COMPMID-897 Merge batch normalization with bounded relu

Change-Id: I9a607fe620f795cdea1a99fdd3f5f8c2fc76f980
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/119234
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

11 files changed, 257 insertions, 56 deletions

diff --git a/tests/benchmark/CL/BatchNormalizationLayer.cpp b/tests/benchmark/CL/BatchNormalizationLayer.cpp
index 0fc8727241..a61e7cc745 100644
--- a/tests/benchmark/CL/BatchNormalizationLayer.cpp
+++ b/tests/benchmark/CL/BatchNormalizationLayer.cpp
@@ -29,6 +29,7 @@
 #include "tests/CL/CLAccessor.h"
 #include "tests/benchmark/fixtures/BatchNormalizationLayerFixture.h"
 #include "tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4BatchNormalizationLayerDataset.h"
+#include "tests/datasets/system_tests/mobilenet/MobileNetBatchNormalizationLayerDataset.h"
 #include "tests/datasets/system_tests/yolo/v2/YOLOV2BatchNormalizationLayerDataset.h"
 #include "tests/framework/Macros.h"
 #include "tests/framework/datasets/Datasets.h"
@@ -47,24 +48,41 @@ using CLBatchNormalizationLayerFixture = BatchNormalizationLayerFixture<CLTensor
 
 TEST_SUITE(CL)
 
+REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetBatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))),
+                                                                                        data_types),
+                                                            framework::dataset::make("Batches", 1)));
+
 REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
-                                framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
                                                                                         data_types),
                                                             framework::dataset::make("Batches", 1)));
 
 REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
-                                framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
                                                                                         data_types),
                                                             framework::dataset::make("Batches", 1)));
 
 TEST_SUITE(NIGHTLY)
+
+REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetBatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))),
+                                                                                        data_types),
+                                                            framework::dataset::make("Batches", { 4, 8 })));
+
 REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
-                                framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
                                                                                         data_types),
                                                             framework::dataset::make("Batches", { 4, 8 })));
 
 REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, CLBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
-                                framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
                                                                                         data_types),
                                                             framework::dataset::make("Batches", { 4, 8 })));
 TEST_SUITE_END()
diff --git a/tests/benchmark/GLES_COMPUTE/BatchNormalizationLayer.cpp b/tests/benchmark/GLES_COMPUTE/BatchNormalizationLayer.cpp
index 4464ea2401..e615860ec8 100755..100644
--- a/tests/benchmark/GLES_COMPUTE/BatchNormalizationLayer.cpp
+++ b/tests/benchmark/GLES_COMPUTE/BatchNormalizationLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -29,6 +29,7 @@
 #include "tests/GLES_COMPUTE/GCAccessor.h"
 #include "tests/benchmark/fixtures/BatchNormalizationLayerFixture.h"
 #include "tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4BatchNormalizationLayerDataset.h"
+#include "tests/datasets/system_tests/mobilenet/MobileNetBatchNormalizationLayerDataset.h"
 #include "tests/datasets/system_tests/yolo/v2/YOLOV2BatchNormalizationLayerDataset.h"
 #include "tests/framework/Macros.h"
 #include "tests/framework/datasets/Datasets.h"
@@ -47,24 +48,41 @@ using GCBatchNormalizationLayerFixture = BatchNormalizationLayerFixture<GCTensor
 
 TEST_SUITE(GC)
 
+REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, GCBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetBatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))),
+                                                                                        data_types),
+                                                            framework::dataset::make("Batches", 1)));
+
 REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, GCBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
-                                framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(), framework::dataset::make("ActivationInfo",
+                                                                                                                    ActivationLayerInfo())),
                                                                                         data_types),
                                                             framework::dataset::make("Batches", 1)));
 
 REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, GCBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
-                                framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
                                                                                         data_types),
                                                             framework::dataset::make("Batches", 1)));
 
 TEST_SUITE(NIGHTLY)
+
+REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, GCBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetBatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))),
+                                                                                        data_types),
+                                                            framework::dataset::make("Batches", { 4, 8 })));
+
 REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, GCBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
-                                framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(), framework::dataset::make("ActivationInfo",
+                                                                                                                    ActivationLayerInfo())),
                                                                                         data_types),
                                                             framework::dataset::make("Batches", { 4, 8 })));
 
 REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, GCBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
-                                framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
                                                                                         data_types),
                                                             framework::dataset::make("Batches", { 4, 8 })));
 TEST_SUITE_END()
diff --git a/tests/benchmark/NEON/BatchNormalizationLayer.cpp b/tests/benchmark/NEON/BatchNormalizationLayer.cpp
index 3a7f2c6b63..2aae3a480b 100644
--- a/tests/benchmark/NEON/BatchNormalizationLayer.cpp
+++ b/tests/benchmark/NEON/BatchNormalizationLayer.cpp
@@ -33,6 +33,7 @@
 
 #include "tests/benchmark/fixtures/BatchNormalizationLayerFixture.h"
 #include "tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4BatchNormalizationLayerDataset.h"
+#include "tests/datasets/system_tests/mobilenet/MobileNetBatchNormalizationLayerDataset.h"
 #include "tests/datasets/system_tests/yolo/v2/YOLOV2BatchNormalizationLayerDataset.h"
 
 namespace arm_compute
@@ -52,21 +53,39 @@ using NEBatchNormalizationLayerFixture = BatchNormalizationLayerFixture<Tensor,
 
 TEST_SUITE(NEON)
 
+REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetBatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))),
+                                                                                        data_types),
+                                                            framework::dataset::make("Batches", 1)));
 REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
-                                framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(), data_types),
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
+                                                                                        data_types),
                                                             framework::dataset::make("Batches", 1)));
 
 REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
-                                framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(), data_types),
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
+                                                                                        data_types),
                                                             framework::dataset::make("Batches", 1)));
 
 TEST_SUITE(NIGHTLY)
+REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetBatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))),
+                                                                                        data_types),
+                                                            framework::dataset::make("Batches", { 4, 8 })));
 REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
-                                framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(), data_types),
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
+                                                                                        data_types),
                                                             framework::dataset::make("Batches", { 4, 8 })));
 
 REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
-                                framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(), data_types),
+                                framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
+                                                                                                                    framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
+                                                                                        data_types),
                                                             framework::dataset::make("Batches", { 4, 8 })));
 TEST_SUITE_END()
 TEST_SUITE_END()
diff --git a/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h b/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h
index 38a3263203..a031ec6d96 100644
--- a/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h
+++ b/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h
@@ -40,7 +40,7 @@ class BatchNormalizationLayerFixture : public framework::Fixture
 {
 public:
     template <typename...>
-    void setup(TensorShape tensor_shape, TensorShape param_shape, float epsilon, DataType data_type, int batches)
+    void setup(TensorShape tensor_shape, TensorShape param_shape, float epsilon, ActivationLayerInfo act_info, DataType data_type, int batches)
     {
         // Set batched in source and destination shapes
         const unsigned int fixed_point_position = 4;
@@ -55,7 +55,7 @@ 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);
+        batch_norm_layer.configure(&src, &dst, &mean, &variance, &beta, &gamma, epsilon, act_info);
 
