| // |
| // Copyright © 2023 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| #pragma once |
| |
| #include <OpaqueDelegateUtils.hpp> |
| |
| namespace armnnOpaqueDelegate |
| { |
| |
| TfLiteStatus VisitDequantizeOperator(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. |
| const int* inputTensors; |
| auto numInputs = TfLiteOpaqueNodeNumberOfInputs(tfLiteNode); |
| 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; |
| } |
| |
| 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); |
| armnn::TensorInfo outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true); |
| |
| UpdateConstantTensorOutputs(inputTensorInfo, outputTensorInfo); |
| |
| bool isSupported = false; |
| armnn::BackendId setBackend; |
| auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported) |
| { |
| FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("DEQUANTIZE", |
| tfLiteContext, |
| IsDequantizeSupported, |
| delegateData.m_Backends, |
| isSupported, |
| setBackend, |
| inputTensorInfo, |
| outputTensorInfo); |
| }; |
| |
| if (!delegateData.m_Network) |
| { |
| validateFunc(outputTensorInfo, isSupported); |
| return isSupported ? kTfLiteOk : kTfLiteError; |
| } |
| |
| auto layerName = GetName(armnn::LayerType::Dequantize, nodeIndex); |
| armnn::IConnectableLayer* dequantizeLayer = delegateData.m_Network->AddDequantizeLayer(layerName.c_str()); |
| dequantizeLayer->SetBackendId(setBackend); |
| ARMNN_ASSERT(dequantizeLayer != nullptr); |
| |
| armnn::IOutputSlot& outputSlot = dequantizeLayer->GetOutputSlot(0); |
| outputSlot.SetTensorInfo(outputTensorInfo); |
| |
| auto inputsTensorsProcess = ProcessInputs(dequantizeLayer, |
| delegateData, |
| tfLiteContext, |
| tfLiteNode, |
| nodeIndex); |
| if (inputsTensorsProcess == kTfLiteError) |
| { |
| return inputsTensorsProcess; |
| } |
| |
| return Connect(dequantizeLayer, tfLiteContext, tfLiteNode, delegateData); |
| } |
| |
| TfLiteStatus VisitQuantizeOperator(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. |
| const int* inputTensors; |
| auto numInputs = TfLiteOpaqueNodeNumberOfInputs(tfLiteNode); |
| 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; |
| } |
| |
| 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; |
| } |
| |
| // Only affine per-layer quantization is supported. |
| if (!IsAffineQuantization(*tfLiteOutputTensor)) |
| { |
| TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| tfLiteContext, |
| "TfLiteArmnnOpaqueDelegate: Only affine per-layer quantization is supported in operator #%d node #%d: ", |
| operatorCode, nodeIndex); |
| return kTfLiteError; |
| } |
| |
| const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor); |
| const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true); |
| |
| bool isSupported = false; |
| armnn::BackendId setBackend; |
| auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported) |
| { |
| FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("QUANTIZE", |
| tfLiteContext, |
| IsQuantizeSupported, |
| delegateData.m_Backends, |
| isSupported, |
| setBackend, |
| inputTensorInfo, |
| outputTensorInfo); |
| }; |
| |
| if (!delegateData.m_Network) |
| { |
| validateFunc(outputTensorInfo, isSupported); |
| return isSupported ? kTfLiteOk : kTfLiteError; |
| } |
| |
| auto layerName = GetName(armnn::LayerType::Quantize, nodeIndex); |
| armnn::IConnectableLayer* quantizeLayer = delegateData.m_Network->AddQuantizeLayer(layerName.c_str()); |
| quantizeLayer->SetBackendId(setBackend); |
| ARMNN_ASSERT(quantizeLayer != nullptr); |
| |
| armnn::IOutputSlot& outputSlot = quantizeLayer->GetOutputSlot(0); |
| outputSlot.SetTensorInfo(outputTensorInfo); |
| |
| // try to connect the Constant Inputs if there are any |
| if (ProcessInputs(quantizeLayer, delegateData, tfLiteContext, tfLiteNode, nodeIndex) != kTfLiteOk) |
| { |
| return kTfLiteError; |
| } |
| |
| return Connect(quantizeLayer, tfLiteContext, tfLiteNode, delegateData); |
| } |
| |
| } // namespace armnnOpaqueDelegate |