) == kv.second, framework::LogLevel::ERRORS); |
| } |
| } |
| |
| TEST_CASE(MissmatchingDataType, framework::DatasetMode::ALL) |
| { |
| constexpr auto non_default_data_type = DataType::F32; |
| |
| const auto input = TensorInfo{ input_shape, 1, default_data_type, default_data_layout }; |
| const auto output = TensorInfo{ output_shape, 1, non_default_data_type, default_data_layout }; |
| Status result{}; |
| |
| result = NEScale::validate(&input, &output, ScaleKernelInfo{ default_interpolation_policy, default_border_mode, PixelValue(), SamplingPolicy::CENTER, false }); |
| ARM_COMPUTE_EXPECT(bool(result) == false, framework::LogLevel::ERRORS); |
| } |
| |
| TEST_CASE(UsePadding, framework::DatasetMode::ALL) |
| { |
| const auto input = TensorInfo{ input_shape, 1, default_data_type, default_data_layout }; |
| const auto output = TensorInfo{ output_shape, 1, default_data_type, default_data_layout }; |
| Status result{}; |
| |
| // Padding is not supported anymore |
| constexpr auto border_mode = BorderMode::CONSTANT; |
| constexpr bool use_padding = true; |
| |
| result = NEScale::validate(&input, &output, ScaleKernelInfo{ default_interpolation_policy, border_mode, PixelValue(), default_sampling_policy, use_padding }); |
| ARM_COMPUTE_EXPECT(bool(result) == false, framework::LogLevel::ERRORS); |
| } |
| |
| TEST_CASE(AreaWithNHWC, framework::DatasetMode::ALL) |
| { |
| // InterpolationPolicy::AREA is not supported for NHWC |
| constexpr auto interpolation_policy = InterpolationPolicy::AREA; |
| constexpr auto data_layout = DataLayout::NHWC; |
| |
| const auto input = TensorInfo{ input_shape, 1, default_data_type, data_layout }; |
| const auto output = TensorInfo{ output_shape, 1, default_data_type, data_layout }; |
| Status result{}; |
| |
| result = NEScale::validate(&input, &output, ScaleKernelInfo{ interpolation_policy, default_border_mode, PixelValue(), SamplingPolicy::CENTER, false }); |
| ARM_COMPUTE_EXPECT(bool(result) == false, framework::LogLevel::ERRORS); |
| } |
| |
| TEST_CASE(AreaWithNonU8, framework::DatasetMode::ALL) |
| { |
| // InterpolationPolicy::AREA only supports U8 |
| constexpr auto interpolation_policy = InterpolationPolicy::AREA; |
| constexpr auto data_type = DataType::F32; |
| constexpr auto data_layout = DataLayout::NCHW; |
| |
| const auto input = TensorInfo{ input_shape, 1, data_type, data_layout }; |
| const auto output = TensorInfo{ output_shape, 1, data_type, data_layout }; |
| Status result{}; |
| |
| result = NEScale::validate(&input, &output, ScaleKernelInfo{ interpolation_policy, default_border_mode, PixelValue(), SamplingPolicy::CENTER, false }); |
| ARM_COMPUTE_EXPECT(bool(result) == false, framework::LogLevel::ERRORS); |
| } |
| |
| TEST_CASE(AlignedCornerNotSupported, framework::DatasetMode::ALL) |
| { |
| // Aligned corners require sampling policy to be TOP_LEFT. |
| constexpr auto interpolation_policy = InterpolationPolicy::BILINEAR; |
| constexpr bool align_corners = true; |
| constexpr auto sampling_policy = SamplingPolicy::CENTER; |
| |
| const auto input = TensorInfo{ input_shape, 1, default_data_type, default_data_layout }; |
| const auto output = TensorInfo{ output_shape, 1, default_data_type, default_data_layout }; |
| Status result{}; |
| |
| result = NEScale::validate(&input, &output, ScaleKernelInfo{ interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false, align_corners }); |
| ARM_COMPUTE_EXPECT(bool(result) == false, framework::LogLevel::ERRORS); |
| } |
| TEST_SUITE_END() // Validate |
| |
| DATA_TEST_CASE(CheckNoPadding, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::Medium4DShapes(), |
| framework::dataset::make("DataType", { DataType::F32, DataType::QASYMM8 })), |
