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Diffstat (limited to 'tests/validation/NEON/DilatedConvolutionLayer.cpp')
-rw-r--r--tests/validation/NEON/DilatedConvolutionLayer.cpp61
1 files changed, 12 insertions, 49 deletions
diff --git a/tests/validation/NEON/DilatedConvolutionLayer.cpp b/tests/validation/NEON/DilatedConvolutionLayer.cpp
index 97afa24ed5..fbfe8b8a7a 100644
--- a/tests/validation/NEON/DilatedConvolutionLayer.cpp
+++ b/tests/validation/NEON/DilatedConvolutionLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2019 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);
@@ -108,49 +109,6 @@ TEST_SUITE_END() // DilatedConvolutionLayer
TEST_SUITE(GEMMDilatedConvolutionLayer)
-DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::SmallDilatedConvolutionLayerDataset(),
- CNNDataTypes),
- input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type)
-{
- auto bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
-
- // Create tensors
- Tensor src = create_tensor<Tensor>(input_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
- Tensor weights = create_tensor<Tensor>(weights_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
- Tensor bias = create_tensor<Tensor>(bias_shape, bias_data_type, 1, QuantizationInfo(2.f / 255.f, 127));
- Tensor dst = create_tensor<Tensor>(output_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
-
- ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
-
- const QuantizationInfo src_quantization_info = src.info()->quantization_info();
- const QuantizationInfo weights_quantization_info = weights.info()->quantization_info();
-
- // Create and configure function
- NEGEMMConvolutionLayer conv;
- conv.configure(&src, &weights, &bias, &dst, info, WeightsInfo(), dilation);
-
- // Validate valid region
- const ValidRegion src_valid_region = shape_to_valid_region(input_shape);
- const ValidRegion weights_valid_region = shape_to_valid_region(weights_shape);
- const ValidRegion bias_valid_region = shape_to_valid_region(bias_shape);
- const ValidRegion dst_valid_region = shape_to_valid_region(output_shape);
-
- validate(src.info()->valid_region(), src_valid_region);
- validate(weights.info()->valid_region(), weights_valid_region);
- validate(bias.info()->valid_region(), bias_valid_region);
- validate(dst.info()->valid_region(), dst_valid_region);
-
- // Validate QuantizationInfo
- ARM_COMPUTE_EXPECT(src.info()->quantization_info() == src_quantization_info, framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(weights.info()->quantization_info() == weights_quantization_info, framework::LogLevel::ERRORS);
-
- // Validate padding
- //TODO(COMPMID-415) Need to validate padding?
-}
-
template <typename T>
using NEGEMMDilatedConvolutionLayerFixture = ConvolutionValidationFixture<Tensor, Accessor, NEConvolutionLayer, T>;
@@ -204,13 +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
@@ -221,7 +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
@@ -231,7 +194,7 @@ TEST_SUITE_END() // QASYMM8
TEST_SUITE_END() // Quantized
TEST_SUITE_END() // GEMMDilatedConvolutionLayer
-TEST_SUITE_END() // NEON
+TEST_SUITE_END() // Neon
} // namespace validation
} // namespace test
} // namespace arm_compute