// // Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // #pragma once #include #include #include #include #include #include namespace armnnDelegate { TfLiteStatus VisitTransposeOperator(DelegateData& delegateData, TfLiteContext* tfLiteContext, TfLiteNode* tfLiteNode, int nodeIndex, int32_t tfliteTransposeOperatorCode) { 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& tfLiteInputTensor0 = tfLiteTensors[tfLiteNode->inputs->data[0]]; if (IsDynamicTensor(tfLiteInputTensor0)) { TF_LITE_MAYBE_KERNEL_LOG(tfLiteContext, "TfLiteArmnnDelegate: Dynamic input tensors are not supported in " "operator #%d node #%d: ", tfliteTransposeOperatorCode, nodeIndex); return kTfLiteError; } const TfLiteTensor& tfLiteInputTensor1 = tfLiteTensors[tfLiteNode->inputs->data[1]]; if (IsDynamicTensor(tfLiteInputTensor1)) { TF_LITE_MAYBE_KERNEL_LOG(tfLiteContext, "TfLiteArmnnDelegate: Dynamic input tensors are not supported in " "operator #%d node #%d: ", tfliteTransposeOperatorCode, nodeIndex); return kTfLiteError; } const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]]; if (IsDynamicTensor(tfLiteOutputTensor)) { TF_LITE_MAYBE_KERNEL_LOG(tfLiteContext, "TfLiteArmnnDelegate: Dynamic output tensors are not supported in " "operator #%d node #%d: ", tfliteTransposeOperatorCode, nodeIndex); return kTfLiteError; } const armnn::TensorInfo& inputTensorInfo0 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor0); const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true); auto* permTensorDataPtr = tflite::GetTensorData(&tfLiteInputTensor1); unsigned int numEl = tfLiteInputTensor1.dims->data[0]; if (numEl > static_cast(armnn::MaxNumOfTensorDimensions)) { return kTfLiteError; } if (tfLiteInputTensor1.dims->size != 1) { return kTfLiteError; } armnn::TransposeDescriptor descriptor(armnn::PermutationVector( reinterpret_cast (permTensorDataPtr), static_cast(numEl))); bool isSupported = false; armnn::BackendId setBackend; auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported) { FORWARD_LAYER_SUPPORT_FUNC("TRANSPOSE", tfLiteContext, IsTransposeSupported, delegateData.m_Backends, isSupported, setBackend, inputTensorInfo0, outputTensorInfo, descriptor); }; if (!delegateData.m_Network) { validateFunc(outputTensorInfo, isSupported); return isSupported ? kTfLiteOk : kTfLiteError; } auto layerName = GetLayerName(armnn::LayerType::Transpose, nodeIndex); armnn::IConnectableLayer* transposeLayer = delegateData.m_Network->AddTransposeLayer(descriptor, layerName.c_str()); transposeLayer->SetBackendId(setBackend); ARMNN_ASSERT(transposeLayer != nullptr); // permutation vector given to descriptor object if (transposeLayer->GetNumInputSlots() != 1) { return kTfLiteError; } armnn::IOutputSlot& outputSlot = transposeLayer->GetOutputSlot(0); outputSlot.SetTensorInfo(outputTensorInfo); // try to connect the Constant Inputs if there are any if (ProcessInputs(transposeLayer, delegateData, tfLiteContext, tfLiteNode, nodeIndex) != kTfLiteOk) { return kTfLiteError; } return Connect(transposeLayer, tfLiteNode, delegateData); } } // namespace armnnDelegate