| Francis Murtagh | c4fb0dd | 2023-03-16 17:01:56 +0000 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2023 Arm Ltd and Contributors. All rights reserved. |
| 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| Teresa Charlin | f69ae56 | 2023-04-27 14:42:23 +0100 | [diff] [blame^] | 5 | |
| 6 | #pragma once |
| 7 | |
| 8 | #include "OpaqueDelegateUtils.hpp" |
| 9 | |
| 10 | namespace armnnOpaqueDelegate |
| 11 | { |
| 12 | |
| 13 | std::string GetLayerName(armnn::UnaryOperation unaryOperation) |
| 14 | { |
| 15 | std::string layerName = "ELEMENTWISE_UNARY"; |
| 16 | switch (unaryOperation) |
| 17 | { |
| 18 | case armnn::UnaryOperation::Abs: |
| 19 | layerName += " ABS"; |
| 20 | break; |
| 21 | case armnn::UnaryOperation::Ceil: |
| 22 | layerName += " CEIL"; |
| 23 | break; |
| 24 | case armnn::UnaryOperation::Exp: |
| 25 | layerName += " EXP"; |
| 26 | break; |
| 27 | case armnn::UnaryOperation::Log: |
| 28 | layerName += " LOG"; |
| 29 | break; |
| 30 | case armnn::UnaryOperation::LogicalNot: |
| 31 | layerName += " LOGICALNOT"; |
| 32 | break; |
| 33 | case armnn::UnaryOperation::Neg: |
| 34 | layerName += " NEG"; |
| 35 | break; |
| 36 | case armnn::UnaryOperation::Rsqrt: |
| 37 | layerName += " RSQRT"; |
| 38 | break; |
| 39 | case armnn::UnaryOperation::Sin: |
| 40 | layerName += " SIN"; |
| 41 | break; |
| 42 | case armnn::UnaryOperation::Sqrt: |
| 43 | layerName += " SQRT"; |
| 44 | break; |
| 45 | default: |
| 46 | layerName += " UNKNOWN"; |
| 47 | } |
| 48 | return layerName; |
| 49 | } |
| 50 | |
| 51 | TfLiteStatus VisitElementwiseUnaryOperator(DelegateData& delegateData, |
| 52 | TfLiteOpaqueContext* tfLiteContext, |
| 53 | TfLiteOpaqueNode* tfLiteNode, |
| 54 | int nodeIndex, |
| 55 | int32_t tfLiteElementWiseUnaryOperatorCode, |
| 56 | armnn::UnaryOperation unaryOperation) |
| 57 | { |
| 58 | TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| 59 | TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| 60 | |
| 61 | // Gather input indices and use to get input tensor. |
| 62 | int numInputs = 0; |
| 63 | const int* inputTensors; |
| 64 | if (TfLiteOpaqueNodeInputs(tfLiteNode, &inputTensors, &numInputs) != kTfLiteOk) |
| 65 | { |
| 66 | TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| 67 | tfLiteContext, |
| 68 | "TfLiteArmnnOpaqueDelegate: Unable to gather input tensor indices from node #%d: ", |
| 69 | nodeIndex); |
| 70 | return kTfLiteError; |
| 71 | } |
| 72 | // Use input indices to get input tensor. |
| 73 | const TfLiteOpaqueTensor* tfLiteInputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]); |
| 74 | if (!IsValid(tfLiteContext, tfLiteInputTensor, tfLiteElementWiseUnaryOperatorCode, nodeIndex)) |
| 75 | { |
| 76 | return kTfLiteError; |
| 77 | } |
| 78 | |
| 79 | // Gather output indices and use to get output tensor. |
| 80 | int numOutputs = 0; |
| 81 | const int* outputTensors; |
| 82 | if (TfLiteOpaqueNodeOutputs(tfLiteNode, &outputTensors, &numOutputs) != kTfLiteOk) |
| 83 | { |
| 84 | TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| 85 | tfLiteContext, |
| 86 | "TfLiteArmnnOpaqueDelegate: Unable to gather output tensor indices from node #%d: ", |
| 87 | nodeIndex); |
| 88 | return kTfLiteError; |
| 89 | } |
| 90 | // Use output indices to get output tensor. |
| 91 | const TfLiteOpaqueTensor* tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]); |
| 92 | if (!IsValid(tfLiteContext, tfLiteOutputTensor, tfLiteElementWiseUnaryOperatorCode, nodeIndex)) |
| 93 | { |
| 94 | return kTfLiteError; |
| 95 | } |
| 96 | |
| 97 | const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor); |
| 98 | const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true); |
| 99 | |
| 100 | armnn::ElementwiseUnaryDescriptor descriptor(unaryOperation); |
| 101 | bool isSupported = false; |
| 102 | armnn::BackendId setBackend; |
| 103 | auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported, std::string layerName) |
| 104 | { |
| 105 | FORWARD_LAYER_OPAQUE_SUPPORT_FUNC(layerName.c_str(), |
| 106 | tfLiteContext, |
| 107 | IsElementwiseUnarySupported, |
| 108 | delegateData.m_Backends, |
| 109 | isSupported, |
| 110 | setBackend, |
| 111 | inputTensorInfo, |
| 112 | outputTensorInfo, |
| 113 | descriptor); |
| 114 | }; |
| 115 | |
| 116 | if (!delegateData.m_Network) |
| 117 | { |
| 118 | validateFunc(outputTensorInfo, isSupported, GetLayerName(unaryOperation)); |
| 119 | return isSupported ? kTfLiteOk : kTfLiteError; |
| 120 | } |
| 121 | |
| 122 | armnn::IConnectableLayer* layer = delegateData.m_Network->AddElementwiseUnaryLayer(descriptor); |
| 123 | layer->SetBackendId(setBackend); |
| 124 | ARMNN_ASSERT(layer != nullptr); |
| 125 | |
| 126 | armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); |
| 127 | outputSlot.SetTensorInfo(outputTensorInfo); |
| 128 | |
| 129 | // try to connect the Constant Inputs if there are any |
| 130 | if(ProcessInputs(layer, delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk ) |
| 131 | { |
| 132 | return kTfLiteError; |
| 133 | } |
| 134 | |
| 135 | // Connect |
| 136 | return Connect(layer, tfLiteContext, tfLiteNode, delegateData); |
| 137 | } |
| 138 | |
| 139 | } // namespace armnnOpaqueDelegate |