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 | // |
Matthew Sloyan | 0bd4c62 | 2023-04-27 11:48:26 +0100 | [diff] [blame] | 5 | |
| 6 | #pragma once |
| 7 | |
| 8 | #include <OpaqueDelegateUtils.hpp> |
| 9 | |
| 10 | namespace armnnOpaqueDelegate |
| 11 | { |
| 12 | |
Teresa Charlin | f69ae56 | 2023-04-27 14:42:23 +0100 | [diff] [blame] | 13 | std::string GetLayerName(armnn::ActivationFunction activationFunction) |
| 14 | { |
| 15 | std::string layerName = "ACTIVATION"; |
| 16 | switch (activationFunction) |
| 17 | { |
| 18 | case armnn::ActivationFunction::Abs: |
| 19 | layerName += " ABS"; |
| 20 | break; |
| 21 | case armnn::ActivationFunction::BoundedReLu: |
| 22 | layerName += " BOUNDED_RELU"; |
| 23 | break; |
| 24 | case armnn::ActivationFunction::Elu: |
| 25 | layerName += " ELU"; |
| 26 | break; |
Teresa Charlin | 077cddb | 2023-09-15 15:19:21 +0100 | [diff] [blame] | 27 | case armnn::ActivationFunction::Gelu: |
| 28 | layerName += " GELU"; |
| 29 | break; |
Teresa Charlin | f69ae56 | 2023-04-27 14:42:23 +0100 | [diff] [blame] | 30 | case armnn::ActivationFunction::HardSwish: |
| 31 | layerName += " HARD_SWISH"; |
| 32 | break; |
| 33 | case armnn::ActivationFunction::LeakyReLu: |
| 34 | layerName += " LEAKY_RELU"; |
| 35 | break; |
| 36 | case armnn::ActivationFunction::Linear: |
| 37 | layerName += " LINEAR"; |
| 38 | break; |
| 39 | case armnn::ActivationFunction::ReLu: |
| 40 | layerName += " RELU"; |
| 41 | break; |
| 42 | case armnn::ActivationFunction::Sigmoid: |
| 43 | layerName += " SIGMOID"; |
| 44 | break; |
| 45 | case armnn::ActivationFunction::SoftReLu: |
| 46 | layerName += " SOFT_RELU"; |
| 47 | break; |
| 48 | case armnn::ActivationFunction::Square: |
| 49 | layerName += " SQUARE"; |
| 50 | break; |
| 51 | case armnn::ActivationFunction::Sqrt: |
| 52 | layerName += " SQRT"; |
| 53 | break; |
| 54 | case armnn::ActivationFunction::TanH: |
| 55 | layerName += " TANH"; |
| 56 | break; |
| 57 | default: |
| 58 | layerName += " UNKNOWN"; |
| 59 | } |
| 60 | return layerName; |
| 61 | } |
| 62 | |
Matthew Sloyan | 0bd4c62 | 2023-04-27 11:48:26 +0100 | [diff] [blame] | 63 | TfLiteStatus ValidateActivationOperator(DelegateData& delegateData, |
| 64 | TfLiteOpaqueContext* tfLiteContext, |
| 65 | const armnn::TensorInfo& inputInfo, |
| 66 | const armnn::TensorInfo& outputInfo, |
| 67 | armnn::ActivationDescriptor& activationDesc) |
| 68 | { |
| 69 | bool isSupported = false; |
Teresa Charlin | f69ae56 | 2023-04-27 14:42:23 +0100 | [diff] [blame] | 70 | auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported, std::string layerName) |
Matthew Sloyan | 0bd4c62 | 2023-04-27 11:48:26 +0100 | [diff] [blame] | 71 | { |
Teresa Charlin | f69ae56 | 2023-04-27 14:42:23 +0100 | [diff] [blame] | 72 | FORWARD_LAYER_OPAQUE_SUPPORT_FUNC(layerName.c_str(), |
Matthew Sloyan | 0bd4c62 | 2023-04-27 11:48:26 +0100 | [diff] [blame] | 73 | tfLiteContext, |
| 74 | IsActivationSupported, |
| 75 | delegateData.m_Backends, |
| 76 | isSupported, |
| 77 | armnn::BackendId(), |
| 78 | inputInfo, |
| 79 | outputInfo, |
| 80 | activationDesc); |
| 81 | }; |
| 82 | |
Teresa Charlin | f69ae56 | 2023-04-27 14:42:23 +0100 | [diff] [blame] | 83 | validateFunc(outputInfo, isSupported, GetLayerName(activationDesc.m_Function)); |
Matthew Sloyan | 0bd4c62 | 2023-04-27 11:48:26 +0100 | [diff] [blame] | 84 | return isSupported ? kTfLiteOk : kTfLiteError; |
| 85 | } |
| 86 | |
| 87 | TfLiteStatus VisitActivationOperator(DelegateData& delegateData, |
| 88 | TfLiteOpaqueContext* tfLiteContext, |
| 89 | TfLiteOpaqueNode* tfLiteNode, |
| 90 | int nodeIndex, |
| 91 | int32_t operatorCode) |
| 92 | { |
| 93 | TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| 94 | TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| 95 | |
| 96 | // Gather input indices and use to get input tensor. |
| 97 | int numInputs = 0; |
| 98 | const int* inputTensors; |
| 99 | if (TfLiteOpaqueNodeInputs(tfLiteNode, &inputTensors, &numInputs) != kTfLiteOk) |
| 100 | { |
| 101 | TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| 102 | tfLiteContext, |
| 103 | "TfLiteArmnnOpaqueDelegate: Unable to gather input tensor indices from node #%d: ", |
| 104 | nodeIndex); |
| 105 | return kTfLiteError; |
| 106 | } |
| 107 | |
| 108 | const TfLiteOpaqueTensor* tfLiteInputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]); |
