COMPMID-987: Make beta and gamma optional in BatchNormalization

Currently we have beta and gamma compulsory in Batch normalization. There are
network that might not need one or both of those. Thus these should be optional
with beta(offset) defaulting to zero and gamma(scale) to 1. Will also reduce
some memory requirements.

Change-Id: I15bf1ec14b814be2acebf1be1a4fba9c4fbd3190
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/123237
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

1 files changed, 27 insertions, 13 deletions

diff --git a/tests/validation/NEON/BatchNormalizationLayer.cpp b/tests/validation/NEON/BatchNormalizationLayer.cpp
index 054ed278a2..7bf1f2633e 100644
--- a/tests/validation/NEON/BatchNormalizationLayer.cpp
+++ b/tests/validation/NEON/BatchNormalizationLayer.cpp
@@ -63,8 +63,10 @@ TEST_SUITE(BatchNormalizationLayer)
 template <typename T>
 using NEBatchNormalizationLayerFixture = BatchNormalizationLayerValidationFixture<Tensor, Accessor, NEBatchNormalizationLayer, T>;
 
-DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::RandomBatchNormalizationLayerDataset(), framework::dataset::make("DataType", { DataType::QS8, DataType::QS16, DataType::F32 })),
-               shape0, shape1, epsilon, dt)
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                                           combine(framework::dataset::make("UseBeta", { false, true }), framework::dataset::make("UseGamma", { false, true }))),
+                                                                   framework::dataset::make("DataType", { DataType::QS8, DataType::QS16, DataType::F32 })),
+               shape0, shape1, epsilon, use_beta, use_gamma, dt)
 {
     // Set fixed point position data type allowed
     const int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0;
@@ -79,7 +81,9 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::Ran
 
     // Create and Configure function
     NEBatchNormalizationLayer norm;
-    norm.configure(&src, &dst, &mean, &var, &beta, &gamma, epsilon);
+    Tensor                   *beta_ptr  = use_beta ? &beta : nullptr;
+    Tensor                   *gamma_ptr = use_gamma ? &gamma : nullptr;
+    norm.configure(&src, &dst, &mean, &var, beta_ptr, gamma_ptr, epsilon);
 
     // Validate valid region
     const ValidRegion valid_region = shape_to_valid_region(shape0);
@@ -150,7 +154,9 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
 // *INDENT-ON*
 
 TEST_SUITE(Float)
-FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                                                                                   combine(framework::dataset::make("UseBeta", { false, true }),
+                                                                                                                           framework::dataset::make("UseGamma", { false, true }))),
                                                                                                                    act_infos),
                                                                                                                    framework::dataset::make("DataType", DataType::F32)))
 {
@@ -161,7 +167,9 @@ TEST_SUITE_END()
 
 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
 TEST_SUITE(Float16)
-FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                                                                                  combine(framework::dataset::make("UseBeta", { false, true }),
+                                                                                                                          framework::dataset::make("UseGamma", { false, true }))),
                                                                                                                   framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
                                                                                                                   framework::dataset::make("DataType", DataType::F16)))
 {
@@ -176,10 +184,13 @@ template <typename T>
 using NEBatchNormalizationLayerFixedPointFixture = BatchNormalizationLayerValidationFixedPointFixture<Tensor, Accessor, NEBatchNormalizationLayer, T>;
 
 TEST_SUITE(QS8)
-FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
-                       framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
-                       framework::dataset::make("DataType", DataType::QS8)),
-                       framework::dataset::make("FractionalBits", 1, 6)))
+FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT,
+                       combine(combine(combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                               framework::dataset::make("UseBeta", false)),
+                                                       framework::dataset::make("UseGamma", false)),
+                                               framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
+                                       framework::dataset::make("DataType", DataType::QS8)),
+                               framework::dataset::make("FractionalBits", 1, 6)))
 {
     // Validate output
     validate(Accessor(_target), _reference, tolerance_qs8, 0);
@@ -187,10 +198,13 @@ FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture<int8_t
 TEST_SUITE_END()
 
 TEST_SUITE(QS16)
-FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
-                       framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
-                       framework::dataset::make("DataType", DataType::QS16)),
-                       framework::dataset::make("FractionalBits", 1, 14)))
+FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT,
+                       combine(combine(combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                               framework::dataset::make("UseBeta", false)),
+                                                       framework::dataset::make("UseGamma", false)),
+                                               framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
+                                       framework::dataset::make("DataType", DataType::QS16)),
+                               framework::dataset::make("FractionalBits", 1, 14)))
 {
     // Validate output
     validate(Accessor(_target), _reference, tolerance_qs16, 0);