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author | Georgios Pinitas <georgios.pinitas@arm.com> | 2017-10-30 15:56:32 +0000 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:35:24 +0000 |
commit | adaae7e453cc4cc07905daca68fa7b938555d581 (patch) | |
tree | 712003aa080cf577b2b2af318f219367897dc0e4 /tests/validation | |
parent | cf3935ffd4c67d9396c2435a3a28d3a159753105 (diff) | |
download | ComputeLibrary-adaae7e453cc4cc07905daca68fa7b938555d581.tar.gz |
COMPMID-647: Exclude padding pixels from averaging factor.
Adds support for excluding the padding pixels from the average scaling
factor calculation.
Change-Id: Ia13fbfeae235aff564db74191613921848231a01
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/93715
Reviewed-by: Robert Hughes <robert.hughes@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Diffstat (limited to 'tests/validation')
-rw-r--r-- | tests/validation/CL/PoolingLayer.cpp | 11 | ||||
-rw-r--r-- | tests/validation/CPP/PoolingLayer.cpp | 36 | ||||
-rw-r--r-- | tests/validation/NEON/PoolingLayer.cpp | 10 | ||||
-rw-r--r-- | tests/validation/fixtures/PoolingLayerFixture.h | 10 |
4 files changed, 41 insertions, 26 deletions
diff --git a/tests/validation/CL/PoolingLayer.cpp b/tests/validation/CL/PoolingLayer.cpp index 809c80f28c..87b86fedf2 100644 --- a/tests/validation/CL/PoolingLayer.cpp +++ b/tests/validation/CL/PoolingLayer.cpp @@ -44,13 +44,14 @@ namespace validation namespace { /** Input data set for float data types */ -const auto PoolingLayerDatasetFP = combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { 2, 3, 4, 7, 9 })), - framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })); +const auto PoolingLayerDatasetFP = combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { 2, 3, 4, 7, 9 })), + framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })), + framework::dataset::make("ExcludePadding", { true, false })); /** Input data set for quantized data types */ -const auto PoolingLayerDatasetQS = combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), framework::dataset::make("PoolingSize", { 2, 3 })), - framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })); - +const auto PoolingLayerDatasetQS = combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), framework::dataset::make("PoolingSize", { 2, 3 })), + framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })), + framework::dataset::make("ExcludePadding", { true, false })); constexpr AbsoluteTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for float types */ constexpr AbsoluteTolerance<float> tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for float types */ constexpr AbsoluteTolerance<float> tolerance_qs8(3); /**< Tolerance value for comparing reference's output against implementation's output for quantized input */ diff --git a/tests/validation/CPP/PoolingLayer.cpp b/tests/validation/CPP/PoolingLayer.cpp index 85a8343d87..4f755ce2c4 100644 --- a/tests/validation/CPP/PoolingLayer.cpp +++ b/tests/validation/CPP/PoolingLayer.cpp @@ -54,12 +54,13 @@ TensorShape calculate_output_shape(TensorShape shape, PoolingLayerInfo info) template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type> SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, PoolingLayerInfo info) { - const int pool_size = info.pool_size(); - PoolingType type = info.pool_type(); - int pool_stride_x = info.pad_stride_info().stride().first; - int pool_stride_y = info.pad_stride_info().stride().second; - int pad_x = info.pad_stride_info().pad().first; - int pad_y = info.pad_stride_info().pad().second; + const int pool_size = info.pool_size(); + PoolingType type = info.pool_type(); + int pool_stride_x = info.pad_stride_info().stride().first; + int pool_stride_y = info.pad_stride_info().stride().second; + int pad_x = info.pad_stride_info().pad().first; + int pad_y = info.pad_stride_info().pad().second; + bool exclude_padding = info.exclude_padding(); const auto w_src = static_cast<int>(src.shape()[0]); const auto h_src = static_cast<int>(src.shape()[1]); @@ -122,6 +123,11 @@ SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, PoolingLayerInfo info) hstart = std::max(hstart, 0); wend = std::min(wend, w_src); hend = std::min(hend, h_src); + // Exclude padding pixels from the average + if(exclude_padding) + { + pool = (hend - hstart) * (wend - wstart); + } if(type == PoolingType::AVG) { @@ -157,12 +163,13 @@ SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, PoolingLayerInfo info) template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type> SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, PoolingLayerInfo