blob: 1b6d68eb7a17ce14a6e9eaef04ed2631e74ef5ac [file] [log] [blame]
//
// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include <armnn_delegate.hpp>
#include "Version.hpp"
#include "Activation.hpp"
#include "ArgMinMax.hpp"
#include "BatchSpace.hpp"
#include "Comparison.hpp"
#include "Convolution.hpp"
#include "Control.hpp"
#include "ElementwiseBinary.hpp"
#include "ElementwiseUnary.hpp"
#include "Fill.hpp"
#include "FullyConnected.hpp"
#include "Gather.hpp"
#include "GatherNd.hpp"
#include "LogicalBinary.hpp"
#include "Lstm.hpp"
#include "Normalization.hpp"
#include "Pack.hpp"
#include "Pad.hpp"
#include "Pooling.hpp"
#include "Prelu.hpp"
#include "Quantization.hpp"
#include "Redefine.hpp"
#include "Reduce.hpp"
#include "Resize.hpp"
#include "Round.hpp"
#include "Shape.hpp"
#include "Slice.hpp"
#include "Softmax.hpp"
#include "SpaceDepth.hpp"
#include "Split.hpp"
#include "Transpose.hpp"
#include "UnidirectionalSequenceLstm.hpp"
#include "Unpack.hpp"
#include <armnnUtils/Filesystem.hpp>
#include <armnn/utility/Timer.hpp>
#include <flatbuffers/flatbuffers.h>
#include <tensorflow/lite/context_util.h>
#include <tensorflow/lite/schema/schema_generated.h>
#include <algorithm>
#include <iostream>
#include <sstream>
namespace armnnDelegate
{
DelegateOptions TfLiteArmnnDelegateOptionsDefault()
{
DelegateOptions options(armnn::Compute::CpuRef);
return options;
}
TfLiteDelegate* TfLiteArmnnDelegateCreate(armnnDelegate::DelegateOptions options)
{
auto* armnnDelegate = new ::armnnDelegate::Delegate(options);
return armnnDelegate->GetDelegate();
}
void TfLiteArmnnDelegateDelete(TfLiteDelegate* tfLiteDelegate)
{
if (tfLiteDelegate != nullptr)
{
delete static_cast<::armnnDelegate::Delegate*>(tfLiteDelegate->data_);
}
}
TfLiteStatus DoPrepare(TfLiteContext* tfLiteContext, TfLiteDelegate* tfLiteDelegate)
{
TfLiteIntArray* supportedOperators =
static_cast<::armnnDelegate::Delegate*>(tfLiteDelegate->data_)->IdentifyOperatorsToDelegate(tfLiteContext);
// ArmNN Delegate Registration
static const TfLiteRegistration kArmnnSubgraphRegistration = {
// ArmnnSubgraph Init
.init = [](TfLiteContext* tfLiteContext, const char* buffer, size_t length) -> void* {
armnn::IgnoreUnused(length);
const TfLiteDelegateParams* parameters = reinterpret_cast<const TfLiteDelegateParams*>(buffer);
return static_cast<void*>(ArmnnSubgraph::Create(
tfLiteContext, parameters, static_cast<::armnnDelegate::Delegate*>(parameters->delegate->data_)));
},
// ArmnnSubgraph Free
.free = [](TfLiteContext* tfLiteContext, void* buffer) -> void {
armnn::IgnoreUnused(tfLiteContext);
if (buffer != nullptr)
{
delete static_cast<ArmnnSubgraph*>(buffer);
}
},
// ArmnnSubgraph Prepare
.prepare = [](TfLiteContext* tfLiteContext, TfLiteNode* tfLiteNode) -> TfLiteStatus {
if (tfLiteNode->user_data == nullptr)
{
return kTfLiteError;
}
return static_cast<ArmnnSubgraph*>(tfLiteNode->user_data)->Prepare(tfLiteContext);
},
// ArmnnSubgraph Invoke
.invoke = [](TfLiteContext* tfLiteContext, TfLiteNode* tfLiteNode) -> TfLiteStatus {
if (tfLiteNode->user_data == nullptr)
{
return kTfLiteError;
}
return static_cast<ArmnnSubgraph*>(tfLiteNode->user_data)->Invoke(tfLiteContext, tfLiteNode);