         // Allocate tensors
         src.allocator()->allocate();
diff --git a/tests/datasets/system_tests/mobilenet/MobileNetBatchNormalizationLayerDataset.h b/tests/datasets/system_tests/mobilenet/MobileNetBatchNormalizationLayerDataset.h
new file mode 100644
index 0000000000..d09ff02ef9
--- /dev/null
+++ b/tests/datasets/system_tests/mobilenet/MobileNetBatchNormalizationLayerDataset.h
@@ -0,0 +1,68 @@
+/*
+ * Copyright (c) 2017-2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef ARM_COMPUTE_TEST_MOBILENET_BATCHNORMALIZATION_LAYER_DATASET
+#define ARM_COMPUTE_TEST_MOBILENET_BATCHNORMALIZATION_LAYER_DATASET
+
+#include "tests/datasets/BatchNormalizationLayerDataset.h"
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace datasets
+{
+class MobileNetBatchNormalizationLayerDataset final : public BatchNormalizationLayerDataset
+{
+public:
+    MobileNetBatchNormalizationLayerDataset()
+    {
+        // conv1_bn, dwc0_bn
+        add_config(TensorShape(112U, 112U, 32U), TensorShape(32U), 0.001f);
+        // pwc0_bn
+        add_config(TensorShape(112U, 112U, 64U), TensorShape(64U), 0.001f);
+        // dwc1_bn
+        add_config(TensorShape(56U, 56U, 64U), TensorShape(64U), 0.001f);
+        // dwc2_bn, pwc1_bn, pwc2_bn
+        add_config(TensorShape(56U, 56U, 128U), TensorShape(128U), 0.001f);
+        // dwc3_bn
+        add_config(TensorShape(28U, 28U, 128U), TensorShape(128U), 0.001f);
+        // dwc4_bn, pwc3_bn, pwc4_bn
+        add_config(TensorShape(28U, 28U, 256U), TensorShape(256U), 0.001f);
+        // dwc5_bn
+        add_config(TensorShape(14U, 14U, 256U), TensorShape(256U), 0.001f);
+        // dwc6_bn, dwc7_bn, dwc8_bn, dwc9_bn, dwc10_bn, pwc5_bn, pwc6_bn, pwc7_bn, pwc8_bn, pwc9_bn, pwc10_bn
+        add_config(TensorShape(14U, 14U, 512U), TensorShape(512U), 0.001f);
+        // dwc11_bn
+        add_config(TensorShape(7U, 7U, 512U), TensorShape(512U), 0.001f);
+        // dwc12_bn, pwc11_bn, pwc12_bn
+        add_config(TensorShape(7U, 7U, 1024U), TensorShape(1024U), 0.001f);
+    }
+};
+} // namespace datasets
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_MOBILENET_BATCHNORMALIZATION_LAYER_DATASET */
diff --git a/tests/validation/CL/BatchNormalizationLayer.cpp b/tests/validation/CL/BatchNormalizationLayer.cpp
index 30dd70a66a..ef535153f2 100644
--- a/tests/validation/CL/BatchNormalizationLayer.cpp
+++ b/tests/validation/CL/BatchNormalizationLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -47,6 +47,12 @@ constexpr AbsoluteTolerance<float> tolerance_f32(0.00001f); /**< Tolerance value
 constexpr AbsoluteTolerance<float> tolerance_f16(0.01f);    /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
 constexpr AbsoluteTolerance<float> tolerance_qs8(3.0f);     /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS8 */
 constexpr AbsoluteTolerance<float> tolerance_qs16(6.0f);    /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS16 */
+const auto                         act_infos = framework::dataset::make("ActivationInfo",
+{
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
+});
 } // namespace
 
 TEST_SUITE(CL)
@@ -80,13 +86,16 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::Ran
 
 // *INDENT-OFF*
 // clang-format off
-DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
                framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),    // Window shrink
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Mismatching data types
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Mismatching data types
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Invalid mean/var/beta/gamma shape
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), // Mismatching fixed point position
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), // Fused activation with fixed point not supported
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Unsupported fused activation
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Fused activation's a < b
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
                                                      }),
@@ -96,6 +105,9 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3),
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
                                                        TensorInfo(),
                                                      })),
@@ -106,16 +118,31 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
                                                      TensorInfo(TensorShape(5U), 1, DataType::F32),
                                                      TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
                                                      TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
+                                                     TensorInfo(TensorShape(2U), 1, DataType::F32),
+                                                     TensorInfo(TensorShape(2U), 1, DataType::F32),
                                                      TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
+                                                     TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
+                                                   })),
+                framework::dataset::make("ActivationLayerInfo",{ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+                                                    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f, 2.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f, 2.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 2.f, 6.f),
+                                                     ActivationLayerInfo(),
+                                                     ActivationLayerInfo(),
                                                    })),
-               framework::dataset::make("Expected", { true, false, false, false, false, false, true, true})),
-               input_info, output_info, mvbg_info, expected)
+               framework::dataset::make("Expected", { true, false, false, false, false, false, false, false, false, true, true})),
+               input_info, output_info, mvbg_info, act_info, expected)
 {
     const auto &mean_info = mvbg_info;
     const auto &var_info = mvbg_info;
     const auto &beta_info = mvbg_info;
     const auto &gamma_info = mvbg_info;
-    bool has_error = bool(CLBatchNormalizationLayer::validate(&input_info.clone()->set_is_resizable(false), (output_info.total_size() == 0) ? nullptr : &output_info.clone()->set_is_resizable(false), &mean_info.clone()->set_is_resizable(false), &var_info.clone()->set_is_resizable(false), &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f));
+    bool has_error = bool(CLBatchNormalizationLayer::validate(&input_info.clone()->set_is_resizable(false), (output_info.total_size() == 0) ? nullptr : &output_info.clone()->set_is_resizable(false), &mean_info.clone()->set_is_resizable(false), &var_info.clone()->set_is_resizable(false), &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f, act_info));
     ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS);
 }
 // clang-format on
@@ -123,7 +150,8 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
 
