// // Copyright © 2020 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // #pragma once #include #include #include #include #include namespace armnnDelegate { TfLiteStatus VisitArgMinMaxOperator(DelegateData& delegateData, TfLiteContext* tfLiteContext, TfLiteNode* tfLiteNode, int nodeIndex, int32_t argMinMaxOperatorCode) { 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& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]]; if (!IsValid(tfLiteContext, tfLiteInputTensor, argMinMaxOperatorCode, nodeIndex)) { return kTfLiteError; } const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]]; if (!IsValid(tfLiteContext, tfLiteOutputTensor, argMinMaxOperatorCode, nodeIndex)) { return kTfLiteError; } const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor); const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor); // Get const axis value from model and set it to descriptor. const TfLiteTensor& tfLiteAxisTensor = tfLiteTensors[tfLiteNode->inputs->data[1]]; if (!IsValid(tfLiteContext, tfLiteAxisTensor, argMinMaxOperatorCode, nodeIndex)) { return kTfLiteError; } armnn::ArgMinMaxDescriptor desc; // Get the axis value from the input tensor switch (tfLiteAxisTensor.type) { case kTfLiteInt32: case kTfLiteInt64: desc.m_Axis = tflite::GetTensorData(&tfLiteAxisTensor)[0]; break; default: TF_LITE_MAYBE_KERNEL_LOG( tfLiteContext, "TfLiteArmnnDelegate: Axis value data type is not supported in operator #%d node #%d: ", argMinMaxOperatorCode, nodeIndex); return kTfLiteError; } // If output_type is int32 then set Signed32 else Signed64. Default type is Signed64. if (argMinMaxOperatorCode == kTfLiteBuiltinArgMax) { desc.m_Function = armnn::ArgMinMaxFunction::Max; auto* argMaxParameters = reinterpret_cast(tfLiteNode->builtin_data); if (argMaxParameters->output_type != kTfLiteInt32 && argMaxParameters->output_type != kTfLiteInt64) { TF_LITE_MAYBE_KERNEL_LOG( tfLiteContext, "TfLiteArmnnDelegate: output_type data type is not supported in operator #%d node #%d: ", argMinMaxOperatorCode, nodeIndex); return kTfLiteError; } } else { desc.m_Function = armnn::ArgMinMaxFunction::Min; auto* argMinParameters = reinterpret_cast(tfLiteNode->builtin_data); if (argMinParameters->output_type != kTfLiteInt32 && argMinParameters->output_type != kTfLiteInt64) { TF_LITE_MAYBE_KERNEL_LOG( tfLiteContext, "TfLiteArmnnDelegate: output_type data type is not supported in operator #%d node #%d: ", argMinMaxOperatorCode, nodeIndex); return kTfLiteError; } } bool isSupported = false; auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported) { FORWARD_LAYER_SUPPORT_FUNC("ARGMINMAX", tfLiteContext, IsArgMinMaxSupported, delegateData.m_Backends, isSupported, inputTensorInfo, outInfo, desc); }; if (!delegateData.m_Network) { validateFunc(outputTensorInfo, isSupported); return isSupported ? kTfLiteOk : kTfLiteError; } // Add an ArgMinMax layer armnn::IConnectableLayer* layer = delegateData.m_Network->AddArgMinMaxLayer(desc); ARMNN_ASSERT(layer != nullptr); armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); outputSlot.SetTensorInfo(outputTensorInfo); // Connect return Connect(layer, tfLiteNode, delegateData); } } // namespace armnnDelegate