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author | Jan Eilers <jan.eilers@arm.com> | 2021-02-03 09:14:30 +0000 |
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committer | KeithARM <keith.davis@arm.com> | 2021-02-15 12:32:46 +0000 |
commit | 2ffddda9d9f890a041bcdcc80948d2de1e627832 (patch) | |
tree | 84f789b1a2536418186e92ccb0661e341dfdfdfd /delegate/src/Slice.hpp | |
parent | 800b281e506e921006c23cd4309781b6508c0fcb (diff) | |
download | armnn-2ffddda9d9f890a041bcdcc80948d2de1e627832.tar.gz |
IVGCVSW-5386 TfLiteDelegate: Add Strided Slice operator
Signed-off-by: Jan Eilers <jan.eilers@arm.com>
Change-Id: Icd87b1c54e1a5de84893882da30840a9097f6d84
Diffstat (limited to 'delegate/src/Slice.hpp')
-rw-r--r-- | delegate/src/Slice.hpp | 125 |
1 files changed, 119 insertions, 6 deletions
diff --git a/delegate/src/Slice.hpp b/delegate/src/Slice.hpp index 0311abf41c..a237034bb6 100644 --- a/delegate/src/Slice.hpp +++ b/delegate/src/Slice.hpp @@ -21,13 +21,126 @@ TfLiteStatus VisitSliceOperator(DelegateData& delegateData, int nodeIndex, int32_t sliceOperatorCode) { - armnn::IgnoreUnused(delegateData, - tfLiteContext, - tfLiteNode, - nodeIndex, - sliceOperatorCode); + TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 4, nodeIndex)); + TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); - return kTfLiteError; + // Read inputs [input, begin, end, strides] + int numInputs = tfLiteNode->inputs->size; + std::vector<const TfLiteTensor*> tfLiteInputs; + tfLiteInputs.reserve(numInputs); + const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; + for (int i = 0; i < numInputs; i++) + { + const TfLiteTensor* inputTensor = &tfLiteTensors[tfLiteNode->inputs->data[i]]; + tfLiteInputs.push_back(inputTensor); + if (!IsValid(tfLiteContext, *inputTensor, sliceOperatorCode, nodeIndex)) + { + return kTfLiteError; + } + } + + // We save the begin, end and strides tensors in our descriptor. Therefore we have to read those values from inputs + int inputRank = tfLiteInputs[0]->dims->size; + auto ReadInt32Input = [&](int inputIndex, std::vector<int32_t>& outputData) -> TfLiteStatus + { + if (tfLiteInputs[inputIndex]->type != kTfLiteInt32) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: The Begin-, End- and Stride-Tensors of the StridedSlice operation need to " + "be of type int32. Operator: #%d node #%d: ", + sliceOperatorCode, nodeIndex); + return kTfLiteError; + } + int rank = tfLiteInputs[inputIndex]->dims->size; + if (rank != 1) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: The Begin-, End- and Stride-Tensors of the StridedSlice operation need to " + "be a 1D-Tensor. Operator: #%d node #%d: ", + sliceOperatorCode, nodeIndex); + return kTfLiteError; + } + int numValues = tfLiteInputs[inputIndex]->dims->data[0]; + if (numValues != inputRank) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: The number of values in the Begin-, End- and Stride-Tensors of the " + "StridedSlice operation need to be equal to the rank of the Input-Tensor. Operator: #%d node #%d: ", + sliceOperatorCode, nodeIndex); + return kTfLiteError; + } + // return tensor data + auto* tensorDataPtr = tflite::GetTensorData<int32_t>(tfLiteInputs[inputIndex]); + outputData.assign(tensorDataPtr, tensorDataPtr+numValues); + return kTfLiteOk; + }; + + std::vector<int32_t> beginData; + if (ReadInt32Input(1, beginData) != kTfLiteOk) + return kTfLiteError; + std::vector<int32_t> endData; + if (ReadInt32Input(2, endData) != kTfLiteOk) + return kTfLiteError; + std::vector<int32_t> strideData; + if (ReadInt32Input(3, strideData) != kTfLiteOk) + return kTfLiteError; + + // parse built in options + auto* stridedSliceParams = reinterpret_cast<TfLiteStridedSliceParams*>(tfLiteNode->builtin_data); + + // Write all data to the descriptor + armnn::StridedSliceDescriptor descriptor; + descriptor.m_Begin = std::move(beginData); + descriptor.m_End = std::move(endData); + descriptor.m_Stride = std::move(strideData); + descriptor.m_BeginMask = stridedSliceParams->begin_mask; + descriptor.m_EllipsisMask = stridedSliceParams->ellipsis_mask; + descriptor.m_EndMask = stridedSliceParams->end_mask; + descriptor.m_NewAxisMask = stridedSliceParams->new_axis_mask; + descriptor.m_ShrinkAxisMask = stridedSliceParams->shrink_axis_mask; + descriptor.m_DataLayout = armnn::DataLayout::NHWC; + + // Validate output + const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]]; + if (!IsValid(tfLiteContext, tfLiteOutputTensor, sliceOperatorCode, nodeIndex)) + { + return kTfLiteError; + } + + const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(*tfLiteInputs[0]); + const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor); + + bool isSupported = false; + auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported) + { + FORWARD_LAYER_SUPPORT_FUNC(__func__, + tfLiteContext, + IsStridedSliceSupported, + delegateData.m_Backends, + isSupported, + inputTensorInfo, + outInfo, + descriptor); + }; + + if (!delegateData.m_Network) + { + validateFunc(outputTensorInfo, isSupported); + return isSupported ? kTfLiteOk : kTfLiteError; + } + + // Add a StridedSlice layer + armnn::IConnectableLayer* layer = delegateData.m_Network->AddStridedSliceLayer(descriptor); + ARMNN_ASSERT(layer != nullptr); + + armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); + outputSlot.SetTensorInfo(outputTensorInfo); + + // Connect + return Connect(layer, tfLiteNode, delegateData); } } // namespace armnnDelegate |