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//
// 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
auto layerName = GetLayerName(desc.m_Function, nodeIndex);
armnn::IConnectableLayer* layer = delegateData.m_Network->AddArgMinMaxLayer(desc, layerName.c_str());
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, nodeIndex) != kTfLiteOk)
{
return kTfLiteError;
}
// Connect
return Connect(layer, tfLiteNode, delegateData);
}
} // namespace armnnDelegate
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