blob: df848469b17fda23386ad97396df42a0d4278602 [file] [log] [blame]
//
// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "OpaqueDelegateUtils.hpp"
namespace armnnOpaqueDelegate
{
std::string GetLayerName(armnn::UnaryOperation unaryOperation)
{
std::string layerName = "ELEMENTWISE_UNARY";
switch (unaryOperation)
{
case armnn::UnaryOperation::Abs:
layerName += " ABS";
break;
case armnn::UnaryOperation::Ceil:
layerName += " CEIL";
break;
case armnn::UnaryOperation::Exp:
layerName += " EXP";
break;
case armnn::UnaryOperation::Log:
layerName += " LOG";
break;
case armnn::UnaryOperation::LogicalNot:
layerName += " LOGICALNOT";
break;
case armnn::UnaryOperation::Neg:
layerName += " NEG";
break;
case armnn::UnaryOperation::Rsqrt:
layerName += " RSQRT";
break;
case armnn::UnaryOperation::Sin:
layerName += " SIN";
break;
case armnn::UnaryOperation::Sqrt:
layerName += " SQRT";
break;
default:
layerName += " UNKNOWN";
}
return layerName;
}
TfLiteStatus VisitElementwiseUnaryOperator(DelegateData& delegateData,
TfLiteOpaqueContext* tfLiteContext,
TfLiteOpaqueNode* tfLiteNode,
int nodeIndex,
int32_t tfLiteElementWiseUnaryOperatorCode,
armnn::UnaryOperation unaryOperation)
{
TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
// Gather input indices and use to get input tensor.
int numInputs = 0;
const int* inputTensors;
if (TfLiteOpaqueNodeInputs(tfLiteNode, &inputTensors, &numInputs) != kTfLiteOk)
{
TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
tfLiteContext,
"TfLiteArmnnOpaqueDelegate: Unable to gather input tensor indices from node #%d: ",
nodeIndex);
return kTfLiteError;
}
// Use input indices to get input tensor.
const TfLiteOpaqueTensor* tfLiteInputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]);
if (!IsValid(tfLiteContext, tfLiteInputTensor, tfLiteElementWiseUnaryOperatorCode, nodeIndex))
{
return kTfLiteError;
}
// Gather output indices and use to get output tensor.
int numOutputs = 0;
const int* outputTensors;
if (TfLiteOpaqueNodeOutputs(tfLiteNode, &outputTensors, &numOutputs) != kTfLiteOk)
{
TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
tfLiteContext,
"TfLiteArmnnOpaqueDelegate: Unable to gather output tensor indices from node #%d: ",
nodeIndex);
return kTfLiteError;
}
// Use output indices to get output tensor.
const TfLiteOpaqueTensor* tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]);
if (!IsValid(tfLiteContext, tfLiteOutputTensor, tfLiteElementWiseUnaryOperatorCode, nodeIndex))
{
return kTfLiteError;
}
const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor);
const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true);
armnn::ElementwiseUnaryDescriptor descriptor(unaryOperation);
bool isSupported = false;
armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported, std::string layerName)
{
FORWARD_LAYER_OPAQUE_SUPPORT_FUNC(layerName.c_str(),
tfLiteContext,
IsElementwiseUnarySupported,
delegateData.m_Backends,
isSupported,
setBackend,
inputTensorInfo,
outputTensorInfo,
descriptor);
};
if (!delegateData.m_Network)
{
validateFunc(outputTensorInfo, isSupported, GetLayerName(unaryOperation));
return isSupported ? kTfLiteOk : kTfLiteError;
}
armnn::IConnectableLayer* layer = delegateData.m_Network->AddElementwiseUnaryLayer(descriptor);
layer->SetBackendId(setBackend);
ARMNN_ASSERT(layer != nullptr);
armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0);
outputSlot.SetTensorInfo(outputTensorInfo);
// try to connect the Constant Inputs if there are any
if(ProcessInputs(layer, delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk )
{
return kTfLiteError;
}
// Connect
return Connect(layer, tfLiteContext, tfLiteNode, delegateData);
}
} // namespace armnnOpaqueDelegate