| // |
| // Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #pragma once |
| |
| #include <armnn/utility/IgnoreUnused.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> |
| |
| namespace armnnDelegate |
| { |
| |
| TfLiteStatus VisitStridedSliceOperator(DelegateData& delegateData, |
| TfLiteContext* tfLiteContext, |
| TfLiteNode* tfLiteNode, |
| int nodeIndex, |
| int32_t sliceOperatorCode) |
| { |
| TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 4, nodeIndex)); |
| TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| |
| // 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; |
| armnn::BackendId setBackend; |
| auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported) |
| { |
| FORWARD_LAYER_SUPPORT_FUNC("STRIDED_SLICE", |
| tfLiteContext, |
| IsStridedSliceSupported, |
| delegateData.m_Backends, |
| isSupported, |
| setBackend, |
| 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); |
| layer->SetBackendId(setBackend); |
| ARMNN_ASSERT(layer != nullptr); |
| |
| armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); |
| outputSlot.SetTensorInfo(outputTensorInfo); |
| |
| // 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 |
| |