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| author | Georgios Pinitas <georgios.pinitas@arm.com> | 2017-11-16 14:37:08 +0000 |
|---|---|---|
| committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:35:24 +0000 |
| commit | 41caa625231c24533a514606bbf2683f7d4964ad (patch) | |
| tree | 4e897dfbcc77d57c996f15bab014b20e4cb4868d /tests/validation/NEON/NormalizationLayer.cpp | |
| parent | 181e65145d153210ec5587a42d2938e27e1d5b01 (diff) | |
| download | ComputeLibrary-41caa625231c24533a514606bbf2683f7d4964ad.tar.gz | |
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>
Diffstat (limited to 'tests/validation/NEON/NormalizationLayer.cpp')
| -rw-r--r-- | tests/validation/NEON/NormalizationLayer.cpp | 12 |
1 files changed, 8 insertions, 4 deletions
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); |