blob: efc1cbae1645c347c8bbe44f27d03f02f9abc3e8 [file] [log] [blame]
//
// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "DelegateUtils.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>
namespace armnnDelegate
{
TfLiteStatus ValidateSoftmaxOperator(DelegateData& delegateData,
TfLiteContext* tfLiteContext,
const armnn::TensorInfo& inputInfo,
const armnn::TensorInfo& outputTensorInfo,
const armnn::SoftmaxDescriptor& descriptor)
{
bool isSupported = false;
FORWARD_LAYER_SUPPORT_FUNC("SOFTMAX",
tfLiteContext,
IsSoftmaxSupported,
delegateData.m_Backends,
isSupported,
inputInfo,
outputTensorInfo,
descriptor);
return isSupported ? kTfLiteOk : kTfLiteError;
}
TfLiteStatus ValidateLogSoftmaxOperator(DelegateData& delegateData,
TfLiteContext* tfLiteContext,
const armnn::TensorInfo& inputInfo,
const armnn::TensorInfo& outputTensorInfo,
const armnn::LogSoftmaxDescriptor& descriptor)
{
bool isSupported = false;
FORWARD_LAYER_SUPPORT_FUNC("LOG_SOFTMAX",
tfLiteContext,
IsLogSoftmaxSupported,
delegateData.m_Backends,
isSupported,
inputInfo,
outputTensorInfo,
descriptor);
return isSupported ? kTfLiteOk : kTfLiteError;
}
TfLiteStatus VisitSoftmaxOperator(DelegateData& delegateData,
TfLiteContext* tfLiteContext,
TfLiteNode* tfLiteNode,
int nodeIndex,
int32_t softmaxOperatorCode)
{
TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors;
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 node #%d: ",
nodeIndex);
return kTfLiteError;
}
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 node #%d: ",
nodeIndex);
return kTfLiteError;
}
const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor);
const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true);
if (!delegateData.m_Network)
{
switch(softmaxOperatorCode)
{
case kTfLiteBuiltinSoftmax:
{
armnn::SoftmaxDescriptor descriptor;
auto* params = reinterpret_cast<TfLiteSoftmaxParams*>(tfLiteNode->builtin_data);
descriptor.m_Beta = params->beta;
return ValidateSoftmaxOperator(delegateData,
tfLiteContext,
inputTensorInfo,
outputTensorInfo,
descriptor);
}
case kTfLiteBuiltinLogSoftmax:
{
armnn::LogSoftmaxDescriptor descriptor;
return ValidateLogSoftmaxOperator(delegateData,
tfLiteContext,
inputTensorInfo,
outputTensorInfo,
descriptor);
}
default:
return kTfLiteError;
}
}
armnn::IConnectableLayer* softmaxLayer = nullptr;
switch(softmaxOperatorCode)
{
case kTfLiteBuiltinSoftmax:
{
armnn::SoftmaxDescriptor descriptor;
auto* params = reinterpret_cast<TfLiteSoftmaxParams*>(tfLiteNode->builtin_data);
descriptor.m_Beta = params->beta;
softmaxLayer = delegateData.m_Network->AddSoftmaxLayer(descriptor);
break;
}
case kTfLiteBuiltinLogSoftmax:
{
armnn::LogSoftmaxDescriptor descriptor;
softmaxLayer = delegateData.m_Network->AddLogSoftmaxLayer(descriptor);
break;
}
default:
return kTfLiteError;
}
ARMNN_ASSERT(softmaxLayer != nullptr);
armnn::IOutputSlot& outputSlot = softmaxLayer->GetOutputSlot(0);
outputSlot.SetTensorInfo(outputTensorInfo);
// Connect
return Connect(softmaxLayer, tfLiteNode, delegateData);
}
} // namespace armnnDelegate