1 files changed, 132 insertions, 0 deletions
diff --git a/delegate/classic/src/ArgMinMax.hpp b/delegate/classic/src/ArgMinMax.hpp
new file mode 100644
index 0000000000..4e4a2a3f3a
--- /dev/null
+++ b/delegate/classic/src/ArgMinMax.hpp
@@ -0,0 +1,132 @@
+//
+// Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#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
+{
+
+TfLiteStatus VisitArgMinMaxOperator(DelegateData& delegateData,
+                                    TfLiteContext* tfLiteContext,
+                                    TfLiteNode* tfLiteNode,
+                                    int nodeIndex,
+                                    int32_t 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, true);
+
+    // 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);
+        if (argMaxParameters->output_type != kTfLiteInt32 && argMaxParameters->output_type != kTfLiteInt64)
+        {
+            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);
+        if (argMinParameters->output_type != kTfLiteInt32 && argMinParameters->output_type != kTfLiteInt64)
+        {
+            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;
+    armnn::BackendId setBackend;
+    auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported)
+    {
+        FORWARD_LAYER_SUPPORT_FUNC("ARGMINMAX",
+                                   tfLiteContext,
+                                   IsArgMinMaxSupported,
+                                   delegateData.m_Backends,
+                                   isSupported,
+                                   setBackend,
+                                   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);
+    layer->SetBackendId(setBackend);
+    ARMNN_ASSERT(layer != nullptr);
+
+    armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0);
+    outputSlot.SetTensorInfo(outputTensorInfo);
+
+    // try to connect the Constant Inputs if there are any
+    if(ProcessInputs(layer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk )
+    {
+        return kTfLiteError;
+    }
+
+    // Connect
+    return Connect(layer, tfLiteNode, delegateData);
+}
+
+} // namespace armnnDelegate