| /* |
| * Copyright (c) 2017-2023 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/CLDirectConvolutionLayer.h" |
| #include "tests/CL/CLAccessor.h" |
| #include "tests/PaddingCalculator.h" |
| #include "tests/datasets/DirectConvolutionLayerDataset.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/DirectConvolutionLayerFixture.h" |
| |
| /** Synced with tests/validation/dynamic_fusion/gpu/cl/DirectConv2d.cpp |
| * Please check there for any differences in the coverage |
| */ |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace |
| { |
| RelativeTolerance<half> tolerance_fp16(half(0.2)); /**< Tolerance for floating point tests */ |
| RelativeTolerance<float> tolerance_fp32(0.05f); /**< Tolerance for floating point tests */ |
| constexpr float abs_tolerance_f32(0.0001f); /**< Absolute tolerance for FP32 tests*/ |
| |
| constexpr float tolerance_num = 0.07f; /**< Tolerance number */ |
| constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance for quantized tests */ |
| |
| const auto data_strides = combine(framework::dataset::make("StrideX", 1, 3), framework::dataset::make("StrideY", 1, 3)); |
| const auto data_strides_small = combine(framework::dataset::make("StrideX", 1), framework::dataset::make("StrideY", 1)); |
| const auto data_ksize_one = combine(framework::dataset::make("PadX", 0, 1), combine(framework::dataset::make("PadY", 0, 1), framework::dataset::make("KernelSize", 1))); |
| const auto data_ksize_one_small = combine(framework::dataset::make("PadX", 0), combine(framework::dataset::make("PadY", 0), framework::dataset::make("KernelSize", 1))); |
| const auto data_ksize_three = combine(framework::dataset::make("PadX", 0, 2), combine(framework::dataset::make("PadY", 0, 2), framework::dataset::make("KernelSize", 3))); |
| const auto data_ksize_five = combine(framework::dataset::make("PadX", 0, 3), combine(framework::dataset::make("PadY", 0, 3), framework::dataset::make("KernelSize", 5))); |
| const auto data_ksize_nine = combine(framework::dataset::make("PadX", 0, 3), combine(framework::dataset::make("PadY", 0, 3), framework::dataset::make("KernelSize", 9))); |
| const auto data_ksize_nine_small = combine(framework::dataset::make("PadX", 0, 1), combine(framework::dataset::make("PadY", 0, 1), framework::dataset::make("KernelSize", 9))); |
| |
| const auto data_all_kernels = concat(concat(data_ksize_one, data_ksize_three), data_ksize_five); |
| |
| const auto data = combine(datasets::SmallDirectConvolutionShapes(), combine(data_strides, data_all_kernels)); |
| const auto data9x9 = combine(datasets::SmallDirectConvolutionShapes(), combine(data_strides, data_ksize_nine)); |
| const auto data_small = combine(datasets::SmallDirectConvolutionShapes(), combine(data_strides_small, data_ksize_one_small)); |
| const auto data_small9x9 = combine(datasets::SmallDirectConvolutionShapes(), combine(data_strides_small, data_ksize_nine_small)); |
| |
| /** Direct convolution nightly data set. */ |
| const auto data_nightly = combine(data, framework::dataset::make("NumKernels", { 1, 4 })); |
| const auto data_nightly_9x9 = combine(data9x9, framework::dataset::make("NumKernels", { 1, 4 })); |
| const auto data_nightly_usecase = combine(framework::dataset::make("InputShape", { TensorShape{ 3U, 800U, 800U } }), |
| combine(framework::dataset::make("StrideX", { 1 }), |
| combine(framework::dataset::make("StrideY", { 1 }), |
| combine(framework::dataset::make("PadX", { 4 }), |
| combine(framework::dataset::make("PadY", { 4 }), |
| combine(framework::dataset::make("KernelSize", 9), |
| framework::dataset::make("NumKernels", { 16 }))))))); |
| |
| /** Direct convolution precommit data set. */ |
| const auto data_precommit = combine(data_small, framework::dataset::make("NumKernels", { 1 })); |
| const auto data_precommit_9x9 = combine(data_small9x9, framework::dataset::make("NumKernels", { 1 })); |
| |
| /** Activation function Dataset*/ |
| const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", |
| { ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f) }); |
| } // namespace |
| |
| TEST_SUITE(CL) |
| TEST_SUITE(DirectConvolutionLayer) |
| |
| /** Check whether the configuration of a Direct Convolution layer with no |
