// // Copyright © 2021 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // #pragma once #include #include #include #include #include namespace armnnDelegate { TfLiteStatus VisitReduceOperator(DelegateData& delegateData, TfLiteContext* tfLiteContext, TfLiteNode* tfLiteNode, int nodeIndex, int32_t reduceOperatorCode) { TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex)); TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]]; if (!IsValid(tfLiteContext, tfLiteInputTensor, reduceOperatorCode, nodeIndex)) { return kTfLiteError; } const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]]; if (!IsValid(tfLiteContext, tfLiteOutputTensor, reduceOperatorCode, nodeIndex)) { return kTfLiteError; } const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor); const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor); // Get const axis value from model and set it to descriptor. const TfLiteTensor& tfLiteAxisTensor = tfLiteTensors[tfLiteNode->inputs->data[1]]; if (!IsValid(tfLiteContext, tfLiteAxisTensor, reduceOperatorCode, nodeIndex)) { return kTfLiteError; } const armnn::TensorInfo& axisTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteAxisTensor); auto* axisTensorData = tflite::GetTensorData(&tfLiteAxisTensor); std::vector axis; // Add axis data to vector to be converter to unsigned int and assigned to descriptor axis. if (axisTensorData != nullptr) { for (unsigned int i = 0; i < axisTensorInfo.GetNumElements(); ++i) { axis.emplace_back(axisTensorData[i]); } } else { for (unsigned int i = 0; i < inputTensorInfo.GetNumDimensions(); ++i) { axis.push_back(i); } } // Convert the axis to unsigned int and remove duplicates. unsigned int rank = inputTensorInfo.GetNumDimensions(); std::set uniqueAxis; std::transform(axis.begin(), axis.end(), std::inserter(uniqueAxis, uniqueAxis.begin()), [rank](int i)->unsigned int{ return (i + rank) % rank; }); armnn::ReduceDescriptor desc; desc.m_vAxis.assign(uniqueAxis.begin(), uniqueAxis.end()); auto* reducerParameters = reinterpret_cast(tfLiteNode->builtin_data); desc.m_KeepDims = reducerParameters->keep_dims; if (reduceOperatorCode == kTfLiteBuiltinReduceMax) { desc.m_ReduceOperation = armnn::ReduceOperation::Max; } else if (reduceOperatorCode == kTfLiteBuiltinReduceMin) { desc.m_ReduceOperation = armnn::ReduceOperation::Min; } else if (reduceOperatorCode == kTfLiteBuiltinSum) { desc.m_ReduceOperation = armnn::ReduceOperation::Sum; } else { TF_LITE_MAYBE_KERNEL_LOG( tfLiteContext, "TfLiteArmnnDelegate: Unsupported Reduction Operator #%d node #%d: ", reduceOperatorCode, nodeIndex); return kTfLiteError; } bool isSupported = false; auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported) { FORWARD_LAYER_SUPPORT_FUNC(__func__, tfLiteContext, IsReduceSupported, delegateData.m_Backends, isSupported, inputTensorInfo, outInfo, desc); }; if (!delegateData.m_Network) { validateFunc(outputTensorInfo, isSupported); return isSupported ? kTfLiteOk : kTfLiteError; } // Add an Reduce layer armnn::IConnectableLayer* layer = delegateData.m_Network->AddReduceLayer(desc); ARMNN_ASSERT(layer != nullptr); armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); outputSlot.SetTensorInfo(outputTensorInfo); // Connect return Connect(layer, tfLiteNode, delegateData); } } // namespace armnnDelegate