},
.profiling_string = nullptr,
.builtin_code = kTfLiteBuiltinDelegate,
.custom_name = "TfLiteArmNnDelegate",
.version = 1,
};
const TfLiteStatus status =
tfLiteContext->ReplaceNodeSubsetsWithDelegateKernels(
tfLiteContext, kArmnnSubgraphRegistration, supportedOperators, tfLiteDelegate);
TfLiteIntArrayFree(supportedOperators);
return status;
}
Delegate::Delegate(armnnDelegate::DelegateOptions options)
: m_Runtime(nullptr, nullptr),
m_Options(std::move(options))
{
// Configures logging for ARMNN
if (options.IsLoggingEnabled())
{
armnn::ConfigureLogging(true, true, options.GetLoggingSeverity());
}
// Create ArmNN Runtime
m_Runtime = armnn::IRuntime::Create(options.GetRuntimeOptions());
std::vector<armnn::BackendId> backends;
if (m_Runtime)
{
const armnn::BackendIdSet supportedDevices = m_Runtime->GetDeviceSpec().GetSupportedBackends();
for (auto& backend : m_Options.GetBackends())
{
if (std::find(supportedDevices.cbegin(), supportedDevices.cend(), backend) == supportedDevices.cend())
{
TFLITE_LOG_PROD(tflite::TFLITE_LOG_INFO,
"TfLiteArmnnDelegate: Requested unknown backend %s", backend.Get().c_str());
}
else
{
backends.push_back(backend);
}
}
}
if (backends.empty())
{
// No known backend specified
throw armnn::InvalidArgumentException("TfLiteArmnnDelegate: No known backend specified.");
}
m_Options.SetBackends(backends);
TFLITE_LOG_PROD_ONCE(tflite::TFLITE_LOG_INFO, "TfLiteArmnnDelegate: Created TfLite ArmNN delegate.");
}
TfLiteIntArray* Delegate::IdentifyOperatorsToDelegate(TfLiteContext* tfLiteContext)
{
TfLiteIntArray* executionPlan = nullptr;
if (tfLiteContext->GetExecutionPlan(tfLiteContext, &executionPlan) != kTfLiteOk)
{
TF_LITE_KERNEL_LOG(tfLiteContext, "TfLiteArmnnDelegate: Unable to get graph execution plan.");
return nullptr;
}
// Delegate data with null network
DelegateData delegateData(m_Options.GetBackends());
TfLiteIntArray* nodesToDelegate = TfLiteIntArrayCreate(executionPlan->size);
nodesToDelegate->size = 0;
std::set<int32_t> unsupportedOperators;
for (int i = 0; i < executionPlan->size; ++i)
{
const int nodeIndex = executionPlan->data[i];
// If TfLite nodes can be delegated to ArmNN
TfLiteNode* tfLiteNode = nullptr;
TfLiteRegistration* tfLiteRegistration = nullptr;
if (tfLiteContext->GetNodeAndRegistration(
tfLiteContext, nodeIndex, &tfLiteNode, &tfLiteRegistration) != kTfLiteOk)
{
TF_LITE_KERNEL_LOG(tfLiteContext,
"TfLiteArmnnDelegate: Unable to get node and registration for node %d.",
nodeIndex);
continue;
}
if (ArmnnSubgraph::VisitNode(
delegateData, tfLiteContext, tfLiteRegistration, tfLiteNode, nodeIndex) != kTfLiteOk)
{
// node is not supported by ArmNN
unsupportedOperators.insert(tfLiteRegistration->builtin_code);
continue;
}
nodesToDelegate->data[nodesToDelegate->size++] = nodeIndex;
}
for (std::set<int32_t>::iterator it=unsupportedOperators.begin(); it!=unsupportedOperators.end(); ++it)
{
TF_LITE_KERNEL_LOG(tfLiteContext,
"Operator %s [%d] is not supported by armnn_delegate.",
tflite::EnumNameBuiltinOperator(tflite::BuiltinOperator(*it)),
*it);
}
std::sort(&nodesToDelegate->data[0], &nodesToDelegate->data[nodesToDelegate->size]);
return nodesToDelegate;
}
TfLiteDelegate* Delegate::GetDelegate()