info) { - const int pool_size = info.pool_size(); - PoolingType type = info.pool_type(); - int pool_stride_x = info.pad_stride_info().stride().first; - int pool_stride_y = info.pad_stride_info().stride().second; - int pad_x = info.pad_stride_info().pad().first; - int pad_y = info.pad_stride_info().pad().second; + const int pool_size = info.pool_size(); + PoolingType type = info.pool_type(); + int pool_stride_x = info.pad_stride_info().stride().first; + int pool_stride_y = info.pad_stride_info().stride().second; + int pad_x = info.pad_stride_info().pad().first; + int pad_y = info.pad_stride_info().pad().second; + bool exclude_padding = info.exclude_padding(); const auto w_src = static_cast<int>(src.shape()[0]); const auto h_src = static_cast<int>(src.shape()[1]); @@ -224,6 +231,11 @@ SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, PoolingLayerInfo info) hstart = std::max(hstart, 0); wend = std::min(wend, w_src); hend = std::min(hend, h_src); + // Exclude padding pixels from the average + if(exclude_padding) + { + pool = (hend - hstart) * (wend - wstart); + } using namespace fixed_point_arithmetic; diff --git a/tests/validation/NEON/PoolingLayer.cpp b/tests/validation/NEON/PoolingLayer.cpp index a721fb9d15..13384620bd 100644 --- a/tests/validation/NEON/PoolingLayer.cpp +++ b/tests/validation/NEON/PoolingLayer.cpp @@ -44,12 +44,14 @@ namespace validation namespace { /** Input data set for float data types */ -const auto PoolingLayerDatasetFP = combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { 2, 3, 7, 9 })), - framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })); +const auto PoolingLayerDatasetFP = combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { 2, 3, 7, 9 })), + framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })), + framework::dataset::make("ExcludePadding", { true, false })); /** Input data set for quantized data types */ -const auto PoolingLayerDatasetQS = combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), framework::dataset::make("PoolingSize", { 2, 3 })), - framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })); +const auto PoolingLayerDatasetQS = combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), framework::dataset::make("PoolingSize", { 2, 3 })), + framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })), + framework::dataset::make("ExcludePadding", { false })); constexpr AbsoluteTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for float types */ #ifdef ARM_COMPUTE_AARCH64_V8_2 diff --git a/tests/validation/fixtures/PoolingLayerFixture.h b/tests/validation/fixtures/PoolingLayerFixture.h index 775c4125fc..09b9e0ef1a 100644 --- a/tests/validation/fixtures/PoolingLayerFixture.h +++ b/tests/validation/fixtures/PoolingLayerFixture.h @@ -47,10 +47,10 @@ class PoolingLayerValidationFixedPointFixture : public framework::Fixture { public: template <typename...> - void setup(TensorShape shape, PoolingType pool_type, int pool_size, PadStrideInfo pad_stride_info, DataType data_type, int fractional_bits) + void setup(TensorShape shape, PoolingType pool_type, int pool_size, PadStrideInfo pad_stride_info, bool exclude_padding, DataType data_type, int fractional_bits) { _fractional_bits = fractional_bits; - PoolingLayerInfo info(pool_type, pool_size, pad_stride_info); + PoolingLayerInfo info(pool_type, pool_size, pad_stride_info, exclude_padding); _target = compute_target(shape, info, data_type, fractional_bits); _reference = compute_reference(shape, info, data_type, fractional_bits); @@ -123,9 +123,9 @@ class PoolingLayerValidationFixture : public PoolingLayerValidationFixedPointFix { public: template <typename...> - void setup(TensorShape shape, PoolingType pool_type, int pool_size, PadStrideInfo pad_stride_info, DataType data_type) + void setup(TensorShape shape, PoolingType pool_type, int pool_size, PadStrideInfo pad_stride_info, bool exclude_padding, DataType data_type) { - PoolingLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, pool_type, pool_size, pad_stride_info, data_type, 0); + PoolingLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, pool_type, pool_size, pad_stride_info, exclude_padding, data_type, 0); } }; @@ -136,7 +136,7 @@ public: template <typename...> void setup(TensorShape shape, PoolingType pool_type, DataType data_type) { - PoolingLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, pool_type, shape.x(), PadStrideInfo(1, 1, 0, 0), data_type, 0); + PoolingLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, pool_type, shape.x(), PadStrideInfo(1, 1, 0, 0), true, data_type, 0); } }; } // namespace validation |