| 109 | if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex)) |
| 110 | { |
| 111 | return kTfLiteError; |
| 112 | } |
| 113 | |
| 114 | // Gather output indices and use to get output tensors. |
| 115 | int numOutputs = 0; |
| 116 | const int* outputTensors; |
| 117 | if (TfLiteOpaqueNodeOutputs(tfLiteNode, &outputTensors, &numOutputs) != kTfLiteOk) |
| 118 | { |
| 119 | TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| 120 | tfLiteContext, |
| 121 | "TfLiteArmnnOpaqueDelegate: Unable to gather output tensor indices from node #%d: ", |
| 122 | nodeIndex); |
| 123 | return kTfLiteError; |
| 124 | } |
| 125 | |
| 126 | const TfLiteOpaqueTensor* tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]); |
| 127 | if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex)) |
| 128 | { |
| 129 | return kTfLiteError; |
| 130 | } |
| 131 | |
| 132 | const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor); |
| 133 | const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true); |
| 134 | |
| 135 | armnn::ActivationDescriptor activationDesc; |
| 136 | switch(operatorCode) |
| 137 | { |
| 138 | case kTfLiteBuiltinRelu: |
| 139 | { |
| 140 | activationDesc.m_Function = armnn::ActivationFunction::ReLu; |
| 141 | break; |
| 142 | } |
| 143 | case kTfLiteBuiltinRelu6: |
| 144 | { |
| 145 | activationDesc.m_Function = armnn::ActivationFunction::BoundedReLu; |
| 146 | activationDesc.m_A = 6.0f; |
| 147 | break; |
| 148 | } |
| 149 | case kTfLiteBuiltinLogistic: |
| 150 | { |
| 151 | activationDesc.m_Function = armnn::ActivationFunction::Sigmoid; |
| 152 | break; |
| 153 | } |
| 154 | case kTfLiteBuiltinTanh: |
| 155 | { |
| 156 | activationDesc.m_Function = armnn::ActivationFunction::TanH; |
| 157 | activationDesc.m_A = 1.0f; |
| 158 | activationDesc.m_B = 1.0f; |
| 159 | break; |
| 160 | } |
| 161 | case kTfLiteBuiltinElu: |
| 162 | { |
| 163 | activationDesc.m_Function = armnn::ActivationFunction::Elu; |
| 164 | activationDesc.m_A = 1.0f; |
| 165 | break; |
| 166 | } |
| 167 | case kTfLiteBuiltinHardSwish: |
| 168 | { |
| 169 | activationDesc.m_Function = armnn::ActivationFunction::HardSwish; |
| 170 | break; |
| 171 | } |
Tianle Cheng | ae93173 | 2023-07-28 11:53:04 +0100 | [diff] [blame] | 172 | case kTfLiteBuiltinLeakyRelu: |
| 173 | { |
| 174 | // Get alpha param from builtin data |
| 175 | auto* leakyReluParameters = |
| 176 | reinterpret_cast<TfLiteLeakyReluParams*>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode)); |
| 177 | activationDesc.m_Function = armnn::ActivationFunction::LeakyReLu; |
| 178 | activationDesc.m_A = leakyReluParameters->alpha; |
| 179 | break; |
| 180 | } |
Teresa Charlin | 077cddb | 2023-09-15 15:19:21 +0100 | [diff] [blame] | 181 | case kTfLiteBuiltinGelu: |
| 182 | { |
| 183 | activationDesc.m_Function = armnn::ActivationFunction::Gelu; |
| 184 | break; |
| 185 | } |
Matthew Sloyan | 0bd4c62 | 2023-04-27 11:48:26 +0100 | [diff] [blame] | 186 | default: |
| 187 | { |
| 188 | return kTfLiteError; |
| 189 | } |
| 190 | } |
| 191 | if (!delegateData.m_Network) |
| 192 | { |
| 193 | return ValidateActivationOperator(delegateData, |
| 194 | tfLiteContext, |
| 195 | inputTensorInfo, |
| 196 | outputTensorInfo, |
| 197 | activationDesc); |
| 198 | } |
Mike Kelly | a280650 | 2023-08-03 10:42:11 +0100 | [diff] [blame] | 199 | auto layerName = GetName(activationDesc.m_Function, nodeIndex); |
| 200 | armnn::IConnectableLayer* activationLayer = delegateData.m_Network->AddActivationLayer(activationDesc, |
| 201 | layerName.c_str()); |
Matthew Sloyan | 0bd4c62 | 2023-04-27 11:48:26 +0100 | [diff] [blame] | 202 | ARMNN_ASSERT(activationLayer != nullptr); |
| 203 | |
| 204 | armnn::IOutputSlot& outputSlot = activationLayer->GetOutputSlot(0); |
| 205 | outputSlot.SetTensorInfo(outputTensorInfo); |
| 206 | |
| 207 | // try to connect the Constant Inputs if there are any |
Mike Kelly | a280650 | 2023-08-03 10:42:11 +0100 | [diff] [blame] | 208 | if (ProcessInputs(activationLayer, delegateData, tfLiteContext, tfLiteNode, nodeIndex) != kTfLiteOk) |
Matthew Sloyan | 0bd4c62 | 2023-04-27 11:48:26 +0100 | [diff] [blame] | 209 | { |
| 210 | return kTfLiteError; |
| 211 | } |
| 212 | |
| 213 | // Connect |
| 214 | return Connect(activationLayer, tfLiteContext, tfLiteNode, delegateData); |
| 215 | } |
| 216 | |
| 217 | } // namespace armnnDelegate |