{
return &m_Delegate;
}
const std::string Delegate::GetVersion()
{
return DELEGATE_VERSION;
}
TfLiteStatus ArmnnSubgraph::AddInputLayer(DelegateData& delegateData,
TfLiteContext* tfLiteContext,
const TfLiteIntArray* inputs,
std::vector<armnn::BindingPointInfo>& inputBindings)
{
const size_t numInputs = static_cast<size_t>(inputs->size);
for (unsigned int i = 0; i < numInputs; ++i)
{
const int32_t tensorId = inputs->data[i];
const TfLiteTensor tensor = tfLiteContext->tensors[tensorId];
// Do not create bindings for constant inputs
if (tensor.allocation_type == kTfLiteMmapRo)
{
continue;
}
auto bindingId = static_cast<armnn::LayerBindingId>((tensorId));
armnn::IConnectableLayer* layer = delegateData.m_Network->AddInputLayer(bindingId);
auto tensorInfo = GetTensorInfoForTfLiteTensor(tensor);
armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0);
outputSlot.SetTensorInfo(tensorInfo);
// Store for creating connections
delegateData.m_OutputSlotForNode[static_cast<unsigned long>(tensorId)] = &outputSlot;
inputBindings.push_back(std::make_pair(bindingId, tensorInfo));
}
return kTfLiteOk;
}
TfLiteStatus ArmnnSubgraph::AddOutputLayer(DelegateData& delegateData,
TfLiteContext* tfLiteContext,
const TfLiteIntArray* outputs,
std::vector<armnn::BindingPointInfo>& outputBindings)
{
const size_t numOutputs = static_cast<size_t>(outputs->size);
for (unsigned int i = 0; i < numOutputs; ++i)
{
const int32_t tensorId = outputs->data[i];
const TfLiteTensor tensor = tfLiteContext->tensors[tensorId];
auto bindingId = static_cast<armnn::LayerBindingId>((tensorId));
armnn::IConnectableLayer* layer = delegateData.m_Network->AddOutputLayer(bindingId);
auto tensorInfo = GetTensorInfoForTfLiteTensor(tensor);
ARMNN_ASSERT(delegateData.m_OutputSlotForNode[static_cast<unsigned long>(tensorId)] != nullptr);
delegateData.m_OutputSlotForNode[static_cast<unsigned long>(tensorId)]->Connect(layer->GetInputSlot(0));
outputBindings.push_back(std::make_pair(bindingId, tensorInfo));
}
return kTfLiteOk;
}
ArmnnSubgraph* ArmnnSubgraph::Create(TfLiteContext* tfLiteContext,
const TfLiteDelegateParams* parameters,
const Delegate* delegate)
{
const auto startTime = armnn::GetTimeNow();
ARMNN_LOG(info) << "ArmnnSubgraph creation";
TfLiteIntArray* executionPlan;
if (tfLiteContext->GetExecutionPlan(tfLiteContext, &executionPlan) != kTfLiteOk)
{
return nullptr;
}
// Initialize DelegateData holds network and output slots information
DelegateData delegateData(delegate->m_Options.GetBackends());
// Build ArmNN Network
armnn::NetworkOptions networkOptions = delegate->m_Options.GetOptimizerOptions().m_ModelOptions;
armnn::NetworkId networkId;
delegateData.m_Network = armnn::INetwork::Create(networkOptions);
delegateData.m_OutputSlotForNode = std::vector<armnn::IOutputSlot*>(tfLiteContext->tensors_size, nullptr);
std::vector<armnn::BindingPointInfo> inputBindings;
std::vector<armnn::BindingPointInfo> outputBindings;
// Add input layer
auto status = AddInputLayer(delegateData, tfLiteContext, parameters->input_tensors, inputBindings);
if (status != kTfLiteOk)
{
throw armnn::Exception("TfLiteArmnnDelegate: Unable to add Inputs to the network!");
}
