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//
// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#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/minimal_logging.h>
#include <tensorflow/lite/kernels/internal/tensor_ctypes.h>
#include <tensorflow/lite/schema/schema_generated.h>
#include <armnn_delegate.hpp>
namespace armnnDelegate
{
TfLiteStatus ValidateBroadcastToOperator(DelegateData& delegateData,
TfLiteContext* tfLiteContext,
const armnn::TensorInfo& inputInfo,
const armnn::TensorInfo& outputInfo,
const armnn::BroadcastToDescriptor& descriptor)
{
bool isSupported = false;
FORWARD_LAYER_SUPPORT_FUNC("BROADCAST_TO",
tfLiteContext,
IsBroadcastToSupported,
delegateData.m_Backends,
isSupported,
armnn::BackendId(),
inputInfo,
outputInfo,
descriptor);
return isSupported ? kTfLiteOk : kTfLiteError;
}
TfLiteStatus VisitBroadcastToOperator(DelegateData& delegateData,
TfLiteContext* tfLiteContext,
TfLiteNode* tfLiteNode,
int nodeIndex,
int32_t broadcastToOperatorCode)
{
TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex));
TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors;
// The input contains the data that should be broadcasted
const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]];
if (IsDynamicTensor(tfLiteInputTensor))
{
TF_LITE_MAYBE_KERNEL_LOG(
tfLiteContext,
"TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ",
broadcastToOperatorCode, nodeIndex);
return kTfLiteError;
}
// The shape tensor contains the new shape to be applied on the input
const TfLiteTensor& tfLiteShapeTensor = tfLiteTensors[tfLiteNode->inputs->data[1]];
if (IsDynamicTensor(tfLiteShapeTensor))
{
TF_LITE_MAYBE_KERNEL_LOG(
tfLiteContext,
"TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ",
broadcastToOperatorCode, nodeIndex);
return kTfLiteError;
}
// The output tensor
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: ",
broadcastToOperatorCode, nodeIndex);
return kTfLiteError;
}
const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor);
const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor);
auto* shapeData = tflite::GetTensorData<int32_t>(&tfLiteShapeTensor);
auto shapeTensorNum = tfLiteShapeTensor.dims->data[0];
armnn::BroadcastToDescriptor broadcastToDescriptor;
broadcastToDescriptor.m_BroadcastToShape = armnn::TensorShape(shapeTensorNum,
shapeData);
// No network pointer indicates that only support for this operator should be checked
if (!delegateData.m_Network)
{
return ValidateBroadcastToOperator(delegateData,
tfLiteContext,
inputTensorInfo,
outputTensorInfo,
broadcastToDescriptor);
}
auto layerName = GetLayerName(armnn::LayerType::BroadcastTo, nodeIndex);
armnn::IConnectableLayer* layer = delegateData.m_Network->AddBroadcastToLayer(broadcastToDescriptor,
layerName.c_str());
if (layer == nullptr)
{
return kTfLiteError;
}
layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
if (ProcessInputs(layer, delegateData, tfLiteContext, tfLiteNode, nodeIndex) != kTfLiteOk)
{
return kTfLiteError;
}
return Connect(layer, tfLiteNode, delegateData);
}
} // namespace armnnDelegate
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