 TEST_SUITE(Float)
 TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                                                                                   act_infos),
                                                                                                                    framework::dataset::make("DataType", DataType::F32)))
 {
     // Validate output
@@ -132,7 +160,8 @@ FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<float>, framewor
 TEST_SUITE_END()
 
 TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                                                                                  framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))),
                                                                                                                   framework::dataset::make("DataType", DataType::F16)))
 {
     // Validate output
@@ -146,7 +175,8 @@ template <typename T>
 using CLBatchNormalizationLayerFixedPointFixture = BatchNormalizationLayerValidationFixedPointFixture<CLTensor, CLAccessor, CLBatchNormalizationLayer, T>;
 
 TEST_SUITE(QS8)
-FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture<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)))
 {
@@ -156,7 +186,8 @@ FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture<int8_t
 TEST_SUITE_END()
 
 TEST_SUITE(QS16)
-FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture<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)))
 {
diff --git a/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp b/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp
index a82149bdcc..d817fc0e67 100644
--- a/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp
+++ b/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -45,6 +45,12 @@ namespace
 {
 constexpr AbsoluteTolerance<float> tolerance_f(0.00001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
 constexpr AbsoluteTolerance<float> tolerance_f16(0.01f);  /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
+const auto                         act_infos = framework::dataset::make("ActivationInfo",
+{
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
+});
 } // namespace
 
 TEST_SUITE(GC)
@@ -78,7 +84,8 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::Ran
 
 TEST_SUITE(Float)
 TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(Random, GCBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, GCBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                                                                                  act_infos),
                                                                                                                   framework::dataset::make("DataType", DataType::F16)))
 {
     // Validate output
@@ -87,7 +94,8 @@ FIXTURE_DATA_TEST_CASE(Random, GCBatchNormalizationLayerFixture<half>, framework
 TEST_SUITE_END()
 
 TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(Random, GCBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, GCBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                                                                                   act_infos),
                                                                                                                    framework::dataset::make("DataType", DataType::F32)))
 {
     // Validate output
diff --git a/tests/validation/NEON/BatchNormalizationLayer.cpp b/tests/validation/NEON/BatchNormalizationLayer.cpp
index dfa32bbb07..3501c359db 100644
--- a/tests/validation/NEON/BatchNormalizationLayer.cpp
+++ b/tests/validation/NEON/BatchNormalizationLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -49,6 +49,12 @@ constexpr AbsoluteTolerance<float> tolerance_f16(0.01f); /**< Tolerance value fo
 #endif                                                   /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
 constexpr AbsoluteTolerance<float> tolerance_qs8(3.0f);  /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS8 */
 constexpr AbsoluteTolerance<float> tolerance_qs16(6.0f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS16 */
+const auto                         act_infos = framework::dataset::make("ActivationInfo",
+{
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
+});
 } // namespace
 
 TEST_SUITE(NEON)
@@ -82,13 +88,15 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::Ran
 
 // *INDENT-OFF*
 // clang-format off
-DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
                framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),    // Window shrink
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Mismatching data types
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Mismatching data types
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Invalid mean/var/beta/gamma shape
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), // Mismatching fixed point position
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), // Fused activation with fixed point not supported
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Fused activation's a < b
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
                                                      }),
@@ -98,6 +106,8 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3),
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
                                                        TensorInfo(),
                                                      })),
@@ -108,10 +118,23 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
                                                      TensorInfo(TensorShape(5U), 1, DataType::F32),
                                                      TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
                                                      TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
+                                                     TensorInfo(TensorShape(2U), 1, DataType::F32),
+                                                     TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
                                                      TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
                                                    })),
-               framework::dataset::make("Expected", { true, false, false, false, false, false, true, true})),
-               input_info, output_info, mvbg_info, expected)
+               framework::dataset::make("ActivationLayerInfo",{ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+                                                    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f, 2.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f, 2.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 2.f, 6.f),
+                                                     ActivationLayerInfo(),
+                                                     ActivationLayerInfo(),
+                                                   })),
+               framework::dataset::make("Expected", { true, false, false, false, false, false, false, false, true, true})),
+               input_info, output_info, mvbg_info, act_info, expected)
 {
     const auto &mean_info = mvbg_info;
     const auto &var_info = mvbg_info;
@@ -120,14 +143,15 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
     bool has_error = bool(NEBatchNormalizationLayer::validate(
             &input_info.clone()->set_is_resizable(false), output_info.total_size() ? &output_info.clone()->set_is_resizable(false) : nullptr,
             &mean_info.clone()->set_is_resizable(false), &var_info.clone()->set_is_resizable(false),
-            &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f));
+            &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f, act_info));
     ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS);
 }
 // clang-format on
 // *INDENT-ON*
 