// Parse TfLite delegate nodes to ArmNN
const auto parseStartTime = armnn::GetTimeNow();
for (int i = 0; i < parameters->nodes_to_replace->size; ++i)
{
const int nodeIndex = parameters->nodes_to_replace->data[i];
TfLiteNode* tfLiteNode = nullptr;
TfLiteRegistration* tfLiteRegistration = nullptr;
if (tfLiteContext->GetNodeAndRegistration(
tfLiteContext, nodeIndex, &tfLiteNode, &tfLiteRegistration) != kTfLiteOk)
{
throw armnn::Exception(&"TfLiteArmnnDelegate: Unable to get node registration: " [ nodeIndex]);
}
if (VisitNode(delegateData, tfLiteContext, tfLiteRegistration, tfLiteNode, nodeIndex) != kTfLiteOk)
{
throw armnn::Exception(&"TfLiteArmnnDelegate: Unable to parse node: " [ nodeIndex]);
}
}
ARMNN_LOG(info) << "Parse nodes to ArmNN time: " << std::setprecision(2)
<< std::fixed << armnn::GetTimeDuration(parseStartTime).count() << " ms";
// Add Output layer
status = AddOutputLayer(delegateData, tfLiteContext, parameters->output_tensors, outputBindings);
if (status != kTfLiteOk)
{
throw armnn::Exception("TfLiteArmnnDelegate: Unable to add Outputs to the network!");
}
// Optimize ArmNN network
armnn::IOptimizedNetworkPtr optNet(nullptr, nullptr);
try
{
const auto optimizeStartTime = armnn::GetTimeNow();
optNet = armnn::Optimize(*(delegateData.m_Network.get()),
delegate->m_Options.GetBackends(),
delegate->m_Runtime->GetDeviceSpec(),
delegate->m_Options.GetOptimizerOptions());
ARMNN_LOG(info) << "Optimize ArmnnSubgraph time: " << std::setprecision(2)
<< std::fixed << armnn::GetTimeDuration(optimizeStartTime).count() << " ms";
}
catch (std::exception &ex)
{
std::stringstream exMessage;
exMessage << "TfLiteArmnnDelegate: Exception (" << ex.what() << ") caught from optimize.";
throw armnn::Exception(exMessage.str());
}
if (!optNet)
{
// Optimize failed
throw armnn::Exception("TfLiteArmnnDelegate: Unable to optimize the network!");
}
// If set, we will serialize the optimized model into a dot file.
const std::string serializeToDotFile = delegate->m_Options.GetSerializeToDot();
if (!serializeToDotFile.empty())
{
ARMNN_LOG(info) << "Writing graph to dot file: " << serializeToDotFile;
fs::path filename = serializeToDotFile;
std::fstream file(filename.c_str(), std::ios_base::out);
optNet->SerializeToDot(file);
}
try
{
const auto loadStartTime = armnn::GetTimeNow();
// Load graph into runtime
std::string errorMessage;
armnn::Status loadingStatus;
armnn::MemorySource inputSource = armnn::MemorySource::Undefined;
armnn::MemorySource outputSource = armnn::MemorySource::Undefined;
// There's a bit of an assumption here that the delegate will only support Malloc memory source.
if (delegate->m_Options.GetOptimizerOptions().m_ImportEnabled)
{
inputSource = armnn::MemorySource::Malloc;
}
if (delegate->m_Options.GetOptimizerOptions().m_ExportEnabled)
{
outputSource = armnn::MemorySource::Malloc;
}
armnn::INetworkProperties networkProperties(false,
inputSource,
outputSource,
delegate->m_Options.GetInternalProfilingState(),
delegate->m_Options.GetInternalProfilingDetail());
loadingStatus = delegate->m_Runtime->LoadNetwork(networkId,
std::move(optNet),
errorMessage,
networkProperties);
if (loadingStatus != armnn::Status::Success)
{
// Network load failed.
