| // |
| // Copyright © 2023 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #pragma once |
| |
| #include <OpaqueDelegateUtils.hpp> |
| #include <SharedFunctions.hpp> |
| |
| namespace armnnOpaqueDelegate |
| { |
| |
| TfLiteStatus VisitFloorOperator(DelegateData& delegateData, |
| TfLiteOpaqueContext* tfLiteContext, |
| TfLiteOpaqueNode* tfLiteNode, |
| int nodeIndex, |
| int32_t operatorCode) |
| { |
| TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| |
| // Gather input indices and use to get input tensor. |
| int numInputs = 0; |
| const int* inputTensors; |
| if (TfLiteOpaqueNodeInputs(tfLiteNode, &inputTensors, &numInputs) != kTfLiteOk) |
| { |
| TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| tfLiteContext, |
| "TfLiteArmnnOpaqueDelegate: Unable to gather input tensor indices from node #%d: ", |
| nodeIndex); |
| return kTfLiteError; |
| } |
| |
| // Use input indices to get input tensors. |
| const TfLiteOpaqueTensor* tfLiteInputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]); |
| if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex)) |
| { |
| return kTfLiteError; |
| } |
| |
| // Gather output indices and use to get output tensors. |
| int numOutputs = 0; |
| const int* outputTensors; |
| if (TfLiteOpaqueNodeOutputs(tfLiteNode, &outputTensors, &numOutputs) != kTfLiteOk) |
| { |
| TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| tfLiteContext, |
| "TfLiteArmnnOpaqueDelegate: Unable to gather output tensor indices from node #%d: ", |
| nodeIndex); |
| return kTfLiteError; |
| } |
| |
| const TfLiteOpaqueTensor* tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]); |
| if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex)) |
| { |
| return kTfLiteError; |
| } |
| |
| const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor); |
| // NOTE: looks like the outputTensorInfo is the only thing that is required for the case |
| // where we are adding the floor layer so maybe move the other stuff inside the |
| // if !delegateData block for efficiency. |
| const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true); |
| |
| // If the m_Network is a nullptr, this signals that a prerequisite TfLite callback is required to clarify the |
| // support for the operator |
| // If supported, VisitFloorOperator will be called again to add the layer to the network as seen further below |
| if (!delegateData.m_Network) |
| { |
| return ValidateFloorOperator(delegateData, tfLiteContext, inputTensorInfo, outputTensorInfo); |
| } |
| |
| // Add a Floor layer |
| armnn::IConnectableLayer* layer = delegateData.m_Network->AddFloorLayer(); |
| 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, tfLiteContext, tfLiteNode, delegateData); |
| } |
| |
| } // namespace armnnOpaqueDelegate |