1 files changed, 124 insertions, 1 deletions
diff --git a/delegate/src/ElementwiseBinary.hpp b/delegate/src/ElementwiseBinary.hpp
index ff24012bdb..a22d9f5751 100644
--- a/delegate/src/ElementwiseBinary.hpp
+++ b/delegate/src/ElementwiseBinary.hpp
@@ -5,6 +5,8 @@
 
 #pragma once
 
+#include "DelegateUtils.hpp"
+
 #include <tensorflow/lite/builtin_ops.h>
 #include <tensorflow/lite/c/builtin_op_data.h>
 #include <tensorflow/lite/c/common.h>
@@ -13,13 +15,134 @@
 namespace armnnDelegate
 {
 
+TfLiteStatus ValidateAddOperator(DelegateData& delegateData,
+                                 TfLiteContext* tfLiteContext,
+                                 const armnn::TensorInfo& inputInfo1,
+                                 const armnn::TensorInfo& inputInfo2,
+                                 const armnn::TensorInfo& outputInfo)
+{
+    bool isSupported = false;
+    auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported)
+    {
+        FORWARD_LAYER_SUPPORT_FUNC(__func__,
+                                   tfLiteContext,
+                                   IsAdditionSupported,
+                                   delegateData.m_Backends,
+                                   isSupported,
+                                   inputInfo1,
+                                   inputInfo2,
+                                   outputTensorInfo);
+    };
+
+    validateFunc(outputInfo, isSupported);
+    return isSupported ? kTfLiteOk : kTfLiteError;
+}
+
+armnn::IConnectableLayer* AddAdditionLayer(DelegateData& delegateData)
+{
+
+    if (!delegateData.m_Network)
+    {
+        return nullptr;
+    }
+
+    return delegateData.m_Network->AddAdditionLayer();
+}
+
 TfLiteStatus VisitElementwiseBinaryOperator(DelegateData& delegateData,
                                             TfLiteContext* tfLiteContext,
                                             TfLiteNode* tfLiteNode,
                                             int nodeIndex,
                                             int32_t elementwiseBinaryOperatorCode)
 {
-    return kTfLiteError;
+    TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex));
+    TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+
+    const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors;
+    const TfLiteTensor& tfLiteInputTensor0 = tfLiteTensors[tfLiteNode->inputs->data[0]];
+    if (IsDynamicTensor(tfLiteInputTensor0))
+    {
+        TF_LITE_MAYBE_KERNEL_LOG(
+            tfLiteContext,
+            "TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ",
+            elementwiseBinaryOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    const TfLiteTensor& tfLiteInputTensor1 = tfLiteTensors[tfLiteNode->inputs->data[1]];
+    if (IsDynamicTensor(tfLiteInputTensor1))
+    {
+        TF_LITE_MAYBE_KERNEL_LOG(
+            tfLiteContext,
+            "TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ",
+            elementwiseBinaryOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]];
+    if (IsDynamicTensor(tfLiteOutputTensor))
+    {
+        TF_LITE_MAYBE_KERNEL_LOG(
+            tfLiteContext,
+            "TfLiteArmnnDelegate: Dynamic output tensors are not supported in operator #%d node #%d: ",
+            elementwiseBinaryOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    const armnn::TensorInfo& inputTensorInfo0 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor0);
+    const armnn::TensorInfo& inputTensorInfo1 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor1);
+    const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor);
+
+    if (!delegateData.m_Network)
+    {
+        switch(elementwiseBinaryOperatorCode)
+        {
+            case kTfLiteBuiltinAdd:
+                return ValidateAddOperator(delegateData,
+                                           tfLiteContext,
+                                           inputTensorInfo0,
+                                           inputTensorInfo1,
+                                           outputTensorInfo);
+            default:
+                return kTfLiteError;
+        }
+    }
+
+    armnn::IConnectableLayer* elementwiseBinaryLayer = nullptr;
+
+    switch(elementwiseBinaryOperatorCode)
+    {
+        case kTfLiteBuiltinAdd:
+            elementwiseBinaryLayer = AddAdditionLayer(delegateData);
+            break;
+        default:
+            return kTfLiteError;
+    }
+    ARMNN_ASSERT(elementwiseBinaryLayer != nullptr);
+
+    armnn::IOutputSlot& outputSlot = elementwiseBinaryLayer->GetOutputSlot(0);
+    outputSlot.SetTensorInfo(outputTensorInfo);
+
+    auto reshapeLayer = BroadcastTensor(inputTensorInfo0,
+                                        inputTensorInfo1,
+                                        elementwiseBinaryLayer,
+                                        tfLiteContext,
+                                        tfLiteNode,
+                                        delegateData);
+    if (!reshapeLayer)
+    {
+        return kTfLiteError;
+    }
+
+    auto* tfLiteNodeParameters = reinterpret_cast<TfLiteAddParams*>(tfLiteNode->builtin_data);
+    if (!tfLiteNodeParameters)
+    {
+        // No Activation
+        return kTfLiteOk;
+    }
+    // Check activation
+    TfLiteFusedActivation activationType = tfLiteNodeParameters->activation;
+    return FusedActivation(tfLiteContext, tfLiteNode, activationType, reshapeLayer, 0, delegateData);
 }
 
 } // namespace armnnDelegate