diff options
Diffstat (limited to 'tests/validation/NEON/DilatedConvolutionLayer.cpp')
| -rw-r--r-- | tests/validation/NEON/DilatedConvolutionLayer.cpp | 16 |
1 files changed, 11 insertions, 5 deletions
diff --git a/tests/validation/NEON/DilatedConvolutionLayer.cpp b/tests/validation/NEON/DilatedConvolutionLayer.cpp index 2f0fce2ce0..fbfe8b8a7a 100644 --- a/tests/validation/NEON/DilatedConvolutionLayer.cpp +++ b/tests/validation/NEON/DilatedConvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2021 Arm Limited. + * Copyright (c) 2018-2021, 2023-2024 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -26,6 +26,7 @@ #include "arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h" #include "arm_compute/runtime/Tensor.h" #include "arm_compute/runtime/TensorAllocator.h" +#include "src/cpu/operators/CpuConv2d.h" #include "tests/NEON/Accessor.h" #include "tests/PaddingCalculator.h" #include "tests/datasets/DilatedConvolutionLayerDataset.h" @@ -49,7 +50,7 @@ const AbsoluteTolerance<float> abs_tolerance_f16(0.3f); const RelativeTolerance<half_float::half> rel_tolerance_f16(half_float::half(0.2f)); /**< Relative tolerance value for comparing reference's output against implementation's output for DataType::F16 */ constexpr float tolerance_num_f16 = 0.07f; /**< Tolerance number for FP16 */ #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ -constexpr AbsoluteTolerance<float> tolerance_qasymm8(0.0); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */ +constexpr AbsoluteTolerance<int32_t> tolerance_qasymm8(1); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */ /** CNN data types */ const auto CNNDataTypes = framework::dataset::make("DataType", @@ -96,7 +97,7 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z framework::dataset::make("Expected", { ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })), input_info, weights_info, output_info, conv_info, dilation, expected) { - ConvolutionMethod is_valid = NEConvolutionLayer::get_convolution_method(&input_info.clone()->set_is_resizable(false), + ConvolutionMethod is_valid = cpu::CpuConv2d::get_convolution_method(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info, WeightsInfo(), dilation); @@ -161,13 +162,18 @@ template <typename T> using NEGEMMDilatedConvolutionLayerQuantizedFixture = ConvolutionValidationQuantizedFixture<Tensor, Accessor, NEGEMMConvolutionLayer, T>; TEST_SUITE(Quantized) +/// @note: Every asymmetric quantized test where there's no fused activation will have its quantization info ignored +/// This is because 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, we can remove the explicit +/// quantization info. TEST_SUITE(QASYMM8) FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QASYMM8)), framework::dataset::make("DataLayout", { DataLayout::NCHW })), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + framework::dataset::make("IgnoredQuantizationInfo", { QuantizationInfo() })), framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output @@ -178,7 +184,7 @@ FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMDilatedConvolutionLayerQuantizedFixture<u framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QASYMM8)), framework::dataset::make("DataLayout", { DataLayout::NCHW })), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + framework::dataset::make("IgnoredQuantizationInfo", { QuantizationInfo() })), framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output |