 TEST_SUITE(Float)
-FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                                                                                   act_infos),
                                                                                                                    framework::dataset::make("DataType", DataType::F32)))
 {
     // Validate output
@@ -137,7 +161,8 @@ TEST_SUITE_END()
 
 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
 TEST_SUITE(Float16)
-FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                                                                                  act_infos),
                                                                                                                   framework::dataset::make("DataType", DataType::F16)))
 {
     // Validate output
@@ -151,7 +176,8 @@ 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(datasets::RandomBatchNormalizationLayerDataset(),
+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)))
 {
@@ -161,7 +187,8 @@ 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(datasets::RandomBatchNormalizationLayerDataset(),
+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)))
 {
diff --git a/tests/validation/fixtures/BatchNormalizationLayerFixture.h b/tests/validation/fixtures/BatchNormalizationLayerFixture.h
index 298c9ca411..e02c619249 100644
--- a/tests/validation/fixtures/BatchNormalizationLayerFixture.h
+++ b/tests/validation/fixtures/BatchNormalizationLayerFixture.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -45,12 +45,12 @@ class BatchNormalizationLayerValidationFixedPointFixture : public framework::Fix
 {
 public:
     template <typename...>
-    void setup(TensorShape shape0, TensorShape shape1, float epsilon, DataType dt, int fractional_bits)
+    void setup(TensorShape shape0, TensorShape shape1, float epsilon, ActivationLayerInfo act_info, DataType dt, int fractional_bits)
     {
         _fractional_bits = fractional_bits;
         _data_type       = dt;
-        _target          = compute_target(shape0, shape1, epsilon, dt, fractional_bits);
-        _reference       = compute_reference(shape0, shape1, epsilon, dt, fractional_bits);
+        _target          = compute_target(shape0, shape1, epsilon, act_info, dt, fractional_bits);
+        _reference       = compute_reference(shape0, shape1, epsilon, act_info, dt, fractional_bits);
     }
 
 protected:
@@ -85,7 +85,7 @@ protected:
         }
     }
 
-    TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, float epsilon, DataType dt, int fixed_point_position)
+    TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, float epsilon, ActivationLayerInfo act_info, DataType dt, int fixed_point_position)
     {
         // Create tensors
         TensorType src   = create_tensor<TensorType>(shape0, dt, 1, fixed_point_position);
@@ -97,7 +97,7 @@ protected:
 
         // Create and configure function
         FunctionType norm;
-        norm.configure(&src, &dst, &mean, &var, &beta, &gamma, epsilon);
+        norm.configure(&src, &dst, &mean, &var, &beta, &gamma, epsilon, act_info);
 
         ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
         ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -130,7 +130,7 @@ protected:
         return dst;
     }
 
-    SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, float epsilon, DataType dt, int fixed_point_position)
+    SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, float epsilon, ActivationLayerInfo act_info, DataType dt, int fixed_point_position)
     {
         // Create reference
         SimpleTensor<T> ref_src{ shape0, dt, 1, fixed_point_position };
@@ -142,7 +142,7 @@ protected:
         // Fill reference
         fill(ref_src, ref_mean, ref_var, ref_beta, ref_gamma);
 
-        return reference::batch_normalization_layer(ref_src, ref_mean, ref_var, ref_beta, ref_gamma, epsilon, fixed_point_position);
+        return reference::batch_normalization_layer(ref_src, ref_mean, ref_var, ref_beta, ref_gamma, epsilon, act_info, fixed_point_position);
     }
 