| * bias leads to a successful execution. |
| */ |
| TEST_CASE(NoBias, framework::DatasetMode::PRECOMMIT) |
| { |
| const auto src_shape = TensorShape(27U, 13U, 2U); |
| const auto weights_shape = TensorShape(3U, 3U, 2U, 4U); |
| const auto bias_shape = TensorShape(4U); |
| const auto dst_shape = TensorShape(25U, 11U, 4U); |
| constexpr auto dt = DataType::F32; |
| |
| auto src = create_tensor<CLTensor>(src_shape, dt); |
| auto weights = create_tensor<CLTensor>(weights_shape, dt); |
| auto dst = create_tensor<CLTensor>(dst_shape, dt); |
| |
| const auto conv_info = PadStrideInfo(1, 1, 0, 0); |
| |
| // Create Direct Convolution function |
| CLDirectConvolutionLayer conv{}; |
| conv.configure(&src, &weights, nullptr, &dst, conv_info); |
| |
| src.allocator()->allocate(); |
| weights.allocator()->allocate(); |
| dst.allocator()->allocate(); |
| |
| library->fill_tensor_value(CLAccessor(src), 1.f); |
| library->fill_tensor_value(CLAccessor(weights), 1.f); |
| |
| conv.run(); |
| |
| // Compute reference to compare |
| SimpleTensor<float> ref_src{ src_shape, dt }; |
| SimpleTensor<float> ref_weights{ weights_shape, dt }; |
| SimpleTensor<float> ref_bias{ bias_shape, dt }; |
| library->fill_tensor_value(ref_src, 1.f); |
| library->fill_tensor_value(ref_weights, 1.f); |
| // No bias |
| library->fill_tensor_value(ref_bias, 0.f); |
| auto ref_dst = reference::convolution_layer<float>(ref_src, ref_weights, ref_bias, dst_shape, conv_info); |
| |
| validate(CLAccessor(dst), ref_dst); |
| } |
| |
| /** Check whether the case of rectangle kernels i.e. when width and height of the weight_shape are not equal |
| * would lead to successful run |
| */ |
| TEST_CASE(NonSquareKernel, framework::DatasetMode::PRECOMMIT) |
| { |
| auto src_shape = TensorShape(33U, 27U, 3U); |
| auto weights_shape = TensorShape(5U, 7U, 3U, 4U); // non-square kernel |
| const auto bias_shape = TensorShape(4U); |
| auto dst_shape = TensorShape(11U, 12U, 4U); |
| constexpr auto dt = DataType::F32; |
| |
| TensorShape src_shape_nhwc(src_shape); |
| TensorShape weights_shape_nhwc(weights_shape); |
| TensorShape dst_shape_nhwc(dst_shape); |
| |
| // Non-square shapes are only allowed for NHWC |
| permute(src_shape_nhwc, PermutationVector(2U, 0U, 1U)); |
| permute(weights_shape_nhwc, PermutationVector(2U, 0U, 1U)); |
| permute(dst_shape_nhwc, PermutationVector(2U, 0U, 1U)); |
| |
| auto src = create_tensor<CLTensor>(src_shape_nhwc, dt, 1, QuantizationInfo(), DataLayout::NHWC); |
| auto weights = create_tensor<CLTensor>(weights_shape_nhwc, dt, 1, QuantizationInfo(), DataLayout::NHWC); |
| auto dst = create_tensor<CLTensor>(dst_shape_nhwc, dt, 1, QuantizationInfo(), DataLayout::NHWC); |
| const auto conv_info = PadStrideInfo(3, 2, 1, 1, 2, 0, DimensionRoundingType::FLOOR); |
| |
| // Create direct convolution function |
| CLDirectConvolutionLayer conv{}; |
| conv.configure(&src, &weights, nullptr, &dst, conv_info); |
| |
| src.allocator()->allocate(); |
| weights.allocator()->allocate(); |
| dst.allocator()->allocate(); |
| |
| library->fill_tensor_value(CLAccessor(src), 1.f); |
| library->fill_tensor_value(CLAccessor(weights), 1.f); |
| |
| conv.run(); |
| |
| // Compute reference to compare |
| SimpleTensor<float> ref_src{ src_shape, dt }; |
| SimpleTensor<float> ref_weights{ weights_shape, dt }; |
| SimpleTensor<float> ref_bias{ bias_shape, dt }; |
| library->fill_tensor_value(ref_src, 1.f); |
| library->fill_tensor_value(ref_weights, 1.f); |
| // No bias |
| library->fill_tensor_value(ref_bias, 0.f); |
| auto ref_dst = reference::convolution_layer<float>(ref_src, ref_weights, ref_bias, dst_shape, conv_info); |
| |
| validate(CLAccessor(dst), ref_dst); |
| } |
| // *INDENT-OFF* |
| // clang-format off |
| DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid: Mismatching data type input/weights |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid: Mismatching input feature maps |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid weights dimensions |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported biases size |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported biases dimensions |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid output size |
| TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32), |
| }), |
| framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F16), |
| TensorInfo(TensorShape(3U, 3U, 3U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U, 3U, 2U, 4U, 3U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(1U, 1U, 2U, 4U), 1, DataType::F32), |
| })), |
| framework::dataset::make("BiasesInfo",{ TensorInfo(TensorShape(4U), 1, DataType::F32), |
| TensorInfo(TensorShape(4U), 1, DataType::F32), |
| TensorInfo(TensorShape(4U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U), 1, DataType::F32), |
| TensorInfo(TensorShape(4U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(4U), 1, DataType::F32), |
| TensorInfo(TensorShape(4U), 1, DataType::F32), |
| })), |
| framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(26U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(32U, 16U, 4U), 1, DataType::F32), |
| })), |
| framework::dataset::make("ConvInfo", { PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| })), |
| framework::dataset::make("ActivationInfo", |
| { |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) |
| })), |
| framework::dataset::make("Expected", { false, false, false, false, false, false, true })), |
| input_info, weights_info, biases_info, output_info, conv_info, act_info, expected) |
| { |
| bool is_valid = bool(CLDirectConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info, act_info)); |
| ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); |
| } |
| // clang-format on |
| // *INDENT-ON* |
| |
| template <typename T> |
| using CLDirectConvolutionLayerFixture = DirectConvolutionValidationFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>; |
| template <typename T> |
| using CLDirectConvolutionLayerMixedDataLayoutFixture = DirectConvolutionValidationFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T, true>; |
| template <typename T> |
| using CLDirectConvolutionValidationWithTensorShapesFixture = DirectConvolutionValidationWithTensorShapesFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>; |
| template <typename T> |
| using CLDirectConvolutionLayerQuantizedFixture = DirectConvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>; |
| template <typename T> |
| using CLDirectConvolutionLayerQuantizedMixedDataLayoutFixture = DirectConvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T, true>; |
| template <typename T> |
| using CLDirectConvolutionValidationWithTensorShapesQuantizedFixture = DirectConvolutionValidationWithTensorShapesQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>; |
| |
| TEST_SUITE(NHWC) |
| // *INDENT-OFF* |
| // clang-format off |
| DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputInfo", { |
| TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Arbitrary weight sizes for NHWC are supported |
| TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Non-rectangular weights dimensions for NHWC are supported |
| TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Strides > 2 for any kernel sizes for NHWC are supported |
| }), |
| framework::dataset::make("WeightsInfo",{ |
| TensorInfo(TensorShape(2U, 13U, 13U, 4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(2U, 5U, 3U, 4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(2U, 3U, 3U, 4U), 1, DataType::F32, DataLayout::NHWC), |
| })), |
| framework::dataset::make("BiasesInfo",{ |
| TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC), |
| })), |
| framework::dataset::make("OutputInfo",{ |
| TensorInfo(TensorShape(4U, 15U, 1U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(4U, 23U, 11U), 1, DataType::F32, DataLayout::NHWC), |
| TensorInfo(TensorShape(4U, 9U, 4U), 1, DataType::F32, DataLayout::NHWC), |
| })), |
| framework::dataset::make("ConvInfo", { |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(3, 3, 0, 0), |
| })), |
| framework::dataset::make("ActivationInfo", |
| { |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| })), |
| framework::dataset::make("Expected", { true, true, true })), |
| input_info, weights_info, biases_info, output_info, conv_info, act_info, expected) |
| { |
| bool is_valid = bool(CLDirectConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info, act_info)); |
| ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); |
| } |
| TEST_SUITE(FP16) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, |
| combine(combine(combine(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(27U, 13U, 23U), |
| TensorShape(19U, 5U, 16U, 4U), |
| TensorShape(13U, 5U, 17U, 2U), |
| TensorShape(32U, 37U, 13U) } ), |
| framework::dataset::make("StrideX", { 1, 3, 1, 1 })), |
| framework::dataset::make("StrideY", { 1, 3, 2, 1 })), |
| framework::dataset::make("PadX", { 1, 3, 0, 4 })), |
| framework::dataset::make("PadY", { 1, 3, 0, 4 })), |
| framework::dataset::make("KernelSize", { 3, 8, 1, 9 })), |
| framework::dataset::make("NumKernels", { 17, 3, 1, 19 })), |
| framework::dataset::make("DataType", DataType::F16)), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )), |
| framework::dataset::make("DataLayout", DataLayout::NHWC))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, |
| combine(combine(combine(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(800U, 800U, 3U) } ), |
| framework::dataset::make("StrideX", { 1 })), |
| framework::dataset::make("StrideY", { 1 })), |
| framework::dataset::make("PadX", { 1 })), |
| framework::dataset::make("PadY", { 1 })), |
| framework::dataset::make("KernelSize", { 9 })), |
| framework::dataset::make("NumKernels", { 3 })), |
| framework::dataset::make("DataType", DataType::F16)), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::IDENTITY) )), |
| framework::dataset::make("DataLayout", DataLayout::NHWC))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num); |
| } |
| |
| TEST_SUITE_END() // FP16 |
| |
| TEST_SUITE(FP32) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, |
| combine(combine(combine(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(27U, 13U, 23U), |
| TensorShape(19U, 5U, 16U, 4U), |
| TensorShape(13U, 5U, 17U, 2U), |
| TensorShape(32U, 37U, 13U) } ), |
| framework::dataset::make("StrideX", { 1, 3, 1, 1 })), |
| framework::dataset::make("StrideY", { 1, 3, 2, 1 })), |
| framework::dataset::make("PadX", { 1, 3, 0, 4 })), |
| framework::dataset::make("PadY", { 1, 3, 0, 4 })), |
| framework::dataset::make("KernelSize", { 3, 8, 1, 9 })), |
| framework::dataset::make("NumKernels", { 17, 3, 1, 19 })), |
| framework::dataset::make("DataType", DataType::F32)), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )), |
| framework::dataset::make("DataLayout", DataLayout::NHWC))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_fp32, 0.0, abs_tolerance_f32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, CLDirectConvolutionLayerMixedDataLayoutFixture<float>, framework::DatasetMode::PRECOMMIT, |
| combine(combine(combine(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(27U, 13U, 23U), |
| TensorShape(19U, 5U, 16U, 4U), |
| TensorShape(13U, 5U, 17U, 2U), |
| TensorShape(32U, 37U, 13U) } ), |
| framework::dataset::make("StrideX", { 1 })), |
| framework::dataset::make("StrideY", { 2 })), |
| framework::dataset::make("PadX", { 1 })), |
| framework::dataset::make("PadY", { 3 })), |
| framework::dataset::make("KernelSize", { 3 })), |
| framework::dataset::make("NumKernels", { 3 })), |
| framework::dataset::make("DataType", DataType::F32)), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )), |
| framework::dataset::make("DataLayout", DataLayout::NHWC))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_fp32, 0.0, abs_tolerance_f32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, |
| combine(combine(combine(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(800U, 800U, 3U) } ), |
| framework::dataset::make("StrideX", { 1 })), |
| framework::dataset::make("StrideY", { 1 })), |
| framework::dataset::make("PadX", { 1 })), |
| framework::dataset::make("PadY", { 1 })), |
| framework::dataset::make("KernelSize", { 9 })), |
| framework::dataset::make("NumKernels", { 3 })), |
| framework::dataset::make("DataType", DataType::F32)), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::IDENTITY) )), |
| framework::dataset::make("DataLayout", DataLayout::NHWC))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_fp32, 0.0, abs_tolerance_f32); |
| } |
| TEST_SUITE_END() // FP32 |
| |
| TEST_SUITE(Quantized) |
| TEST_SUITE(QASYMM8) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, |
