1 files changed, 113 insertions, 9 deletions
diff --git a/delegate/src/Pad.hpp b/delegate/src/Pad.hpp
index 2134232b61..6149819950 100644
--- a/delegate/src/Pad.hpp
+++ b/delegate/src/Pad.hpp
@@ -5,8 +5,6 @@
 
 #pragma once
 
-#include <armnn/utility/IgnoreUnused.hpp>
-
 #include <tensorflow/lite/builtin_ops.h>
 #include <tensorflow/lite/c/builtin_op_data.h>
 #include <tensorflow/lite/c/common.h>
@@ -19,15 +17,121 @@ TfLiteStatus VisitPadOperator(DelegateData& delegateData,
                               TfLiteContext* tfLiteContext,
                               TfLiteNode* tfLiteNode,
                               int nodeIndex,
-                              int32_t padOperatorCode)
+                              int32_t tfLitePadOperatorCode)
 {
-    armnn::IgnoreUnused(delegateData,
-                        tfLiteContext,
-                        tfLiteNode,
-                        nodeIndex,
-                        padOperatorCode);
+    TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+
+    switch(tfLitePadOperatorCode)
+    {
+        case kTfLiteBuiltinPad:
+            TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex));
+            break;
+        case kTfLiteBuiltinPadv2:
+            TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 3, nodeIndex));
+            break;
+        default:
+            return kTfLiteError;
+    }
+
+    const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors;
+    const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]];
+    const TfLiteTensor& tfLitepaddingTensor = tfLiteTensors[tfLiteNode->inputs->data[1]];
+
+    if (IsDynamicTensor(tfLiteInputTensor))
+    {
+        TF_LITE_MAYBE_KERNEL_LOG(
+            tfLiteContext,
+            "TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ",
+            tfLitePadOperatorCode, 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: ",
+            tfLitePadOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor);
+    const armnn::TensorInfo& paddingTensorInfo = GetTensorInfoForTfLiteTensor(tfLitepaddingTensor);
+    const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor);
+
+    // Get the padding data from the input tensor
+    auto* paddingData = tflite::GetTensorData<int32_t>(&tfLitepaddingTensor);
+
+    size_t step = 2;
+    armnn::PadDescriptor descriptor;
+    for (unsigned int i = 0; i < paddingTensorInfo.GetNumElements() / step; ++i)
+    {
+        descriptor.m_PadList.emplace_back(paddingData[i * step], paddingData[i * step + 1]);
+    }
+
+    if (tfLitePadOperatorCode == kTfLiteBuiltinPad && inputTensorInfo.IsQuantized())
+    {
+        descriptor.m_PadValue = inputTensorInfo.GetQuantizationOffset();
+    }
+    else if (tfLitePadOperatorCode == kTfLiteBuiltinPadv2)
+    {
+        const TfLiteTensor& tfLitepaddingValue = tfLiteTensors[tfLiteNode->inputs->data[2]];
+        armnn::TensorInfo paddingValueTensorInfo = GetTensorInfoForTfLiteTensor(tfLitepaddingValue);
+        if (paddingValueTensorInfo.GetNumElements() != 1)
+        {
+            TF_LITE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnDelegate: Multiple padding value are not supported in operator #%d node #%d: ",
+                tfLitePadOperatorCode, nodeIndex);
+            return kTfLiteError;
+        }
+        // Get the padding value from the input tensor
+        switch (tfLitepaddingValue.type)
+        {
+            case kTfLiteFloat32:
+                descriptor.m_PadValue = tflite::GetTensorData<float>(&tfLitepaddingValue)[0];
+                break;
+            case kTfLiteUInt8:
+                descriptor.m_PadValue = tflite::GetTensorData<uint8>(&tfLitepaddingValue)[0];
+                break;
+            case kTfLiteInt8:
+                descriptor.m_PadValue = tflite::GetTensorData<int8>(&tfLitepaddingValue)[0];
+                break;
+            case kTfLiteInt16:
+                descriptor.m_PadValue = tflite::GetTensorData<int16>(&tfLitepaddingValue)[0];
+                break;
+            default:
+                TF_LITE_MAYBE_KERNEL_LOG(
+                    tfLiteContext,
+                    "TfLiteArmnnDelegate: Padding value datatype is not supported in operator #%d node #%d: ",
+                    tfLitePadOperatorCode, nodeIndex);
+                return kTfLiteError;
+        }
+    }
+
+    if (!delegateData.m_Network)
+    {
+        bool isSupported = false;
+        FORWARD_LAYER_SUPPORT_FUNC(__func__,
+                                   tfLiteContext,
+                                   IsPadSupported,
+                                   delegateData.m_Backends,
+                                   isSupported,
+                                   inputTensorInfo,
+                                   outputTensorInfo,
+                                   descriptor);
+
+        return isSupported ? kTfLiteOk : kTfLiteError;
+    }
+
+    armnn::IConnectableLayer* padLayer = delegateData.m_Network->AddPadLayer(descriptor);
+    ARMNN_ASSERT(padLayer != nullptr);
+
+    armnn::IOutputSlot& outputSlot = padLayer->GetOutputSlot(0);
+    outputSlot.SetTensorInfo(outputTensorInfo);
 
-    return kTfLiteError;
+    return Connect(padLayer, tfLiteNode, delegateData);
 }
 
 } // namespace armnnDelegate