| framework::dataset::make("InterpolationPolicy", { InterpolationPolicy::BILINEAR, InterpolationPolicy::NEAREST_NEIGHBOR })), |
| framework::dataset::make("SamplingPolicy", { SamplingPolicy::CENTER, SamplingPolicy::TOP_LEFT })), |
| framework::dataset::make("DataLayout", { DataLayout::NHWC, DataLayout::NCHW })), |
| shape, data_type, interpolation_policy, sampling_policy, data_layout) |
| { |
| constexpr auto default_border_mode = BorderMode::CONSTANT; |
| ScaleKernelInfo info(interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false); |
| |
| // Create tensors |
| Tensor src = create_tensor<Tensor>(shape, data_type); |
| src.info()->set_data_layout(data_layout); |
| |
| const float scale_x = 0.5f; |
| const float scale_y = 0.5f; |
| TensorShape shape_scaled(shape); |
| const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); |
| const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); |
| shape_scaled.set(idx_width, shape[idx_width] * scale_x, /* apply_dim_correction = */ false); |
| shape_scaled.set(idx_height, shape[idx_height] * scale_y, /* apply_dim_correction = */ false); |
| Tensor dst = create_tensor<Tensor>(shape_scaled, data_type); |
| |
| ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); |
| |
| // Create and configure function |
| NEScale scale; |
| scale.configure(&src, &dst, info); |
| |
| validate(src.info()->padding(), PaddingSize(0, 0, 0, 0)); |
| validate(dst.info()->padding(), PaddingSize(0, 0, 0, 0)); |
| } |
| |
| DATA_TEST_CASE(CheckNoPaddingInterpAREA, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::Medium4DShapes(), |
| framework::dataset::make("DataType", { DataType::U8 })), |
| framework::dataset::make("InterpolationPolicy", { InterpolationPolicy::AREA })), |
| framework::dataset::make("SamplingPolicy", { SamplingPolicy::CENTER, SamplingPolicy::TOP_LEFT })), |
| framework::dataset::make("DataLayout", { DataLayout::NCHW })), |
| shape, data_type, interpolation_policy, sampling_policy, data_layout) |
| { |
| constexpr auto default_border_mode = BorderMode::CONSTANT; |
| ScaleKernelInfo info(interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false); |
| |
| // Create tensors |
| Tensor src = create_tensor<Tensor>(shape, data_type); |
| src.info()->set_data_layout(data_layout); |
| |
| const float scale_x = 0.5f; |
| const float scale_y = 0.5f; |
| TensorShape shape_scaled(shape); |
| const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); |
| const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); |
| shape_scaled.set(idx_width, shape[idx_width] * scale_x, /* apply_dim_correction = */ false); |
| shape_scaled.set(idx_height, shape[idx_height] * scale_y, /* apply_dim_correction = */ false); |
| |
| Tensor dst = create_tensor<Tensor>(shape, data_type); |
| |
| ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); |
| |
| // Create and configure function |
| NEScale scale; |
| scale.configure(&src, &dst, info); |
| |
| validate(src.info()->padding(), PaddingSize(0, 0, 0, 0)); |
| validate(dst.info()->padding(), PaddingSize(0, 0, 0, 0)); |
| } |
| |
| template <typename T> |
| using NEScaleFixture = ScaleValidationFixture<Tensor, Accessor, NEScale, T>; |
| template <typename T> |
| using NEScaleQuantizedFixture = ScaleValidationQuantizedFixture<Tensor, Accessor, NEScale, T>; |
| |
| TEST_SUITE(Float) |
| TEST_SUITE(FP32) |
| const auto f32_shape = combine((SCALE_SHAPE_DATASET(num_elements_per_vector<float>())), framework::dataset::make("DataType", DataType::F32)); |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEScaleFixture<float>, framework::DatasetMode::ALL, ASSEMBLE_DATASET(f32_shape, ScaleSamplingPolicySet)) |
| { |
| //Create valid region |
| TensorInfo src_info(_shape, 1, _data_type); |
| ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _policy, _sampling_policy, (_border_mode == BorderMode::UNDEFINED)); |
| |
| // Validate output |
| validate(Accessor(_target), _reference, valid_region, tolerance_f32, tolerance_num_f32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmallAlignCorners, NEScaleFixture<float>, framework::DatasetMode::ALL, ASSEMBLE_DATASET(f32_shape, ScaleAlignCornersSamplingPolicySet)) |
| { |
| //Create valid region |
| TensorInfo src_info(_shape, 1, _data_type); |
| ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _policy, _sampling_policy, (_border_mode == BorderMode::UNDEFINED)); |
| |
| // Validate output |
| validate(Accessor(_target), _reference, valid_region, tolerance_f32, tolerance_num_f32); |
| } |
| TEST_SUITE_END() // FP32 |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| TEST_SUITE(FP16) |
| const auto f16_shape = combine((SCALE_SHAPE_DATASET(num_elements_per_vector<half>())), framework::dataset::make("DataType", DataType::F16)); |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEScaleFixture<half>, framework::DatasetMode::ALL, ASSEMBLE_DATASET(f16_shape, ScaleSamplingPolicySet)) |
| { |
| //Create valid region |
| TensorInfo src_info(_shape, 1, _data_type); |
| const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _policy, _sampling_policy, (_border_mode == BorderMode::UNDEFINED)); |
| |
| // Validate output |
| validate(Accessor(_target), _reference, valid_region, tolerance_f16); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmallAlignCorners, NEScaleFixture<half>, framework::DatasetMode::ALL, ASSEMBLE_DATASET(f16_shape, ScaleAlignCornersSamplingPolicySet)) |
| { |
| //Create valid region |
| TensorInfo src_info(_shape, 1, _data_type); |
| const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _policy, _sampling_policy, (_border_mode == BorderMode::UNDEFINED)); |
| |
| // Validate output |
| validate(Accessor(_target), _reference, valid_region, tolerance_f16); |
| } |
| TEST_SUITE_END() // FP16 |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| TEST_SUITE_END() // Float |
| |
| TEST_SUITE(Integer) |
| TEST_SUITE(U8) |
| const auto u8_shape = combine((SCALE_SHAPE_DATASET(num_elements_per_vector<uint8_t>())), framework::dataset::make("DataType", DataType::U8)); |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEScaleFixture<uint8_t>, framework::DatasetMode::ALL, ASSEMBLE_DATASET(u8_shape, ScaleSamplingPolicySet)) |
| { |
| //Create valid region |
| TensorInfo src_info(_shape, 1, _data_type); |
| ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _policy, _sampling_policy, (_border_mode == BorderMode::UNDEFINED)); |
| |
| // Validate output |
| validate(Accessor(_target), _reference, valid_region, tolerance_u8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmallAlignCorners, NEScaleFixture<uint8_t>, framework::DatasetMode::ALL, ASSEMBLE_DATASET(u8_shape, ScaleAlignCornersSamplingPolicySet)) |
| { |
| //Create valid region |
| TensorInfo src_info(_shape, 1, _data_type); |
| ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _policy, _sampling_policy, (_border_mode == BorderMode::UNDEFINED)); |
| |
| // Validate output |
| validate(Accessor(_target), _reference, valid_region, tolerance_u8); |
| } |
| TEST_SUITE_END() // U8 |
| TEST_SUITE(S16) |
| const auto s16_shape = combine((SCALE_SHAPE_DATASET(num_elements_per_vector<int16_t>())), framework::dataset::make("DataType", DataType::S16)); |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEScaleFixture<int16_t>, framework::DatasetMode::ALL, ASSEMBLE_DATASET(s16_shape, ScaleSamplingPolicySet)) |
| { |
| //Create valid region |
