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Diffstat (limited to 'delegate/src/Split.hpp')
| -rw-r--r-- | delegate/src/Split.hpp | 347 |
1 files changed, 0 insertions, 347 deletions
diff --git a/delegate/src/Split.hpp b/delegate/src/Split.hpp deleted file mode 100644 index b183b55c54..0000000000 --- a/delegate/src/Split.hpp +++ /dev/null @@ -1,347 +0,0 @@ -// -// Copyright © 2020,2022-2023 Arm Ltd and Contributors. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#pragma once - -#include "DelegateUtils.hpp" - -#include <algorithm> -#include <iterator> -#include <vector> - -namespace armnnDelegate -{ - -constexpr unsigned int MaxNumOfTensorDimensions = 5U; - -TfLiteStatus VisitSplitOperator(DelegateData& delegateData, - TfLiteContext* tfLiteContext, - TfLiteNode* tfLiteNode, - int nodeIndex, - int32_t tfLiteSplitOperatorCode) -{ - TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex)); - - auto* splitParameters = reinterpret_cast<TfLiteSplitParams*>(tfLiteNode->builtin_data); - const unsigned int numSplits = NonNegative(splitParameters->num_splits, nodeIndex); - - TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, numSplits, nodeIndex)); - - const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; - const TfLiteTensor& tfLiteAxisTensor = tfLiteTensors[tfLiteNode->inputs->data[0]]; - if (!IsValid(tfLiteContext, tfLiteAxisTensor, tfLiteSplitOperatorCode, nodeIndex)) - { - return kTfLiteError; - } - - const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[1]]; - if (!IsValid(tfLiteContext, tfLiteInputTensor, tfLiteSplitOperatorCode, nodeIndex)) - { - return kTfLiteError; - } - - const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor); - - ARMNN_ASSERT(GetTensorInfoForTfLiteTensor(tfLiteAxisTensor).GetNumElements() == 1); - auto* axisTensorDataPtr = tflite::GetTensorData<int32_t>(&tfLiteAxisTensor); - std::vector<int32_t> axisTensorData(axisTensorDataPtr, axisTensorDataPtr + 1); - int32_t axis = axisTensorData[0]; - - auto inputDimensions = static_cast<int32_t>(inputTensorInfo.GetNumDimensions()); - if (((axis < -inputDimensions) && (axis < 0)) || ((axis >= inputDimensions) && (axis > 0))) - { - // Square bracket denotes inclusive n while parenthesis denotes exclusive n - // E.g. Rank 4 tensor can have axis in range [-4, 3) - // -1 == 3, -2 == 2, -3 == 1, -4 == 0 - TF_LITE_MAYBE_KERNEL_LOG( - tfLiteContext, - "TfLiteArmnnDelegate: Operation has invalid axis: #%d. Axis must be in range [-n, n) in node #%d:", - axis, nodeIndex); - } - const unsigned int splitDim = ComputeWrappedIndex(axis, inputTensorInfo.GetNumDimensions()); - - std::vector<armnn::TensorInfo> outputs; - for (unsigned int i = 0; i < numSplits; ++i) - { - const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[i]]; - if (!IsValid(tfLiteContext, tfLiteOutputTensor, tfLiteSplitOperatorCode, nodeIndex)) - { - return kTfLiteError; - } - outputs.push_back(GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true)); - } - const std::vector<std::reference_wrapper<armnn::TensorInfo>> outputTensorInfos(outputs.begin(), outputs.end()); - - auto inputDimSize = inputTensorInfo.GetNumDimensions(); - if (inputDimSize > MaxNumOfTensorDimensions) - { - TF_LITE_MAYBE_KERNEL_LOG( - tfLiteContext, - "TfLiteArmnnDelegate: The number of dimensions: #%d for input tensors of the split op cannot be greater " - "than #%d in node #%d: ", inputDimSize, MaxNumOfTensorDimensions, nodeIndex); - return kTfLiteError; - } - - std::vector<unsigned int> splitterDimSizes(inputDimSize); - - // Add current input shape to splitterDimSizes - for (unsigned int i = 0; i < inputDimSize; ++i) - { - splitterDimSizes[i] = inputTensorInfo.GetShape()[i]; - } - - if (splitterDimSizes[splitDim] % numSplits != 0) - { - TF_LITE_MAYBE_KERNEL_LOG( - tfLiteContext, - "TfLiteArmnnDelegate: Number of splits #%d must evenly divide the dimension #%d