     TensorType      _target{};
@@ -156,9 +156,9 @@ class BatchNormalizationLayerValidationFixture : public BatchNormalizationLayerV
 {
 public:
     template <typename...>
-    void setup(TensorShape shape0, TensorShape shape1, float epsilon, DataType dt)
+    void setup(TensorShape shape0, TensorShape shape1, float epsilon, ActivationLayerInfo act_info, DataType dt)
     {
-        BatchNormalizationLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, epsilon, dt, 0);
+        BatchNormalizationLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, epsilon, act_info, dt, 0);
     }
 };
 } // namespace validation
diff --git a/tests/validation/reference/BatchNormalizationLayer.cpp b/tests/validation/reference/BatchNormalizationLayer.cpp
index e4446d1694..a9d9f0320d 100644
--- a/tests/validation/reference/BatchNormalizationLayer.cpp
+++ b/tests/validation/reference/BatchNormalizationLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -23,6 +23,8 @@
  */
 #include "BatchNormalizationLayer.h"
 
+#include "ActivationLayer.h"
+
 #include "tests/validation/FixedPoint.h"
 #include "tests/validation/Helpers.h"
 
@@ -37,8 +39,9 @@ namespace reference
 // Batch Normalization Layer for fixed point type
 template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type *>
 SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
-                                          int fixed_point_position)
+                                          ActivationLayerInfo act_info, int fixed_point_position)
 {
+    ARM_COMPUTE_UNUSED(act_info);
     SimpleTensor<T> result(src.shape(), src.data_type());
 
     const auto cols       = static_cast<int>(src.shape()[0]);
@@ -79,7 +82,7 @@ SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const Simp
 // Batch Normalization Layer for floating point type
 template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type *>
 SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
-                                          int fixed_point_position)
+                                          ActivationLayerInfo act_info, int fixed_point_position)
 {
     ARM_COMPUTE_UNUSED(fixed_point_position);
 
@@ -103,21 +106,28 @@ SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const Simp
                     const float numerator   = src[pos] - mean[i];
                     const float x_bar       = numerator / denominator;
                     result[pos]             = beta[i] + x_bar * gamma[i];
+                    ;
                 }
             }
         }
     }
+
+    if(act_info.enabled())
+    {
+        result = activation_layer(result, act_info);
+    }
+
     return result;
 }
 template SimpleTensor<float> batch_normalization_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &mean, const SimpleTensor<float> &var, const SimpleTensor<float> &beta,
-                                                       const SimpleTensor<float> &gamma, float epsilon, int fixed_point_position);
+                                                       const SimpleTensor<float> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
 template SimpleTensor<int8_t> batch_normalization_layer(const SimpleTensor<int8_t> &src, const SimpleTensor<int8_t> &mean, const SimpleTensor<int8_t> &var, const SimpleTensor<int8_t> &beta,
-                                                        const SimpleTensor<int8_t> &gamma, float epsilon, int fixed_point_position);
+                                                        const SimpleTensor<int8_t> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
 template SimpleTensor<int16_t> batch_normalization_layer(const SimpleTensor<int16_t> &src, const SimpleTensor<int16_t> &mean, const SimpleTensor<int16_t> &var, const SimpleTensor<int16_t> &beta,
-                                                         const SimpleTensor<int16_t> &gamma, float epsilon, int fixed_point_position);
+                                                         const SimpleTensor<int16_t> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
 template SimpleTensor<half> batch_normalization_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &mean, const SimpleTensor<half> &var,
                                                       const SimpleTensor<half> &beta,
-                                                      const SimpleTensor<half> &gamma, float epsilon, int fixed_point_position);
+                                                      const SimpleTensor<half> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
 
 } // namespace reference
 } // namespace validation
diff --git a/tests/validation/reference/BatchNormalizationLayer.h b/tests/validation/reference/BatchNormalizationLayer.h
index 1a554adf7e..329909dab4 100644
--- a/tests/validation/reference/BatchNormalizationLayer.h
+++ b/tests/validation/reference/BatchNormalizationLayer.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -37,11 +37,13 @@ namespace reference
 {
 template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type * = nullptr>
 SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
-                                          int fixed_point_position);
+                                          ActivationLayerInfo act_info,
+                                          int                 fixed_point_position);
 
 template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type * = nullptr>
 SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
-                                          int fixed_point_position);
+                                          ActivationLayerInfo act_info,
+                                          int                 fixed_point_position);
 } // namespace reference
 } // namespace validation
 } // namespace test