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