in node #%d: ", - numSplits, splitterDimSizes[splitDim], nodeIndex); - return kTfLiteError; - } - splitterDimSizes[splitDim] /= numSplits; - - armnn::SplitterDescriptor splitDescriptor(numSplits, inputDimSize); - for (unsigned int j = 0; j < numSplits; ++j) - { - // Set the size of the views. - for (unsigned int dimIdx = 0; dimIdx < splitterDimSizes.size(); ++dimIdx) - { - splitDescriptor.SetViewSize(j, dimIdx, splitterDimSizes[dimIdx]); - } - splitDescriptor.SetViewOriginCoord(j, splitDim, splitterDimSizes[splitDim] * j); - } - - armnn::BackendId setBackend; - if (!delegateData.m_Network) - { - // Check if supported - bool isSupported = false; - FORWARD_LAYER_SUPPORT_FUNC("SPLIT", - tfLiteContext, - IsSplitterSupported, - delegateData.m_Backends, - isSupported, - setBackend, - inputTensorInfo, - outputTensorInfos, - splitDescriptor); - return isSupported ? kTfLiteOk : kTfLiteError; - } - - armnn::IConnectableLayer* layer = delegateData.m_Network->AddSplitterLayer(splitDescriptor); - layer->SetBackendId(setBackend); - ARMNN_ASSERT(layer != nullptr); - - for (unsigned int k = 0; k < layer->GetNumOutputSlots(); ++k) - { - layer->GetOutputSlot(k).SetTensorInfo(outputs[k]); - } - - // Connect the input slots - delegateData.m_OutputSlotForNode[tfLiteNode->inputs->data[1]]->Connect(layer->GetInputSlot(0)); - - // Prepare output slots - for (unsigned int outputIndex = 0; outputIndex < layer->GetNumOutputSlots(); ++outputIndex) - { - armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(outputIndex); - delegateData.m_OutputSlotForNode[ - static_cast<unsigned long>(tfLiteNode->outputs->data[outputIndex])] = &outputSlot; - } - - return kTfLiteOk; -} - -TfLiteStatus VisitSplitVOperator(DelegateData& delegateData, - TfLiteContext* tfLiteContext, - TfLiteNode* tfLiteNode, - int nodeIndex, - int32_t tfLiteSplitVOperatorCode) -{ - TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 3, nodeIndex)); - - const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; - const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]]; - if (!IsValid(tfLiteContext, tfLiteInputTensor, tfLiteSplitVOperatorCode, nodeIndex)) - { - return kTfLiteError; - } - - const TfLiteTensor& tfLiteSplitsTensor = tfLiteTensors[tfLiteNode->inputs->data[1]]; - if (!IsValid(tfLiteContext, tfLiteSplitsTensor, tfLiteSplitVOperatorCode, nodeIndex)) - { - return kTfLiteError; - } - - const TfLiteTensor& tfLiteAxisTensor = tfLiteTensors[tfLiteNode->inputs->data[2]]; - if (!IsValid(tfLiteContext, tfLiteAxisTensor, tfLiteSplitVOperatorCode, nodeIndex)) - { - return kTfLiteError; - } - - const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor); - const armnn::TensorInfo& splitsTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteSplitsTensor); - ARMNN_ASSERT(splitsTensorInfo.GetNumDimensions() == 1); - ARMNN_ASSERT(GetTensorInfoForTfLiteTensor(tfLiteAxisTensor).GetNumElements() == 1); - - auto* axisTensorDataPtr = tflite::GetTensorData<int32_t>(&tfLiteAxisTensor); - std::vector<int32_t> axisTensorData(axisTensorDataPtr, axisTensorDataPtr + 1); - int32_t axis = axisTensorData[0]; - - auto inputDimensions = static_cast<int32_t>(inputTensorInfo.GetNumDimensions()); - if (((axis < -inputDimensions) && (axis < 0)) || ((axis >= inputDimensions) && (axis > 0))) - { - TF_LITE_MAYBE_KERNEL_LOG( - tfLiteContext, - "TfLiteArmnnDelegate: Operation has invalid axis: #%d. Axis must be in range [-n, n) in node #%d:", - axis, nodeIndex); - } - const unsigned int splitDim = ComputeWrappedIndex(axisTensorData[0], inputTensorInfo.GetNumDimensions()); - - auto* splitVParameters = reinterpret_cast<TfLiteSplitVParams*>(tfLiteNode->builtin_data); - unsigned int numSplits = 0; - if (splitVParameters) - { - numSplits = NonNegative(splitVParameters->num_splits, nodeIndex); - } - else - { - numSplits = splitsTensorInfo.GetNumElements(); - } - - if (numSplits <= 0) - { - TF_LITE_MAYBE_KERNEL_LOG( - tfLiteContext, "TfLiteArmnnDelegate: Invalid number of splits %d in node #%d", - numSplits, nodeIndex); - return kTfLiteError; - } - - TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, numSplits, nodeIndex)); - std::vector<armnn::TensorInfo> outputs; - for (unsigned int i = 0; i < numSplits; ++i) - { - const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[i]]; - if (!IsValid(tfLiteContext, tfLiteOutputTensor, tfLiteSplitVOperatorCode, nodeIndex)) - { - return kTfLiteError; - } - outputs.push_back(GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true)); - } - const std::vector<std::reference_wrapper<armnn::TensorInfo>> outputTensorInfos(outputs.begin(), outputs.end()); - - auto inputDimSize = inputTensorInfo.GetNumDimensions(); - if (inputDimSize > MaxNumOfTensorDimensions) - { - TF_LITE_MAYBE_KERNEL_LOG( - tfLiteContext, - "TfLiteArmnnDelegate: The number of dimensions: #%d for input tensors of the split op cannot be greater " - "than #%d in node #%d: ", inputDimSize, MaxNumOfTensorDimensions, nodeIndex); - return kTfLiteError; - } - - std::vector<int32_t> splitsTensorData(numSplits); - std::memcpy(splitsTensorData.data(), tfLiteSplitsTensor.data.data, splitsTensorInfo.GetNumBytes()); - - - unsigned int index = 0; - unsigned int inferredIndex = 0; - int numberOfInferred = 0; - int splitSum = 0; - - for (auto splitData : splitsTensorData) - { - if (splitData < 0) - { - ++numberOfInferred; - inferredIndex = index; - } - else - { - splitSum += splitData; - } - ++index; - } - - // Check for inferred axis - if (numberOfInferred == 0) - { - if (splitSum != armnn::numeric_cast<int>(inputTensorInfo.GetShape()[splitDim])) - { - TF_LITE_MAYBE_KERNEL_LOG( - tfLiteContext, "TfLiteArmnnDelegate: SplitV split_sizes does not sum to the dimension of value along" - " split_dim in node #%d", nodeIndex); - return kTfLiteError; - } - } - else if (numberOfInferred == 1) - { - splitsTensorData[inferredIndex] = armnn::numeric_cast<int>(inputTensorInfo.GetShape()[splitDim]) - splitSum; - } - else - { - TF_LITE_MAYBE_KERNEL_LOG( - tfLiteContext, "TfLiteArmnnDelegate: SplitV cannot infer split size for more than one split in node #%d", - nodeIndex); - return kTfLiteError; - } - - armnn::SplitterDescriptor splitDescriptor(numSplits, inputDimSize); - unsigned int accumSplit = 0; - for (unsigned int j = 0; j < numSplits; ++j) - { - unsigned int splitSize = armnn::numeric_cast<unsigned int>(splitsTensorData[j]); - - // Set the size of the views. - for (unsigned int dimIdx = 0; dimIdx < inputTensorInfo.GetNumDimensions(); ++dimIdx) - { - unsigned int dimSize = inputTensorInfo.GetShape()[dimIdx]; - if (dimIdx == splitDim) - { - dimSize = splitSize; - } - splitDescriptor.SetViewSize(j, dimIdx, dimSize); - } - - splitDescriptor.SetViewOriginCoord(j, splitDim, accumSplit); - accumSplit += splitSize; - } - - armnn::BackendId setBackend; - if (!delegateData.m_Network) - { - // Check if supported - bool isSupported = false; - FORWARD_LAYER_SUPPORT_FUNC("SPLIT", - tfLiteContext, - IsSplitterSupported, - delegateData.m_Backends, - isSupported, - setBackend, - inputTensorInfo, - outputTensorInfos, - splitDescriptor); - return isSupported ? kTfLiteOk : kTfLiteError; - } - - armnn::IConnectableLayer* layer = delegateData.m_Network->AddSplitterLayer(splitDescriptor); - layer->SetBackendId(setBackend); - ARMNN_ASSERT(layer != nullptr); - - for (unsigned int k = 0; k < layer->GetNumOutputSlots(); ++k) - { - layer->GetOutputSlot(k).SetTensorInfo(outputs[k]); - } - - // try to connect the Constant Inputs if there are any - if(ProcessInputs(layer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk ) - { - return kTfLiteError; - } - - // Connect - return Connect(layer, tfLiteNode, delegateData); -} - -} // namespace armnnDelegate
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