| combine(combine(combine(combine(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(27U, 13U, 23U), |
| TensorShape(19U, 5U, 16U, 4U), |
| TensorShape(13U, 5U, 17U, 2U), |
| TensorShape(32U, 37U, 13U) } ), |
| framework::dataset::make("StrideX", { 1, 3, 1, 1 })), |
| framework::dataset::make("StrideY", { 1, 3, 2, 1 })), |
| framework::dataset::make("PadX", { 1, 3, 0, 4 })), |
| framework::dataset::make("PadY", { 1, 3, 0, 4 })), |
| framework::dataset::make("KernelSize", { 3, 8, 1, 9 })), |
| framework::dataset::make("NumKernels", { 7, 3, 1, 3 })), |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| framework::dataset::make("QuantizationInfo", QuantizationInfo(1.1f / 255, 10))), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )), |
| framework::dataset::make("DataLayout", DataLayout::NHWC))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, CLDirectConvolutionLayerQuantizedMixedDataLayoutFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, |
| combine(combine(combine(combine(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(27U, 13U, 23U), |
| TensorShape(19U, 5U, 16U, 4U), |
| TensorShape(13U, 5U, 17U, 2U), |
| TensorShape(32U, 37U, 13U) } ), |
| framework::dataset::make("StrideX", { 1 })), |
| framework::dataset::make("StrideY", { 2 })), |
| framework::dataset::make("PadX", { 1 })), |
| framework::dataset::make("PadY", { 1 })), |
| framework::dataset::make("KernelSize", { 3 })), |
| framework::dataset::make("NumKernels", { 3 })), |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| framework::dataset::make("QuantizationInfo", QuantizationInfo(1.1f / 255, 10))), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )), |
| framework::dataset::make("DataLayout", DataLayout::NHWC))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, |
| combine(combine(combine(combine(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(800U, 800U, 3U) } ), |
| framework::dataset::make("StrideX", { 1 })), |
| framework::dataset::make("StrideY", { 1 })), |
| framework::dataset::make("PadX", { 1 })), |
| framework::dataset::make("PadY", { 1 })), |
| framework::dataset::make("KernelSize", { 9 })), |
| framework::dataset::make("NumKernels", { 3 })), |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| framework::dataset::make("QuantizationInfo", QuantizationInfo(2.f / 255, 10))), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )), |
| framework::dataset::make("DataLayout", DataLayout::NHWC))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| |
| TEST_SUITE_END() // QASYMM8 |
| TEST_SUITE(QASYMM8_SIGNED) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT, |
| combine(combine(combine(combine(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(27U, 13U, 23U), |
| TensorShape(19U, 5U, 16U, 4U), |
| TensorShape(13U, 5U, 17U, 2U), |
| TensorShape(32U, 37U, 13U) } ), |
| framework::dataset::make("StrideX", { 1, 3, 1, 1 })), |
| framework::dataset::make("StrideY", { 1, 3, 2, 1 })), |
| framework::dataset::make("PadX", { 1, 3, 0, 4 })), |
| framework::dataset::make("PadY", { 1, 3, 0, 4 })), |
| framework::dataset::make("KernelSize", { 3, 8, 1, 9 })), |
| framework::dataset::make("NumKernels", { 7, 3, 1, 3 })), |
| framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), |
| framework::dataset::make("QuantizationInfo", QuantizationInfo(2.f / 255, 10))), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )), |
| framework::dataset::make("DataLayout", DataLayout::NHWC))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, CLDirectConvolutionLayerQuantizedMixedDataLayoutFixture<int8_t>, framework::DatasetMode::PRECOMMIT, |
| combine(combine(combine(combine(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(27U, 13U, 23U), |
| TensorShape(19U, 5U, 16U, 4U), |
| TensorShape(13U, 5U, 17U, 2U), |
| TensorShape(32U, 37U, 13U) } ), |
| framework::dataset::make("StrideX", { 1 })), |
| framework::dataset::make("StrideY", { 1 })), |
| framework::dataset::make("PadX", { 1 })), |
| framework::dataset::make("PadY", { 1 })), |
| framework::dataset::make("KernelSize", { 3 })), |
| framework::dataset::make("NumKernels", { 3 })), |
| framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), |
