COMPMID-683: Normalization layer API clarification.
Adds a is_scaled parameter in the NormalizationLayerInfo that flags if
the alpha parameter should be scaled by the normalization size of not.
Unscaled parameter is used by [Krichevksy 2012] which is used in
AndroidNN and TensorFlow LRN layer.
Change-Id: Iad2aa5e688cf4dcd6cc77a6e28c0663764f34ccb
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/96102
Reviewed-by: Diego Lopez Recas <diego.lopezrecas@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
diff --git a/tests/validation/CL/NormalizationLayer.cpp b/tests/validation/CL/NormalizationLayer.cpp
index 4fca6bf..18f0c37 100644
--- a/tests/validation/CL/NormalizationLayer.cpp
+++ b/tests/validation/CL/NormalizationLayer.cpp
@@ -52,9 +52,14 @@
constexpr AbsoluteTolerance<int16_t> tolerance_qs16(3);
/** Input data set. */
-const auto NormalizationDataset = combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("NormType", { NormType::IN_MAP_1D, NormType::CROSS_MAP })),
- framework::dataset::make("NormalizationSize", 3, 9, 2)),
- framework::dataset::make("Beta", { 0.5f, 1.f, 2.f }));
+const auto NormalizationDataset = combine(combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("NormType", { NormType::IN_MAP_1D, NormType::CROSS_MAP })),
+ framework::dataset::make("NormalizationSize", 3, 9, 2)),
+ framework::dataset::make("Beta", { 0.5f, 1.f, 2.f })),
+ framework::dataset::make("IsScaled", { true }));
+const auto NormalizationDatasetFP32 = combine(combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("NormType", { NormType::IN_MAP_1D, NormType::CROSS_MAP })),
+ framework::dataset::make("NormalizationSize", 3, 9, 2)),
+ framework::dataset::make("Beta", { 0.5f, 1.f, 2.f })),
+ framework::dataset::make("IsScaled", { true, false }));
} // namespace
TEST_SUITE(CL)
@@ -80,12 +85,12 @@
TEST_SUITE_END()
TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(NormalizationDataset, framework::dataset::make("DataType", DataType::F32)))
+FIXTURE_DATA_TEST_CASE(RunSmall, CLNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(NormalizationDatasetFP32, framework::dataset::make("DataType", DataType::F32)))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLNormalizationLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(NormalizationDataset, framework::dataset::make("DataType", DataType::F32)))
+FIXTURE_DATA_TEST_CASE(RunLarge, CLNormalizationLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(NormalizationDatasetFP32, framework::dataset::make("DataType", DataType::F32)))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32);
diff --git a/tests/validation/GLES_COMPUTE/NormalizationLayer.cpp b/tests/validation/GLES_COMPUTE/NormalizationLayer.cpp
index 4f6ae55..4bd931e 100644
--- a/tests/validation/GLES_COMPUTE/NormalizationLayer.cpp
+++ b/tests/validation/GLES_COMPUTE/NormalizationLayer.cpp
@@ -47,9 +47,10 @@
constexpr AbsoluteTolerance<float> tolerance_f32(0.00001f);
/** Input data set. */
-const auto NormalizationDataset = combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("NormType", { NormType::IN_MAP_1D, NormType::CROSS_MAP })),
- framework::dataset::make("NormalizationSize", 3, 9, 2)),
- framework::dataset::make("Beta", { 0.5f, 1.f, 2.f }));
+const auto NormalizationDataset = combine(combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("NormType", { NormType::IN_MAP_1D, NormType::CROSS_MAP })),
+ framework::dataset::make("NormalizationSize", 3, 9, 2)),
+ framework::dataset::make("Beta", { 0.5f, 1.f, 2.f })),
+ framework::dataset::make("IsScaled", { true, false }));
} // namespace
TEST_SUITE(GC)
@@ -75,9 +76,6 @@
TEST_SUITE_END()
TEST_SUITE_END()
-template <typename T>