throw armnn::Exception("TfLiteArmnnDelegate: Network could not be loaded:" + errorMessage);
}
ARMNN_LOG(info) << "Load ArmnnSubgraph time: " << std::setprecision(2)
<< std::fixed << armnn::GetTimeDuration(loadStartTime).count() << " ms";
}
catch (std::exception& ex)
{
std::stringstream exMessage;
exMessage << "TfLiteArmnnDelegate: Exception (" << ex.what() << ") caught from LoadNetwork.";
throw armnn::Exception(exMessage.str());
}
// Register debug callback function
if (delegate->m_Options.GetDebugCallbackFunction().has_value())
{
delegate->m_Runtime->RegisterDebugCallback(networkId, delegate->m_Options.GetDebugCallbackFunction().value());
}
ARMNN_LOG(info) << "Overall ArmnnSubgraph creation time: " << std::setprecision(2)
<< std::fixed << armnn::GetTimeDuration(startTime).count() << " ms\n";
// Create a new SubGraph with networkId and runtime
return new ArmnnSubgraph(networkId, delegate->m_Runtime.get(), inputBindings, outputBindings);
}
TfLiteStatus ArmnnSubgraph::Prepare(TfLiteContext* tfLiteContext)
{
armnn::IgnoreUnused(tfLiteContext);
return kTfLiteOk;
}
TfLiteStatus ArmnnSubgraph::Invoke(TfLiteContext* tfLiteContext, TfLiteNode* tfLiteNode)
{
// Prepare inputs
armnn::InputTensors inputTensors;
size_t inputIndex = 0;
for (auto inputIdx : tflite::TfLiteIntArrayView(tfLiteNode->inputs))
{
TfLiteTensor* tensor = &tfLiteContext->tensors[inputIdx];
if (tensor->allocation_type != kTfLiteMmapRo)
{
const armnn::BindingPointInfo& inputBinding = m_InputBindings[inputIndex];
armnn::TensorInfo inputTensorInfo = inputBinding.second;
inputTensorInfo.SetConstant(true);
const armnn::ConstTensor inputTensor(inputTensorInfo, tensor->data.data);
inputTensors.emplace_back(inputIdx, inputTensor);
++inputIndex;
}
}
// Prepare outputs
armnn::OutputTensors outputTensors;
size_t outputIndex = 0;
for (auto outputIdx : tflite::TfLiteIntArrayView(tfLiteNode->outputs))
{
const armnn::BindingPointInfo& outputBinding = m_OutputBindings[outputIndex];
TfLiteTensor* tensor = &tfLiteContext->tensors[outputIdx];
const armnn::Tensor outputTensor(outputBinding.second, tensor->data.data);
outputTensors.emplace_back(outputIdx, outputTensor);
++outputIndex;
}
// Run graph
auto status = m_Runtime->EnqueueWorkload(m_NetworkId, inputTensors, outputTensors);
// The delegate holds its own Arm NN runtime so this is our last chance to print internal profiling data.
std::shared_ptr<armnn::IProfiler> profiler = m_Runtime->GetProfiler(m_NetworkId);
if (profiler && profiler->IsProfilingEnabled())
{
profiler->Print(std::cout);
}
return (status == armnn::Status::Success) ? kTfLiteOk : kTfLiteError;
}
TfLiteStatus ArmnnSubgraph::VisitNode(DelegateData& delegateData,
TfLiteContext* tfLiteContext,
TfLiteRegistration* tfLiteRegistration,
TfLiteNode* tfLiteNode,
int nodeIndex)
{
switch (tfLiteRegistration->builtin_code)
{
case kTfLiteBuiltinCustom:
{
#if defined(ARMNN_POST_TFLITE_2_5)
// Custom operators are defined by the name rather than the builtin code.
