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//
// Copyright © 2020,2022 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "DelegateUtils.hpp"
#include <algorithm>
#include <iterator>
#include <string>
#include <vector>
namespace armnnDelegate
{
TfLiteStatus VisitGatherOperator(DelegateData& delegateData,
TfLiteContext* tfLiteContext,
TfLiteNode* tfLiteNode,
int nodeIndex,
int32_t operatorCode)
{
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, operatorCode, nodeIndex))
{
return kTfLiteError;
}
const TfLiteTensor& tfLiteIndicesTensor = tfLiteTensors[tfLiteNode->inputs->data[1]];
if (!IsValid(tfLiteContext, tfLiteIndicesTensor, operatorCode, nodeIndex))
{
return kTfLiteError;
}
const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]];
if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex))
{
return kTfLiteError;
}
auto* gatherParameters = reinterpret_cast<TfLiteGatherParams*>(tfLiteNode->builtin_data);
auto axis = gatherParameters->axis;
const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor);
const armnn::TensorInfo& indicesTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteIndicesTensor);
const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true);
armnn::GatherDescriptor gatherDescriptor;
gatherDescriptor.m_Axis = axis;
auto inputDimensions = static_cast<int32_t>(inputTensorInfo.GetNumDimensions());
auto indicesDimensions = indicesTensorInfo.GetNumDimensions();
auto outputDimensions = outputTensorInfo.GetNumDimensions();
if (((axis < -inputDimensions) && (axis < 0)) || ((axis >= inputDimensions) && (axis > 0)))
{
TF_LITE_MAYBE_KERNEL_LOG( tfLiteContext,
"TfLiteArmnnDelegate: Operation has invalid axis: %d. It is out of bounds [-%d, %d))",
axis, inputDimensions, inputDimensions);
return kTfLiteError;
}
if (outputDimensions != static_cast<unsigned int>(inputDimensions) + indicesDimensions - 1)
{
TF_LITE_MAYBE_KERNEL_LOG( tfLiteContext,
"Operation has invalid output dimensions: %d. Output must be an (%d + %d - 1)-D tensor",
outputDimensions, inputDimensions, indicesDimensions);
return kTfLiteError;
}
armnn::BackendId setBackend;
if (!delegateData.m_Network)
{
// Check if supported
bool isSupported = false;
FORWARD_LAYER_SUPPORT_FUNC("GATHER",
tfLiteContext,
IsGatherSupported,
delegateData.m_Backends,
isSupported,
setBackend,
inputTensorInfo,
indicesTensorInfo,
outputTensorInfo,
gatherDescriptor);
return isSupported ? kTfLiteOk : kTfLiteError;
}
armnn::IConnectableLayer* layer = delegateData.m_Network->AddGatherLayer(gatherDescriptor);
layer->SetBackendId(setBackend);
ARMNN_ASSERT(layer != nullptr);
layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
auto inputsTensorsProcess = ProcessInputs(layer,
delegateData,
tfLiteContext,
tfLiteNode);
if (inputsTensorsProcess == kTfLiteError)
{
return inputsTensorsProcess;
}
Connect(layer, tfLiteNode, delegateData);
return kTfLiteOk;
}
} // namespace armnnDelegate
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