1 files changed, 112 insertions, 8 deletions
diff --git a/delegate/src/ArgMinMax.hpp b/delegate/src/ArgMinMax.hpp
index 367ef2ed14..090d18ef65 100644
--- a/delegate/src/ArgMinMax.hpp
+++ b/delegate/src/ArgMinMax.hpp
@@ -5,11 +5,10 @@
 
 #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>
+#include <tensorflow/lite/kernels/internal/tensor_ctypes.h>
 #include <tensorflow/lite/minimal_logging.h>
 
 namespace armnnDelegate
@@ -21,13 +20,118 @@ TfLiteStatus VisitArgMinMaxOperator(DelegateData& delegateData,
                                     int nodeIndex,
                                     int32_t argMinMaxOperatorCode)
 {
-    armnn::IgnoreUnused(delegateData,
-                        tfLiteContext,
-                        tfLiteNode,
-                        nodeIndex,
-                        argMinMaxOperatorCode);
+    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& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]];
+    if (!IsValid(tfLiteContext, tfLiteInputTensor, argMinMaxOperatorCode, nodeIndex))
+    {
+        return kTfLiteError;
+    }
+
+    const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]];
+    if (!IsValid(tfLiteContext, tfLiteOutputTensor, argMinMaxOperatorCode, nodeIndex))
+    {
+        return kTfLiteError;
+    }
+
+    const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor);
+    const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor);
+
+    // Get const axis value from model and set it to descriptor.
+    const TfLiteTensor& tfLiteAxisTensor = tfLiteTensors[tfLiteNode->inputs->data[1]];
+    if (!IsValid(tfLiteContext, tfLiteAxisTensor, argMinMaxOperatorCode, nodeIndex))
+    {
+        return kTfLiteError;
+    }
+
+    armnn::ArgMinMaxDescriptor desc;
+    // Get the axis value from the input tensor
+    switch (tfLiteAxisTensor.type)
+    {
+        case kTfLiteInt32:
+        case kTfLiteInt64:
+            desc.m_Axis = tflite::GetTensorData<int>(&tfLiteAxisTensor)[0];
+            break;
+        default:
+            TF_LITE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnDelegate: Axis value data type is not supported in operator #%d node #%d: ",
+                argMinMaxOperatorCode, nodeIndex);
+            return kTfLiteError;
+    }
+
+    // If output_type is int32 then set Signed32 else Signed64. Default type is Signed64.
+    if (argMinMaxOperatorCode == kTfLiteBuiltinArgMax)
+    {
+        desc.m_Function = armnn::ArgMinMaxFunction::Max;
+        auto* argMaxParameters = reinterpret_cast<TfLiteArgMaxParams*>(tfLiteNode->builtin_data);
+        switch (argMaxParameters->output_type)
+        {
+            case kTfLiteInt32:
+                desc.m_Output_Type = armnn::DataType::Signed32;
+                break;
+            case kTfLiteInt64:
+                desc.m_Output_Type = armnn::DataType::Signed64;
+                break;
+            default:
+                TF_LITE_MAYBE_KERNEL_LOG(
+                    tfLiteContext,
+                    "TfLiteArmnnDelegate: output_type data type is not supported in operator #%d node #%d: ",
+                    argMinMaxOperatorCode, nodeIndex);
+                return kTfLiteError;
+        }
+    }
+    else
+    {
+        desc.m_Function = armnn::ArgMinMaxFunction::Min;
+        auto* argMinParameters = reinterpret_cast<TfLiteArgMinParams*>(tfLiteNode->builtin_data);
+        switch (argMinParameters->output_type)
+        {
+            case kTfLiteInt32:
+                desc.m_Output_Type = armnn::DataType::Signed32;
+                break;
+            case kTfLiteInt64:
+                desc.m_Output_Type = armnn::DataType::Signed64;
+                break;
+            default:
+                TF_LITE_MAYBE_KERNEL_LOG(
+                    tfLiteContext,
+                    "TfLiteArmnnDelegate: output_type data type is not supported in operator #%d node #%d: ",
+                    argMinMaxOperatorCode, nodeIndex);
+                return kTfLiteError;
+        }
+    }
+
+    bool isSupported = false;
+    auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported)
+    {
+        FORWARD_LAYER_SUPPORT_FUNC(__func__,
+                                   tfLiteContext,
+                                   IsArgMinMaxSupported,
+                                   delegateData.m_Backends,
+                                   isSupported,
+                                   inputTensorInfo,
+                                   outInfo,
+                                   desc);
+    };
+
+    if (!delegateData.m_Network)
+    {
+        validateFunc(outputTensorInfo, isSupported);
+        return isSupported ? kTfLiteOk : kTfLiteError;
+    }
+
+    // Add an ArgMinMax layer
+    armnn::IConnectableLayer* layer = delegateData.m_Network->AddArgMinMaxLayer(desc);
+    ARMNN_ASSERT(layer != nullptr);
+
+    armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0);
+    outputSlot.SetTensorInfo(outputTensorInfo);
 
-    return kTfLiteError;
+    // Connect
+    return Connect(layer, tfLiteNode, delegateData);
 }
 
 } // namespace armnnDelegate