-using GCNormalizationLayerFixedPointFixture = NormalizationValidationFixedPointFixture<GCTensor, GCAccessor, GCNormalizationLayer, T>;
-
TEST_SUITE_END()
TEST_SUITE_END()
} // namespace validation
diff --git a/tests/validation/NEON/NormalizationLayer.cpp b/tests/validation/NEON/NormalizationLayer.cpp
index e22922c..3afa52c 100644
--- a/tests/validation/NEON/NormalizationLayer.cpp
+++ b/tests/validation/NEON/NormalizationLayer.cpp
@@ -53,8 +53,12 @@
constexpr AbsoluteTolerance<int16_t> tolerance_qs16(4);
/** Input data set. */
-const auto NormalizationDataset = combine(combine(combine(datasets::SmallShapes(), datasets::NormalizationTypes()), framework::dataset::make("NormalizationSize", 3, 9, 2)),
- framework::dataset::make("Beta", { 0.5f, 1.f, 2.f }));
+const auto NormalizationDataset = combine(combine(combine(combine(datasets::SmallShapes(), datasets::NormalizationTypes()), framework::dataset::make("NormalizationSize", 3, 9, 2)),
+ framework::dataset::make("Beta", { 0.5f, 1.f, 2.f })),
+ framework::dataset::make("IsScaled", { true }));
+const auto NormalizationDatasetFP32 = combine(combine(combine(combine(datasets::SmallShapes(), datasets::NormalizationTypes()), framework::dataset::make("NormalizationSize", 3, 9, 2)),
+ framework::dataset::make("Beta", { 0.5f, 1.f, 2.f })),
+ framework::dataset::make("IsScaled", { true, false }));
} // namespace
TEST_SUITE(NEON)
@@ -82,12 +86,12 @@
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(RunSmall, NENormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(NormalizationDataset, framework::dataset::make("DataType", DataType::F32)))
+FIXTURE_DATA_TEST_CASE(RunSmall, NENormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(NormalizationDatasetFP32, framework::dataset::make("DataType", DataType::F32)))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f32);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, NENormalizationLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(NormalizationDataset, framework::dataset::make("DataType", DataType::F32)))
+FIXTURE_DATA_TEST_CASE(RunLarge, NENormalizationLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(NormalizationDatasetFP32, framework::dataset::make("DataType", DataType::F32)))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f32);
diff --git a/tests/validation/fixtures/NormalizationLayerFixture.h b/tests/validation/fixtures/NormalizationLayerFixture.h
index 696d14f..67881d0 100644
--- a/tests/validation/fixtures/NormalizationLayerFixture.h
+++ b/tests/validation/fixtures/NormalizationLayerFixture.h
@@ -47,10 +47,10 @@
{
public:
template <typename...>
- void setup(TensorShape shape, NormType norm_type, int norm_size, float beta, DataType data_type, int fractional_bits)
+ void setup(TensorShape shape, NormType norm_type, int norm_size, float beta, bool is_scaled, DataType data_type, int fractional_bits)
{
_fractional_bits = fractional_bits;
- NormalizationLayerInfo info(norm_type, norm_size, 5, beta);
+ NormalizationLayerInfo info(norm_type, norm_size, 5, beta, 1.f, is_scaled);
_target = compute_target(shape, info, data_type, fractional_bits);
_reference = compute_reference(shape, info, data_type, fractional_bits);
@@ -122,9 +122,9 @@
{
public:
template <typename...>
- void setup(TensorShape shape, NormType norm_type, int norm_size, float beta, DataType data_type)
+ void setup(TensorShape shape, NormType norm_type, int norm_size, float beta, bool is_scaled, DataType data_type)
{
- NormalizationValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, norm_type, norm_size, beta, data_type, 0);
+ NormalizationValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, norm_type, norm_size, beta, is_scaled, data_type, 0);
}
};
} // namespace validation