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, 4 insertions, 2 deletions

diff --git a/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h b/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h
index fbb7700710..c55bb2acc9 100644
--- a/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h
+++ b/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h
@@ -42,7 +42,7 @@ class BatchNormalizationLayerFixture : public framework::Fixture
 {
 public:
     template <typename...>
-    void setup(TensorShape tensor_shape, TensorShape param_shape, float epsilon, ActivationLayerInfo act_info, DataType data_type, int batches)
+    void setup(TensorShape tensor_shape, TensorShape param_shape, float epsilon, bool use_gamma, bool use_beta, ActivationLayerInfo act_info, DataType data_type, int batches)
     {
         // Set batched in source and destination shapes
         const unsigned int fixed_point_position = 4;
@@ -57,7 +57,9 @@ public:
         gamma    = create_tensor<TensorType>(param_shape, data_type, 1, fixed_point_position);
 
         // Create and configure function
-        batch_norm_layer.configure(&src, &dst, &mean, &variance, &beta, &gamma, epsilon, act_info);
+        TensorType *beta_ptr  = use_beta ? &beta : nullptr;
+        TensorType *gamma_ptr = use_gamma ? &gamma : nullptr;
+        batch_norm_layer.configure(&src, &dst, &mean, &variance, beta_ptr, gamma_ptr, epsilon, act_info);
 
         // Allocate tensors
         src.allocator()->allocate();