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>

4 files changed, 26 insertions, 19 deletions

diff --git a/tests/validation/CL/NormalizationLayer.cpp b/tests/validation/CL/NormalizationLayer.cpp
index 4fca6bf297..18f0c37ab6 100644
--- a/tests/validation/CL/NormalizationLayer.cpp
+++ b/tests/validation/CL/NormalizationLayer.cpp
@@ -52,9 +52,14 @@ constexpr AbsoluteTolerance<int8_t>  tolerance_qs8(2);
 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 @@ FIXTURE_DATA_TEST_CASE(RunLarge, CLNormalizationLayerFixture<half>, framework::D
 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 4f6ae55677..4bd931e420 100644
--- a/tests/validation/GLES_COMPUTE/NormalizationLayer.cpp
+++ b/tests/validation/GLES_COMPUTE/NormalizationLayer.cpp
@@ -47,9 +47,10 @@ namespace
 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 @@ FIXTURE_DATA_TEST_CASE(RunLarge, GCNormalizationLayerFixture<float>, framework::
 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 e22922cf8a..3afa52cb4c 100644
--- a/tests/validation/NEON/NormalizationLayer.cpp
+++ b/tests/validation/NEON/NormalizationLayer.cpp
@@ -53,8 +53,12 @@ constexpr AbsoluteTolerance<int8_t>  tolerance_qs8(2);
 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 @@ TEST_SUITE_END()
 #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 696d14fbbb..67881d0347 100644
--- a/tests/validation/fixtures/NormalizationLayerFixture.h
+++ b/tests/validation/fixtures/NormalizationLayerFixture.h
@@ -47,10 +47,10 @@ class NormalizationValidationFixedPointFixture : public framework::Fixture
 {
 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 @@ class NormalizationValidationFixture : public NormalizationValidationFixedPointF
 {
 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