// Parse the custom_name param in the registration to point to the correct visitor function.
std::string customOperatorName = tfLiteRegistration->custom_name;
if ( customOperatorName == "AveragePool3D" )
{
return VisitPooling3dOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
customOperatorName);
}
else if (customOperatorName == "MaxPool3D")
{
return VisitPooling3dOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
customOperatorName);
}
#endif
// Invalid or unsupported custom operator
return kTfLiteError;
}
case kTfLiteBuiltinAbs:
return VisitElementwiseUnaryOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
armnn::UnaryOperation::Abs);
case kTfLiteBuiltinAdd:
return VisitElementwiseBinaryOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinAdd);
case kTfLiteBuiltinArgMax:
return VisitArgMinMaxOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinArgMax);
case kTfLiteBuiltinArgMin:
return VisitArgMinMaxOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinArgMin);
case kTfLiteBuiltinAveragePool2d:
return VisitPooling2dOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinAveragePool2d);
case kTfLiteBuiltinBatchToSpaceNd:
return VisitBatchToSpaceNdOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinBatchToSpaceNd);
case kTfLiteBuiltinCast:
return VisitCastOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinCast);
case kTfLiteBuiltinConcatenation:
return VisitControlOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinConcatenation);
case kTfLiteBuiltinConv2d:
return VisitConvolutionOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinConv2d);
// Conv3d is only correctly supported for external delegates from TF Lite v2.6, as there was a breaking bug in v2.5.
#if defined(ARMNN_POST_TFLITE_2_5)
case kTfLiteBuiltinConv3d:
return VisitConvolutionOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinConv3d);
#endif
case kTfLiteBuiltinDepthToSpace:
return VisitDepthToSpaceOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinDepthToSpace);
case kTfLiteBuiltinDepthwiseConv2d:
return VisitConvolutionOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinDepthwiseConv2d);
case kTfLiteBuiltinDequantize:
return VisitDequantizeOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinDequantize);
case kTfLiteBuiltinDiv:
return VisitElementwiseBinaryOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinDiv);
case kTfLiteBuiltinElu:
return VisitActivationOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinElu);
case kTfLiteBuiltinEqual:
return VisitComparisonOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinEqual);
case kTfLiteBuiltinExp:
return VisitElementwiseUnaryOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
armnn::UnaryOperation::Exp);
case kTfLiteBuiltinExpandDims:
return VisitExpandDimsOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinExpandDims);
case kTfLiteBuiltinFill:
return VisitFillOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinFill);
case kTfLiteBuiltinFloor:
return VisitFloorOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinFloor);
case kTfLiteBuiltinFloorDiv:
return VisitElementwiseBinaryOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinFloorDiv);
case kTfLiteBuiltinFullyConnected:
return VisitFullyConnectedOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinFullyConnected);
case kTfLiteBuiltinGather:
return VisitGatherOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinGather);
case kTfLiteBuiltinGatherNd:
return VisitGatherNdOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinGatherNd);
case kTfLiteBuiltinGreater:
return VisitComparisonOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinGreater);
case kTfLiteBuiltinGreaterEqual:
return VisitComparisonOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinGreaterEqual);
case kTfLiteBuiltinHardSwish:
return VisitActivationOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinHardSwish);
case kTfLiteBuiltinL2Normalization:
return VisitL2NormalizationOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinL2Normalization);
case kTfLiteBuiltinL2Pool2d:
return VisitPooling2dOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinL2Pool2d);
case kTfLiteBuiltinLess:
return VisitComparisonOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinLess);
case kTfLiteBuiltinLessEqual:
return VisitComparisonOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinLessEqual);
case kTfLiteBuiltinLocalResponseNormalization:
return VisitLocalResponseNormalizationOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinLocalResponseNormalization);
case kTfLiteBuiltinLogicalAnd:
return VisitLogicalBinaryOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinLogicalAnd,
armnn::LogicalBinaryOperation::LogicalAnd);
case kTfLiteBuiltinLogicalNot:
return VisitElementwiseUnaryOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
armnn::UnaryOperation::LogicalNot);
case kTfLiteBuiltinLogicalOr:
return VisitLogicalBinaryOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinLogicalOr,
armnn::LogicalBinaryOperation::LogicalOr);
case kTfLiteBuiltinLogistic:
return VisitActivationOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinLogistic);
case kTfLiteBuiltinLogSoftmax:
return VisitSoftmaxOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinLogSoftmax);
case kTfLiteBuiltinLstm:
return VisitLstmOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinLstm);
case kTfLiteBuiltinMaxPool2d:
return VisitPooling2dOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinMaxPool2d);
case kTfLiteBuiltinMaximum:
return VisitElementwiseBinaryOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinMaximum);
case kTfLiteBuiltinMean:
return VisitControlOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinMean);
case kTfLiteBuiltinMinimum:
return VisitElementwiseBinaryOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinMinimum);
case kTfLiteBuiltinMirrorPad:
return VisitPadOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinMirrorPad);
case kTfLiteBuiltinMul:
return VisitElementwiseBinaryOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinMul);
case kTfLiteBuiltinNeg:
return VisitElementwiseUnaryOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
armnn::UnaryOperation::Neg);
case kTfLiteBuiltinNotEqual:
return VisitComparisonOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinNotEqual);
case kTfLiteBuiltinPack:
return VisitPackOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinPack);
case kTfLiteBuiltinPad:
return VisitPadOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinPad);
case kTfLiteBuiltinPadv2:
return VisitPadOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinPadv2);
case kTfLiteBuiltinPrelu:
return VisitPreluOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinPrelu);
case kTfLiteBuiltinQuantize:
return VisitQuantizeOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinQuantize);
case kTfLiteBuiltinRank:
return VisitControlOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinRank);
case kTfLiteBuiltinReduceMax:
return VisitReduceOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinReduceMax);
case kTfLiteBuiltinReduceMin:
return VisitReduceOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinReduceMin);
case kTfLiteBuiltinReduceProd:
return VisitReduceOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinReduceProd);
case kTfLiteBuiltinRelu:
return VisitActivationOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinRelu);
case kTfLiteBuiltinReluN1To1:
return VisitActivationOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinReluN1To1);
case kTfLiteBuiltinRelu6:
return VisitActivationOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinRelu6);
case kTfLiteBuiltinReshape:
return VisitReshapeOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinReshape);
case kTfLiteBuiltinResizeBilinear:
return VisitResizeOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinResizeBilinear);
case kTfLiteBuiltinResizeNearestNeighbor:
return VisitResizeOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinResizeNearestNeighbor);
case kTfLiteBuiltinRsqrt:
return VisitElementwiseUnaryOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
armnn::UnaryOperation::Rsqrt);
case kTfLiteBuiltinShape:
return VisitShapeOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinShape);
case kTfLiteBuiltinSplit:
return VisitSplitOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinSplit);
case kTfLiteBuiltinSplitV:
return VisitSplitVOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinSplitV);
case kTfLiteBuiltinSqrt:
return VisitElementwiseUnaryOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
armnn::UnaryOperation::Sqrt);
case kTfLiteBuiltinSqueeze:
return VisitSqueezeOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinSqueeze);
case kTfLiteBuiltinStridedSlice:
return VisitSliceOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinStridedSlice);
case kTfLiteBuiltinSum:
return VisitReduceOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinSum);
case kTfLiteBuiltinTranspose:
return VisitTransposeOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinTranspose);
case kTfLiteBuiltinTransposeConv:
return VisitConvolutionOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinTransposeConv);
case kTfLiteBuiltinSoftmax:
return VisitSoftmaxOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinSoftmax);
case kTfLiteBuiltinSpaceToBatchNd:
return VisitSpaceToBatchNdOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinSpaceToBatchNd);
case kTfLiteBuiltinSpaceToDepth:
return VisitSpaceToDepthOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinSpaceToDepth);
case kTfLiteBuiltinSub:
return VisitElementwiseBinaryOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinSub);
case kTfLiteBuiltinTanh:
return VisitActivationOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinTanh);
case kTfLiteBuiltinUnidirectionalSequenceLstm:
return VisitUnidirectionalSequenceLstmOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinUnidirectionalSequenceLstm);
case kTfLiteBuiltinUnpack:
return VisitUnpackOperator(delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex,
kTfLiteBuiltinUnpack);
default:
return kTfLiteError;
}
}
} // armnnDelegate namespace