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//
// Copyright © 2021 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/minimal_logging.h>
namespace armnnDelegate
{
TfLiteStatus VisitPackOperator(DelegateData& delegateData,
TfLiteContext* tfLiteContext,
TfLiteNode* tfLiteNode,
int nodeIndex,
int32_t operatorCode)
{
unsigned int numInputs = tfLiteNode->inputs->size;
if (numInputs < 1)
{
TF_LITE_MAYBE_KERNEL_LOG(
tfLiteContext, "TfLiteArmnnDelegate: Must have at least one input in (%d != %d) in node #%d",
1, numInputs, nodeIndex);
return kTfLiteError;
}
TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors;
// Validate all inputs and get TensorInfo
std::vector<armnn::TensorInfo> inputTensorInfos;
for (unsigned int i = 0; i < numInputs; ++i)
{
const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[i]];
if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex))
{
return kTfLiteError;
}
armnn::TensorInfo inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor);
inputTensorInfos.emplace_back(inputTensorInfo);
}
// Convert input tensors to const armnn::TensorInfo* type for FORWARD_LAYER_SUPPORT_FUNC.
std::vector<const armnn::TensorInfo*> inputConstTensorInfos;
std::transform(inputTensorInfos.begin(),
inputTensorInfos.end(),
std::back_inserter(inputConstTensorInfos),
[](armnn::TensorInfo& t)->const armnn::TensorInfo*{ return &t; });
// Validate output and get TensorInfo
const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]];
if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex))
{
return kTfLiteError;
}
const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor);
armnn::StackDescriptor desc;
desc.m_NumInputs = static_cast<uint32_t>(numInputs);
// Get axis from TfLite parameters
auto* params = reinterpret_cast<TfLitePackParams*>(tfLiteNode->builtin_data);
desc.m_Axis = static_cast<uint32_t>(params->axis);
// Use the tensor shape of the first input as the "correct" input shape in the descriptor
desc.m_InputShape = inputTensorInfos[0].GetShape();
// Check if supported
bool isSupported = false;
auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
tfLiteContext,
IsStackSupported,
delegateData.m_Backends,
isSupported,
inputConstTensorInfos,
outputTensorInfo,
desc);
};
// If the m_Network is a nullptr, this signals that a prerequisite TfLite callback is required to clarify the
// support for the operator
// If supported, VisitPackOperator will be called again to add the layer to the network as seen below
if (!delegateData.m_Network)
{
validateFunc(outputTensorInfo, isSupported);
return isSupported ? kTfLiteOk : kTfLiteError;
}
// The TfLite Pack operator is equivalent to the ArmNN Stack operator
armnn::IConnectableLayer* layer = delegateData.m_Network->AddStackLayer(desc);
ARMNN_ASSERT(layer != nullptr);
// Connect the Constant Inputs
auto inputsTensorsProcess = ProcessInputs(layer,
delegateData,
tfLiteContext,
tfLiteNode);
if (inputsTensorsProcess == kTfLiteError)
{
return inputsTensorsProcess;
}
armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0);
outputSlot.SetTensorInfo(outputTensorInfo);
// Connect
return Connect(layer, tfLiteNode, delegateData);
}
} // namespace armnnDelegate
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