diff options
Diffstat (limited to 'tests/validation/CL/DirectConvolutionLayer.cpp')
| -rw-r--r-- | tests/validation/CL/DirectConvolutionLayer.cpp | 724 |
1 files changed, 605 insertions, 119 deletions
diff --git a/tests/validation/CL/DirectConvolutionLayer.cpp b/tests/validation/CL/DirectConvolutionLayer.cpp index 3c39151a29..ff22ae5ef0 100644 --- a/tests/validation/CL/DirectConvolutionLayer.cpp +++ b/tests/validation/CL/DirectConvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2020 ARM Limited. + * Copyright (c) 2017-2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -35,6 +35,9 @@ #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 @@ -43,11 +46,12 @@ namespace validation { namespace { -// COMPMID-517 Investigate the mismatch to see whether it is a real bug -RelativeTolerance<half> tolerance_fp16(half(0.2)); /**< Tolerance for floating point tests */ -RelativeTolerance<float> tolerance_fp32(0.02f); /**< Tolerance for floating point tests */ -constexpr float tolerance_num = 0.07f; /**< Tolerance number */ -constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance for quantized tests */ +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)); @@ -66,8 +70,16 @@ const auto data_small = combine(datasets::SmallDirectConvolutionShapes(), com 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 = 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 })); @@ -80,57 +92,132 @@ const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo TEST_SUITE(CL) TEST_SUITE(DirectConvolutionLayer) -//TODO(COMPMID-415): Configuration tests? +/** 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), // Mismatching data type input/weights - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching input feature maps - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported kernel width - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Non-rectangular weights dimensions + 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), // Invalid stride - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid biases size - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid biases 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(27U, 13U, 2U), 1, DataType::F32), // Window shrink 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(11U, 11U, 2U, 4U), 1, DataType::F32), - TensorInfo(TensorShape(5U, 3U, 2U, 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(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(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), - 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(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(25U, 11U, 4U), 1, DataType::F32), TensorInfo(TensorShape(32U, 16U, 4U), 1, DataType::F32), })), framework::dataset::make("ConvInfo", { PadStrideInfo(1, 1, 0, 0), @@ -138,18 +225,20 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( PadStrideInfo(1, 1, 0, 0), PadStrideInfo(1, 1, 0, 0), PadStrideInfo(1, 1, 0, 0), - PadStrideInfo(3, 3, 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, false, false, false, false, true })), + 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)); @@ -161,7 +250,307 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( 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) @@ -179,49 +568,29 @@ FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerFixture<half>, framewor // Validate output validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num); } -FIXTURE_DATA_TEST_CASE(RunLarge9x9, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data_nightly_9x9, framework::dataset::make("DataType", - DataType::F16)), - ActivationFunctionsDataset), - framework::dataset::make("DataLayout", { DataLayout::NHWC }))) -{ - validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num); -} -FIXTURE_DATA_TEST_CASE(RunSmall9x9, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit_9x9, framework::dataset::make("DataType", - DataType::F16)), - ActivationFunctionsDataset), - 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(data_precommit, framework::dataset::make("DataType", DataType::F32)), ActivationFunctionsDataset), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) + framework::dataset::make("DataLayout", { DataLayout::NCHW }))) { - validate(CLAccessor(_target), _reference, tolerance_fp32); + 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, DataLayout::NHWC }))) -{ - validate(CLAccessor(_target), _reference, tolerance_fp32); -} -FIXTURE_DATA_TEST_CASE(RunLarge9x9, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data_nightly_9x9, framework::dataset::make("DataType", - DataType::F32)), - ActivationFunctionsDataset), - framework::dataset::make("DataLayout", { DataLayout::NHWC }))) +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); + validate(CLAccessor(_target), _reference, tolerance_fp32, 0.0, abs_tolerance_f32); } -FIXTURE_DATA_TEST_CASE(RunSmall9x9, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit_9x9, framework::dataset::make("DataType", - DataType::F32)), - ActivationFunctionsDataset), - framework::dataset::make("DataLayout", { DataLayout::NHWC }))) +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); + validate(CLAccessor(_target), _reference, tolerance_fp32, 0.0, abs_tolerance_f32); } TEST_SUITE_END() // FP32 @@ -231,96 +600,202 @@ FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionValidationWithTensorShapesFixture ActivationFunctionsDataset)) { // Validate output - validate(CLAccessor(_target), _reference, tolerance_fp32); + validate(CLAccessor(_target), _reference, tolerance_fp32, 0.0, abs_tolerance_f32); } TEST_SUITE_END() // FP32_CustomDataset TEST_SUITE_END() // Float -template <typename T> -using CLDirectConvolutionLayerQuantizedFixture = DirectConvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>; -template <typename T> -using CLDirectConvolutionValidationWithTensorShapesQuantizedFixture = DirectConvolutionValidationWithTensorShapesQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>; - +/// @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(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(RunSmall, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(data_precommit, +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)), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10), QuantizationInfo(1.1f, 10) })), - QuantizedActivationFunctionsDataset), - framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) + DataType::QASYMM8), + IgnoredQuantizationInfo, + NoActivation, + 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(combine(combine(combine(data_precommit_9x9, +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(2.f / 255, 10), QuantizationInfo(1.1f, 10) })), - QuantizedActivationFunctionsDataset), + 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(combine(combine(combine(data_nightly, 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, DataLayout::NHWC }))) +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(RunLarge9x9, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(data_nightly_9x9, +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)), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10), QuantizationInfo(1.1f, 10) })), - QuantizedActivationFunctionsDataset), + DataType::QASYMM8), + IgnoredQuantizationInfo, + NoActivation, framework::dataset::make("DataLayout", { DataLayout::NCHW }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8); } - -TEST_SUITE_END() // QASYMM8 - -TEST_SUITE(QASYMM8_CustomDataset) -FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionValidationWithTensorShapesQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, - combine(combine(combine(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, DataLayout::NHWC }))) +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); } -TEST_SUITE_END() // QASYMM8_CustomDataset +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(combine(combine(combine(data_precommit, framework::dataset::make("DataType", - DataType::QASYMM8_SIGNED)), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10), QuantizationInfo(1.1f, -10) })), - QuantizedActivationFunctionsDataset), +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(RunSmall9x9, CLDirectConvolutionLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(data_precommit_9x9, +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)), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10), QuantizationInfo(1.1f, 10) })), - QuantizedActivationFunctionsDataset), + 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 @@ -328,22 +803,33 @@ FIXTURE_DATA_TEST_CASE(RunSmall9x9, CLDirectConvolutionLayerQuantizedFixture<int } FIXTURE_DATA_TEST_CASE(RunCustomDataset, CLDirectConvolutionValidationWithTensorShapesQuantizedFixture<int8_t>, framework::DatasetMode::NIGHTLY, - combine(combine(combine(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, DataLayout::NHWC }))) + 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); } -TEST_SUITE_END() // QASYMM8_SIGNED +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() // Float +TEST_SUITE_END() // CL + } // namespace validation } // namespace test } // namespace arm_compute |