| framework::dataset::make("QuantizationInfo", QuantizationInfo(2.f / 255, 10))), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )), |
| framework::dataset::make("DataLayout", DataLayout::NHWC))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerQuantizedFixture<int8_t>, framework::DatasetMode::NIGHTLY, |
| combine(combine(combine(combine(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(800U, 800U, 3U) } ), |
| framework::dataset::make("StrideX", { 1 })), |
| framework::dataset::make("StrideY", { 1 })), |
| framework::dataset::make("PadX", { 1 })), |
| framework::dataset::make("PadY", { 1 })), |
| framework::dataset::make("KernelSize", { 9 })), |
| framework::dataset::make("NumKernels", { 3 })), |
| framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), |
| framework::dataset::make("QuantizationInfo", QuantizationInfo(2.f / 255, 10))), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )), |
| framework::dataset::make("DataLayout", DataLayout::NHWC))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| TEST_SUITE_END() // QASYMM8_SIGNED |
| TEST_SUITE_END() // Quantized |
| TEST_SUITE_END() // NHWC |
| |
| TEST_SUITE(NCHW) |
| DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputInfo", { |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, DataLayout::NCHW), // Unsupported kernel width |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, DataLayout::NCHW), // Non-rectangular weights dimensions are unsupported |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, DataLayout::NCHW) // Unsupported stride |
| }), |
| framework::dataset::make("WeightsInfo",{ |
| TensorInfo(TensorShape(11U, 11U, 2U, 4U), 1, DataType::F32, DataLayout::NCHW), |
| TensorInfo(TensorShape(5U, 3U, 2U, 4U), 1, DataType::F32, DataLayout::NCHW), |
| TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32, DataLayout::NCHW) |
| })), |
| framework::dataset::make("BiasesInfo",{ |
| TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NCHW), |
| TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NCHW), |
| TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NCHW) |
| })), |
| framework::dataset::make("OutputInfo",{ |
| TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32, DataLayout::NCHW), |
| TensorInfo(TensorShape(23U, 11U, 4U), 1, DataType::F32, DataLayout::NCHW), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32, DataLayout::NCHW) |
| })), |
| framework::dataset::make("ConvInfo", { |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(3, 3, 0, 0) |
| })), |
| framework::dataset::make("ActivationInfo", |
| { |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) |
| })), |
| framework::dataset::make("Expected", { false, false, false})), |
| input_info, weights_info, biases_info, output_info, conv_info, act_info, expected) |
| { |
| bool is_valid = bool(CLDirectConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info, act_info)); |
| ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); |
| } |
| // clang-format on |
| // *INDENT-ON* |
| |
| TEST_SUITE(Float) |
| TEST_SUITE(FP16) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit, framework::dataset::make("DataType", DataType::F16)), |
| ActivationFunctionsDataset), |
| framework::dataset::make("DataLayout", DataLayout::NCHW))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data_nightly, framework::dataset::make("DataType", DataType::F16)), |
| ActivationFunctionsDataset), |
| framework::dataset::make("DataLayout", DataLayout::NCHW))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num); |
| } |
| TEST_SUITE_END() // FP16 |
| |
| TEST_SUITE(FP32) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit, framework::dataset::make("DataType", |
| DataType::F32)), |
| ActivationFunctionsDataset), |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_fp32, 0.0, abs_tolerance_f32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, CLDirectConvolutionLayerMixedDataLayoutFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit, |
| framework::dataset::make("DataType", |
| DataType::F32)), |
| ActivationFunctionsDataset), |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_fp32, 0.0, abs_tolerance_f32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data_nightly, framework::dataset::make("DataType", DataType::F32)), |
| ActivationFunctionsDataset), |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_fp32, 0.0, abs_tolerance_f32); |
| } |
| TEST_SUITE_END() // FP32 |
| |
| TEST_SUITE(FP32_CustomDataset) |
| FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionValidationWithTensorShapesFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::DirectConvolutionLayerDataset(), |
| framework::dataset::make("DataType", DataType::F32)), |
| ActivationFunctionsDataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_fp32, 0.0, abs_tolerance_f32); |
| } |
| TEST_SUITE_END() // FP32_CustomDataset |
| TEST_SUITE_END() // Float |
| |
| /// @note: Every quantized test has a version with or without activation because the quantization info given is |
| /// ignored when there is no activation. Instead of using the same quantization information for all the tensors, the |
| /// fixture generates separate quantization info for each input and the output tensor. |
| /// When we can also support dynamic quantization with the presence of activation, these two versions should be merged |
| /// again, with the explicitly specified quantization info removed |
| const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationInfo", |
| { |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f) |
| }); |
| const auto NoActivation = framework::dataset::make("ActivationInfo", |
| { |
| ActivationLayerInfo() |
| }); |
| const auto IgnoredQuantizationInfo = framework::dataset::make("IgnoredQuantizationInfo", |
| { |
| QuantizationInfo() |
| }); |
| TEST_SUITE(Quantized) |
| TEST_SUITE(QASYMM8) |
| FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, CLDirectConvolutionLayerQuantizedMixedDataLayoutFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(data_precommit, |
| framework::dataset::make("DataType", DataType::QASYMM8), |
| IgnoredQuantizationInfo, |
| NoActivation, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunMixedDataLayoutWithActivation, CLDirectConvolutionLayerQuantizedMixedDataLayoutFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(data_precommit, |
| framework::dataset::make("DataType", DataType::QASYMM8), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10) }), |
| QuantizedActivationFunctionsDataset, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(data_precommit, |
| framework::dataset::make("DataType", DataType::QASYMM8), |
| IgnoredQuantizationInfo, |
| NoActivation, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmallWithActivation, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(data_precommit, |
| framework::dataset::make("DataType", DataType::QASYMM8), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10), QuantizationInfo(1.1f, 10) }), |
| QuantizedActivationFunctionsDataset, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmall9x9, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(data_precommit_9x9, |
| framework::dataset::make("DataType", |
| DataType::QASYMM8), |
| IgnoredQuantizationInfo, |
| NoActivation, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmall9x9WithActivation, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(data_precommit_9x9, |
| framework::dataset::make("DataType", |
| DataType::QASYMM8), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(3.f / 255, 10), QuantizationInfo(1.1f, 10) }), |
| QuantizedActivationFunctionsDataset, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(data_nightly, framework::dataset::make("DataType", |
| DataType::QASYMM8), |
| IgnoredQuantizationInfo, |
| NoActivation, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLargeWithActivation, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(data_nightly, framework::dataset::make("DataType", |
| DataType::QASYMM8), |
| framework::dataset::make("QuantizationInfoIf", { QuantizationInfo(2.f / 255, 10), QuantizationInfo(1.1f, 10) }), |
| QuantizedActivationFunctionsDataset, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge9x9, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(data_nightly_9x9, |
| framework::dataset::make("DataType", |
| DataType::QASYMM8), |
| IgnoredQuantizationInfo, |
| NoActivation, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge9x9WithActivation, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(data_nightly_9x9, |
| framework::dataset::make("DataType", |
| DataType::QASYMM8), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(3.f / 255, 10), QuantizationInfo(1.1f, 10) }), |
| QuantizedActivationFunctionsDataset, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(CustomDataset, CLDirectConvolutionValidationWithTensorShapesQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, |
| combine(datasets::DirectConvolutionLayerDataset(), |
| framework::dataset::make("DataType", DataType::QASYMM8), |
| IgnoredQuantizationInfo, |
| NoActivation, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(CustomDatasetWithActivation, CLDirectConvolutionValidationWithTensorShapesQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, |
| combine(datasets::DirectConvolutionLayerDataset(), |
| framework::dataset::make("DataType", DataType::QASYMM8), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 127), QuantizationInfo(1.1f, 10) }), |
| QuantizedActivationFunctionsDataset, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| TEST_SUITE_END() // QASYMM8 |
| |
| TEST_SUITE(QASYMM8_SIGNED) |
| |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL, combine(data_precommit, framework::dataset::make("DataType", |
| DataType::QASYMM8_SIGNED), |
| IgnoredQuantizationInfo, |
| NoActivation, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmallWithActivation, CLDirectConvolutionLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL, combine(data_precommit, framework::dataset::make("DataType", |
| DataType::QASYMM8_SIGNED), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10), QuantizationInfo(1.1f, -10) }), |
| QuantizedActivationFunctionsDataset, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, CLDirectConvolutionLayerQuantizedMixedDataLayoutFixture<int8_t>, framework::DatasetMode::ALL, combine(data_precommit, |
| framework::dataset::make("DataType", |
| DataType::QASYMM8_SIGNED), |
| IgnoredQuantizationInfo, |
| NoActivation, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunMixedDataLayoutWithActivation, CLDirectConvolutionLayerQuantizedMixedDataLayoutFixture<int8_t>, framework::DatasetMode::ALL, combine(data_precommit, |
| framework::dataset::make("DataType", |
| DataType::QASYMM8_SIGNED), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.1f, -10) }), |
| QuantizedActivationFunctionsDataset, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmall9x9, CLDirectConvolutionLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL, combine(data_precommit_9x9, |
| framework::dataset::make("DataType", |
| DataType::QASYMM8_SIGNED), |
| IgnoredQuantizationInfo, |
| NoActivation, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmall9x9WithActivation, CLDirectConvolutionLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL, combine(data_precommit_9x9, |
| framework::dataset::make("DataType", |
| DataType::QASYMM8_SIGNED), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10), QuantizationInfo(1.1f, 10) }), |
| QuantizedActivationFunctionsDataset, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunCustomDataset, CLDirectConvolutionValidationWithTensorShapesQuantizedFixture<int8_t>, framework::DatasetMode::NIGHTLY, |
| combine(datasets::DirectConvolutionLayerDataset(), |
| framework::dataset::make("DataType", DataType::QASYMM8_SIGNED), |
| IgnoredQuantizationInfo, |
| NoActivation, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunCustomDatasetWithActivation, CLDirectConvolutionValidationWithTensorShapesQuantizedFixture<int8_t>, framework::DatasetMode::NIGHTLY, |
| combine(datasets::DirectConvolutionLayerDataset(), |
| framework::dataset::make("DataType", DataType::QASYMM8_SIGNED), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 127), QuantizationInfo(1.1f, 10) }), |
| QuantizedActivationFunctionsDataset, |
| framework::dataset::make("DataLayout", { DataLayout::NCHW }))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| |
| TEST_SUITE_END() // QASYMM8_SIGNED |
| TEST_SUITE_END() // Quantized |
| TEST_SUITE_END() // NCHW |
| TEST_SUITE_END() // DirectConvolutionLayer |
| TEST_SUITE_END() // CL |
| |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |