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>

3 files changed, 27 insertions, 18 deletions

diff --git a/src/graph/nodes/BatchNormalizationLayer.cpp b/src/graph/nodes/BatchNormalizationLayer.cpp
index 7851aa5b9e..24287ac61a 100644
--- a/src/graph/nodes/BatchNormalizationLayer.cpp
+++ b/src/graph/nodes/BatchNormalizationLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -77,6 +77,7 @@ std::unique_ptr<arm_compute::IFunction> BatchNormalizationLayer::instantiate_nod
     node_ctx.add_input(_gamma.tensor());
     node_ctx.add_output(out);
     node_ctx.add_parameter<float>("epsilon", _epsilon);
+    node_ctx.add_parameter<ActivationLayerInfo>("act_info", _act_info);
 
     // Configure operation
     auto func = OperationRegistry::get().find_operation(OperationType::BatchNormalizationLayer, _target_hint)->configure(node_ctx);
diff --git a/src/graph/operations/CLSimpleOperations.cpp b/src/graph/operations/CLSimpleOperations.cpp
index 61315e73b2..94e3fe15f7 100644
--- a/src/graph/operations/CLSimpleOperations.cpp
+++ b/src/graph/operations/CLSimpleOperations.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -79,17 +79,18 @@ REGISTER_SIMPLE_OPERATION(CLBatchNormalizationLayerOperation, OPENCL, OperationT
     ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr);
 
     // Extract IO and info
-    auto      *in      = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
-    auto      *mean    = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(1));
-    auto      *var     = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(2));
-    auto      *beta    = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(3));
-    auto      *gamma   = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(4));
-    auto      *out     = dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0));
-    const auto epsilon = ctx.parameter<float>("epsilon");
+    auto      *in       = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
+    auto      *mean     = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(1));
+    auto      *var      = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(2));
+    auto      *beta     = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(3));
+    auto      *gamma    = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(4));
+    auto      *out      = dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0));
+    const auto epsilon  = ctx.parameter<float>("epsilon");
+    const auto act_info = ctx.parameter<ActivationLayerInfo>("act_info");
 
     // Create and configure function
     auto batch_norm = arm_compute::support::cpp14::make_unique<arm_compute::CLBatchNormalizationLayer>();
-    batch_norm->configure(in, out, mean, var, beta, gamma, epsilon);
+    batch_norm->configure(in, out, mean, var, beta, gamma, epsilon, act_info);
 
     // Log info
     ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating CLBatchNormalizationLayer"
@@ -101,6 +102,9 @@ REGISTER_SIMPLE_OPERATION(CLBatchNormalizationLayerOperation, OPENCL, OperationT
                                << " Beta shape: " << beta->info()->tensor_shape()
                                << " Gamma shape: " << gamma->info()->tensor_shape()
                                << " Epsilon: " << epsilon
+                               << " Activation function: " << act_info.activation()
+                               << " a: " << act_info.a()
+                               << " b: " << act_info.b()
                                << std::endl);
 
     return std::move(batch_norm);
diff --git a/src/graph/operations/NESimpleOperations.cpp b/src/graph/operations/NESimpleOperations.cpp
index 5a00e230ea..265bed6b7a 100644
--- a/src/graph/operations/NESimpleOperations.cpp
+++ b/src/graph/operations/NESimpleOperations.cpp
@@ -79,17 +79,18 @@ REGISTER_SIMPLE_OPERATION(NEBatchNormalizationLayerOperation, NEON, OperationTyp
     ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr);
 
     // Extract IO and info
-    auto      *in      = dynamic_cast<arm_compute::ITensor *>(ctx.input(0));
-    auto      *mean    = dynamic_cast<arm_compute::ITensor *>(ctx.input(1));
-    auto      *var     = dynamic_cast<arm_compute::ITensor *>(ctx.input(2));
-    auto      *beta    = dynamic_cast<arm_compute::ITensor *>(ctx.input(3));
-    auto      *gamma   = dynamic_cast<arm_compute::ITensor *>(ctx.input(4));
-    auto      *out     = dynamic_cast<arm_compute::ITensor *>(ctx.output(0));
-    const auto epsilon = ctx.parameter<float>("epsilon");
+    auto      *in       = dynamic_cast<arm_compute::ITensor *>(ctx.input(0));
+    auto      *mean     = dynamic_cast<arm_compute::ITensor *>(ctx.input(1));
+    auto      *var      = dynamic_cast<arm_compute::ITensor *>(ctx.input(2));
+    auto      *beta     = dynamic_cast<arm_compute::ITensor *>(ctx.input(3));
+    auto      *gamma    = dynamic_cast<arm_compute::ITensor *>(ctx.input(4));
+    auto      *out      = dynamic_cast<arm_compute::ITensor *>(ctx.output(0));
+    const auto epsilon  = ctx.parameter<float>("epsilon");
+    const auto act_info = ctx.parameter<ActivationLayerInfo>("act_info");
 
     // Create and configure function
     auto batch_norm = arm_compute::support::cpp14::make_unique<arm_compute::NEBatchNormalizationLayer>();
-    batch_norm->configure(in, out, mean, var, beta, gamma, epsilon);
+    batch_norm->configure(in, out, mean, var, beta, gamma, epsilon, act_info);
 
     // Log info
     ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NEBatchNormalizationLayer"
@@ -101,6 +102,9 @@ REGISTER_SIMPLE_OPERATION(NEBatchNormalizationLayerOperation, NEON, OperationTyp
                                << " Beta shape: " << beta->info()->tensor_shape()
                                << " Gamma shape: " << gamma->info()->tensor_shape()
                                << " Epsilon: " << epsilon
+                               << " Activation function: " << act_info.activation()
+                               << " a: " << act_info.a()
+                               << " b: " << act_info.b()
                                << std::endl);
 
     return std::move(batch_norm);