| TensorInfo src_info(_shape, 1, _data_type); |
| ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _policy, _sampling_policy, (_border_mode == BorderMode::UNDEFINED)); |
| |
| // Validate output |
| validate(Accessor(_target), _reference, valid_region, tolerance_s16, tolerance_num_s16); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmallAlignCorners, NEScaleFixture<int16_t>, framework::DatasetMode::ALL, ASSEMBLE_DATASET(s16_shape, ScaleAlignCornersSamplingPolicySet)) |
| { |
| //Create valid region |
| TensorInfo src_info(_shape, 1, _data_type); |
| ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _policy, _sampling_policy, (_border_mode == BorderMode::UNDEFINED)); |
| |
| // Validate output |
| validate(Accessor(_target), _reference, valid_region, tolerance_s16, tolerance_num_s16); |
| } |
| TEST_SUITE_END() // S16 |
| TEST_SUITE_END() // Integer |
| |
| TEST_SUITE(Quantized) |
| TEST_SUITE(QASYMM8) |
| const auto qasymm8_shape = combine((SCALE_SHAPE_DATASET(num_elements_per_vector<uint8_t>())), framework::dataset::make("DataType", DataType::QASYMM8)); |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEScaleQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, ASSEMBLE_QUANTIZED_DATASET(qasymm8_shape, ScaleSamplingPolicySet, QuantizationInfoSet)) |
| { |
| //Create valid region |
| TensorInfo src_info(_shape, 1, _data_type); |
| ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _policy, _sampling_policy, (_border_mode == BorderMode::UNDEFINED)); |
| |
| // Validate output |
| validate(Accessor(_target), _reference, valid_region, tolerance_u8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmallAlignCorners, NEScaleQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, ASSEMBLE_QUANTIZED_DATASET(qasymm8_shape, ScaleAlignCornersSamplingPolicySet, |
| QuantizationInfoSet)) |
| { |
| //Create valid region |
| TensorInfo src_info(_shape, 1, _data_type); |
| ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _policy, _sampling_policy, (_border_mode == BorderMode::UNDEFINED)); |
| |
| // Validate output |
| validate(Accessor(_target), _reference, valid_region, tolerance_u8); |
| } |
| TEST_SUITE_END() // QASYMM8 |
| TEST_SUITE(QASYMM8_SIGNED) |
| const auto qasymm8_signed_shape = combine((SCALE_SHAPE_DATASET(num_elements_per_vector<int8_t>())), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)); |
| constexpr AbsoluteTolerance<int8_t> tolerance_qasymm8_signed{ 1 }; |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEScaleQuantizedFixture<int8_t>, framework::DatasetMode::ALL, ASSEMBLE_QUANTIZED_DATASET(qasymm8_signed_shape, ScaleSamplingPolicySet, QuantizationInfoSet)) |
| { |
| //Create valid region |
| TensorInfo src_info(_shape, 1, _data_type); |
| ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _policy, _sampling_policy, (_border_mode == BorderMode::UNDEFINED)); |
| |
| // Validate output |
| validate(Accessor(_target), _reference, valid_region, tolerance_qasymm8_signed); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmallAlignCorners, NEScaleQuantizedFixture<int8_t>, framework::DatasetMode::ALL, ASSEMBLE_QUANTIZED_DATASET(qasymm8_signed_shape, ScaleAlignCornersSamplingPolicySet, |
| QuantizationInfoSet)) |
| { |
| //Create valid region |
| TensorInfo src_info(_shape, 1, _data_type); |
| ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _policy, _sampling_policy, (_border_mode == BorderMode::UNDEFINED)); |
| |
| // Validate output |
| validate(Accessor(_target), _reference, valid_region, tolerance_qasymm8_signed); |
| } |
| TEST_SUITE_END() // QASYMM8_SIGNED |
| TEST_SUITE_END() // Quantized |
| |
| TEST_SUITE_END() // Scale |
| TEST_SUITE_END() // NEON |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |