| // |
| // Copyright © 2020 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 VisitDequantizeOperator(DelegateData& delegateData, |
| TfLiteContext* tfLiteContext, |
| TfLiteNode* tfLiteNode, |
| int nodeIndex, |
| int32_t tfLiteDequantizeOperatorCode) |
| { |
| TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| |
| const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; |
| const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]]; |
| if (IsDynamicTensor(tfLiteInputTensor)) |
| { |
| TF_LITE_MAYBE_KERNEL_LOG( |
| tfLiteContext, |
| "TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ", |
| tfLiteDequantizeOperatorCode, 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: ", |
| tfLiteDequantizeOperatorCode, nodeIndex); |
| |
| return kTfLiteError; |
| } |
| |
| const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor); |
| const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor); |
| |
| bool isSupported = false; |
| auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported) |
| { |
| FORWARD_LAYER_SUPPORT_FUNC(__func__, |
| tfLiteContext, |
| IsDequantizeSupported, |
| delegateData.m_Backends, |
| isSupported, |
| inputTensorInfo, |
| outputTensorInfo); |
| }; |
| |
| if (!delegateData.m_Network) |
| { |
| validateFunc(outputTensorInfo, isSupported); |
| return isSupported ? kTfLiteOk : kTfLiteError; |
| } |
| |
| armnn::IConnectableLayer* dequantizeLayer = delegateData.m_Network->AddDequantizeLayer(); |
| ARMNN_ASSERT(dequantizeLayer != nullptr); |
| |
| armnn::IOutputSlot& outputSlot = dequantizeLayer->GetOutputSlot(0); |
| outputSlot.SetTensorInfo(outputTensorInfo); |
| |
| return Connect(dequantizeLayer, tfLiteNode, delegateData); |
| } |
| |
| TfLiteStatus VisitQuantizeOperator(DelegateData& delegateData, |
| TfLiteContext* tfLiteContext, |
| TfLiteNode* tfLiteNode, |
| int nodeIndex, |
| int32_t tfLiteQuantizeOperatorCode) |
| { |
| TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| |
| const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; |
| const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]]; |
| if (IsDynamicTensor(tfLiteInputTensor)) |
| { |
| TF_LITE_MAYBE_KERNEL_LOG( |
| tfLiteContext, |
| "TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ", |
| tfLiteQuantizeOperatorCode, 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: ", |
| tfLiteQuantizeOperatorCode, nodeIndex); |
| return kTfLiteError; |
| } |
| |
| // Only affine per-layer quantization is supported. |
| if (!IsAffineQuantization(tfLiteOutputTensor)) |
| { |
| TF_LITE_MAYBE_KERNEL_LOG( |
| tfLiteContext, |
| "TfLiteArmnnDelegate: Only affine per-layer quantization is supported in operator #%d node #%d: ", |
| tfLiteQuantizeOperatorCode, nodeIndex); |
| return kTfLiteError; |
| } |
| |
| const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor); |
| const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor); |
| |
| bool isSupported = false; |
| auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported) |
| { |
| FORWARD_LAYER_SUPPORT_FUNC(__func__, |
| tfLiteContext, |
| IsQuantizeSupported, |
| delegateData.m_Backends, |
| isSupported, |
| inputTensorInfo, |
| outputTensorInfo); |
| }; |
| |
| if (!delegateData.m_Network) |
| { |
| validateFunc(outputTensorInfo, isSupported); |
| return isSupported ? kTfLiteOk : kTfLiteError; |
| } |
| |
| armnn::IConnectableLayer* quantizeLayer = delegateData.m_Network->AddQuantizeLayer(); |
| ARMNN_ASSERT(quantizeLayer != nullptr); |
| |
| armnn::IOutputSlot& outputSlot = quantizeLayer->GetOutputSlot(0); |
| outputSlot.SetTensorInfo(outputTensorInfo); |
| |
| return Connect(quantizeLayer, tfLiteNode, delegateData); |
| } |
| |
| } // namespace armnnDelegate |