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Diffstat (limited to 'delegate/src/Unpack.hpp')
| -rw-r--r-- | delegate/src/Unpack.hpp | 184 |
1 files changed, 184 insertions, 0 deletions
diff --git a/delegate/src/Unpack.hpp b/delegate/src/Unpack.hpp new file mode 100644 index 0000000000..87200ff431 --- /dev/null +++ b/delegate/src/Unpack.hpp @@ -0,0 +1,184 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include <armnn/utility/IgnoreUnused.hpp> + +#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> +#include <numeric> + +namespace armnnDelegate +{ + +TfLiteStatus VisitUnpackOperator(DelegateData& delegateData, + TfLiteContext* tfLiteContext, + TfLiteNode* tfLiteNode, + int nodeIndex, + int32_t operatorCode) +{ + TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); + + const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; + const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]]; + + if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex)) + { + return kTfLiteError; + } + + // Get Unpack Axis + const auto params = reinterpret_cast<TfLiteUnpackParams*>(tfLiteNode->builtin_data); + + const unsigned int unpackAxis = NonNegative(params->axis, nodeIndex); + + const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor); + + if (unpackAxis >= inputTensorInfo.GetNumDimensions()) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: The unpack axis #%d cannot be greater than or equal to " + "the number of input dimensions #%d in operator #%d node #%d", + unpackAxis, inputTensorInfo.GetNumDimensions(), operatorCode, nodeIndex); + return kTfLiteError; + } + + // Get Unpack Num + unsigned int unpackNum = NonNegative(params->num, nodeIndex); + + // If num is not defined, automatically infer from the length of the dimension axis. + if(unpackNum == 0) + { + unpackNum = inputTensorInfo.GetShape()[unpackAxis]; + } + + // If unpack number cannot be inferred and is still zero, return kTfLiteError. + if(unpackNum == 0) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: Number to unpack must greater than zero in operator #%d node #%d: ", + operatorCode, nodeIndex); + return kTfLiteError; + } + + // Check outputs + TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, unpackNum, nodeIndex)); + + + auto inputDimSize = inputTensorInfo.GetNumDimensions(); + std::vector<unsigned int> unpackDimSizes(inputDimSize); + + // Add current input shape to unpackDimSizes + for (unsigned int i = 0; i < inputDimSize; ++i) + { + unpackDimSizes[i] = inputTensorInfo.GetShape()[i]; + } + + if (unpackDimSizes[unpackAxis] != unpackNum) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: Number to unpack must be the same as length " + "of the dimension to unpack along in operator #%d node #%d: ", + operatorCode, nodeIndex); + return kTfLiteError; + } + + unpackDimSizes[unpackAxis] /= unpackNum; + + armnn::SplitterDescriptor splitDesc(unpackNum, static_cast<unsigned int>(unpackDimSizes.size())); + for (unsigned int j = 0; j < unpackNum; ++j) + { + // Set the size of the views. + for (unsigned int dimIdx = 0; dimIdx < unpackDimSizes.size(); ++dimIdx) + { + splitDesc.SetViewSize(j, dimIdx, unpackDimSizes[dimIdx]); + } + splitDesc.SetViewOriginCoord(j, unpackAxis, unpackDimSizes[unpackAxis] * j); + } + + std::vector<armnn::TensorInfo> outputs; + for (unsigned int i = 0; i < unpackNum; ++i) + { + const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[i]]; + if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex)) + { + return kTfLiteError; + } + outputs.push_back(GetTensorInfoForTfLiteTensor(tfLiteOutputTensor)); + } + const std::vector<std::reference_wrapper<armnn::TensorInfo>> outputTensorInfos(outputs.begin(), outputs.end()); + + if (!delegateData.m_Network) + { + // Check if supported + bool isSupported = false; + FORWARD_LAYER_SUPPORT_FUNC(__func__, + tfLiteContext, + IsSplitterSupported, + delegateData.m_Backends, + isSupported, + inputTensorInfo, + outputTensorInfos, + splitDesc); + return isSupported ? kTfLiteOk : kTfLiteError; + } + + std::string splitterLayerName("Unpack Splitter"); + + armnn::IConnectableLayer* splitterLayer = delegateData.m_Network->AddSplitterLayer(splitDesc, + splitterLayerName.c_str()); + ARMNN_ASSERT(splitterLayer != nullptr); + + for (unsigned int k = 0; k < splitterLayer->GetNumOutputSlots(); ++k) + { + splitterLayer->GetOutputSlot(k).SetTensorInfo(outputs[k]); + } + + // Connect the input slots + delegateData.m_OutputSlotForNode[tfLiteNode->inputs->data[0]]->Connect(splitterLayer->GetInputSlot(0)); + + armnn::TensorShape splitOutShape = armnn::TensorShape(static_cast<unsigned int>(unpackDimSizes.size()), + unpackDimSizes.data()); + + // Create reshape to remove the unpacked dimension for unpack operator of each output from Splitter. + for (unsigned int outputIndex = 0; outputIndex < splitterLayer->GetNumOutputSlots(); ++outputIndex) + { + armnn::TensorInfo outputTensorInfo = outputTensorInfos[outputIndex]; + + std::string reshapeLayerName("Unpack Reshape"); + armnn::ReshapeDescriptor reshapeDescriptor; + reshapeDescriptor.m_TargetShape = outputTensorInfo.GetShape(); + armnn::IConnectableLayer* reshapeLayer = delegateData.m_Network->AddReshapeLayer(reshapeDescriptor, + reshapeLayerName.c_str()); + + ARMNN_ASSERT(reshapeLayer != nullptr); + + splitterLayer->GetOutputSlot(outputIndex).SetTensorInfo(armnn::TensorInfo(splitOutShape, + outputTensorInfo.GetDataType(), + outputTensorInfo.GetQuantizationScale(), + outputTensorInfo.GetQuantizationOffset())); + splitterLayer->GetOutputSlot(outputIndex).Connect(reshapeLayer->GetInputSlot(0)); + + reshapeLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); + + armnn::IOutputSlot& slot = reshapeLayer->GetOutputSlot(0); + + delegateData.m_OutputSlotForNode[ + static_cast<unsigned long>(tfLiteNode->outputs->data[outputIndex])] = &slot; + + } + + return kTfLiteOk; +} + +} // namespace armnnDelegate |