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 | // |
Ryan OShea | a37ccb0 | 2023-04-11 10:54:07 +0100 | [diff] [blame] | 5 | #pragma once |
| 6 | |
Matthew Sloyan | c49aacc | 2023-04-28 17:27:26 +0100 | [diff] [blame^] | 7 | #include <OpaqueDelegateUtils.hpp> |
Ryan OShea | a37ccb0 | 2023-04-11 10:54:07 +0100 | [diff] [blame] | 8 | |
| 9 | namespace armnnOpaqueDelegate |
| 10 | { |
| 11 | |
| 12 | TfLiteStatus VisitCastOperator(DelegateData& delegateData, |
| 13 | TfLiteOpaqueContext* tfLiteContext, |
| 14 | TfLiteOpaqueNode* tfLiteNode, |
| 15 | int nodeIndex, |
| 16 | int32_t operatorCode) |
| 17 | { |
| 18 | TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| 19 | TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| 20 | int numInputs = 0; |
| 21 | const int* inputTensors; |
| 22 | if (TfLiteOpaqueNodeInputs(tfLiteNode, &inputTensors, &numInputs) != kTfLiteOk) |
| 23 | { |
| 24 | return kTfLiteError; |
| 25 | } |
| 26 | |
| 27 | // This layer only has 1 input, so we can directly assign tensor[0] to a new opaque tensor |
| 28 | const TfLiteOpaqueTensor* |
| 29 | tfLiteInputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[numInputs-1]); |
| 30 | if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex)) |
| 31 | { |
| 32 | return kTfLiteError; |
| 33 | } |
| 34 | |
| 35 | int numOutputs = 0; |
| 36 | const int* outputTensors; |
| 37 | if (TfLiteOpaqueNodeOutputs(tfLiteNode, &outputTensors, &numOutputs) != kTfLiteOk) |
| 38 | { |
| 39 | return kTfLiteError; |
| 40 | } |
| 41 | |
| 42 | // This layer only has 1 output, so we can directly assign tensor[0] to a new opaque tensor |
| 43 | const TfLiteOpaqueTensor* |
| 44 | tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[numOutputs-1]); |
| 45 | if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex)) |
| 46 | { |
| 47 | return kTfLiteError; |
| 48 | } |
| 49 | |
| 50 | const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor); |
| 51 | const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true); |
| 52 | |
| 53 | bool isSupported = false; |
| 54 | armnn::BackendId setBackend; |
| 55 | auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported) { |
| 56 | FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("CAST", |
Matthew Sloyan | c49aacc | 2023-04-28 17:27:26 +0100 | [diff] [blame^] | 57 | tfLiteContext, |
| 58 | IsCastSupported, |
| 59 | delegateData.m_Backends, |
| 60 | isSupported, |
| 61 | setBackend, |
| 62 | inputTensorInfo, |
| 63 | outInfo); |
Ryan OShea | a37ccb0 | 2023-04-11 10:54:07 +0100 | [diff] [blame] | 64 | }; |
| 65 | |
| 66 | // If the m_Network is a nullptr, this signals that a prerequisite TfLite callback is required to clarify the |
| 67 | // support for the operator |
| 68 | // If supported, VisitCastOperator will be called again to add the layer to the network as seen further below |
| 69 | if (!delegateData.m_Network) |
| 70 | { |
| 71 | validateFunc(outputTensorInfo, isSupported); |
| 72 | return isSupported ? kTfLiteOk : kTfLiteError; |
| 73 | } |
| 74 | |
| 75 | // Add a Cast layer |
| 76 | armnn::IConnectableLayer* layer = delegateData.m_Network->AddCastLayer(); |
| 77 | layer->SetBackendId(setBackend); |
| 78 | ARMNN_ASSERT(layer != nullptr); |
| 79 | |
| 80 | armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); |
| 81 | outputSlot.SetTensorInfo(outputTensorInfo); |
| 82 | |
| 83 | // try to connect the Constant Inputs if there are any |
| 84 | if (ProcessInputs(layer, delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk) |
| 85 | { |
| 86 | return kTfLiteError; |
| 87 | } |
| 88 | |
| 89 | // Connect |
| 90 | return Connect(layer, tfLiteContext, tfLiteNode, delegateData); |
| 91 | } |
Matthew Sloyan | c49aacc | 2023-04-28 17:27:26 +0100 | [diff] [blame^] | 92 | |
| 93 | TfLiteStatus VisitReshapeOperator(DelegateData& delegateData, |
| 94 | TfLiteOpaqueContext* tfLiteContext, |
| 95 | TfLiteOpaqueNode* tfLiteNode, |
| 96 | int nodeIndex, |
| 97 | int32_t operatorCode) |
| 98 | { |
| 99 | auto numInputs = TfLiteOpaqueNodeNumberOfInputs(tfLiteNode); |
| 100 | |
| 101 | if (numInputs == 2) |
| 102 | { |
| 103 | TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex)); |
| 104 | } |
| 105 | else |
| 106 | { |
| 107 | TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| 108 | } |
| 109 | TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| 110 | |
| 111 | // Gather input indices and use to get input tensor. |
| 112 | const int* inputTensors; |
| 113 | if (TfLiteOpaqueNodeInputs(tfLiteNode, &inputTensors, &numInputs) != kTfLiteOk) |
| 114 | { |
| 115 | TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| 116 | tfLiteContext, |
| 117 | "TfLiteArmnnOpaqueDelegate: Unable to gather input tensor indices from node #%d: ", |
| 118 | nodeIndex); |
| 119 | return kTfLiteError; |
| 120 | } |
| 121 | |
| 122 | const TfLiteOpaqueTensor* tfLiteInputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]); |
| 123 | if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex)) |
| 124 | { |
| 125 | return kTfLiteError; |
| 126 | } |
| 127 | |
| 128 | // Gather output indices and use to get output tensors. |
| 129 | int numOutputs = 0; |
| 130 | const int* outputTensors; |
| 131 | if (TfLiteOpaqueNodeOutputs(tfLiteNode, &outputTensors, &numOutputs) != kTfLiteOk) |
| 132 | { |
| 133 | TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| 134 | tfLiteContext, |
| 135 | "TfLiteArmnnOpaqueDelegate: Unable to gather output tensor indices from node #%d: ", |
| 136 | nodeIndex); |
| 137 | return kTfLiteError; |
| 138 | } |
| 139 | |
| 140 | const TfLiteOpaqueTensor* tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]); |
| 141 | if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex)) |
| 142 | { |
| 143 | return kTfLiteError; |
| 144 | } |
| 145 | |
| 146 | const armnn::TensorInfo& inputTensorInfo0 = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor); |
| 147 | const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true); |
| 148 | |
| 149 | armnn::ReshapeDescriptor reshapeDesc; |
| 150 | std::vector<int32_t> targetShape; |
| 151 | |
| 152 | auto* reshapeOptions = reinterpret_cast<TfLiteReshapeParams*>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode)); |
| 153 | |
| 154 | // The new shape can be defined by either a second input tensor or by a builtin option, we need to check for both. |
| 155 | // Options might be set without valid data. we need to check the dimensions are in a valid range. |
| 156 | if (reshapeOptions && reshapeOptions->num_dimensions > 0 && reshapeOptions->num_dimensions <= 8) |
| 157 | { |
| 158 | for (int i = 0; i < reshapeOptions->num_dimensions; ++i) |
| 159 | { |
| 160 | targetShape.push_back(reshapeOptions->shape[i]); |
| 161 | } |
| 162 | } |
| 163 | else if (numInputs == 2) |
| 164 | { |
| 165 | // Get shape from the second input tensor |
| 166 | const TfLiteOpaqueTensor* tfLiteShapeInputTensor = |
| 167 | TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[1]); |
| 168 | if (!IsValid(tfLiteContext, tfLiteShapeInputTensor, operatorCode, nodeIndex)) |
| 169 | { |
| 170 | return kTfLiteError; |
| 171 | } |
| 172 | |
| 173 | int32_t numDims = TfLiteOpaqueTensorNumDims(tfLiteShapeInputTensor); |
| 174 | if (numDims != 1) |
| 175 | { |
| 176 | TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| 177 | tfLiteContext, |
| 178 | "TfLiteArmnnOpaqueDelegate: Target 'shape' input is not a 1D tensor in " |
| 179 | "operator #%d node #%d: Falling back to TfLiteOptions.", |
| 180 | operatorCode, nodeIndex); |
| 181 | } |
| 182 | else |
| 183 | { |
| 184 | // Get the shape data out of the input tensor |
| 185 | auto* shapeTensorDataPtr = static_cast<int32_t*>(TfLiteOpaqueTensorData(tfLiteShapeInputTensor)); |
| 186 | int32_t shapeTensorNumValues = TfLiteOpaqueTensorDim(tfLiteShapeInputTensor, 0); |
| 187 | for (int32_t i = 0; i < shapeTensorNumValues; ++i) |
| 188 | { |
| 189 | targetShape.push_back(shapeTensorDataPtr[i]); |
| 190 | } |
| 191 | } |
| 192 | } |
| 193 | else |
| 194 | { |
| 195 | TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| 196 | tfLiteContext, |
| 197 | "TfLiteArmnnOpaqueDelegate: Target shape not defined in reshape parameters or input tensor. " |
| 198 | "At least one method required in operator #%d node #%d: ", |
| 199 | operatorCode, nodeIndex); |
| 200 | return kTfLiteError; |
| 201 | } |
| 202 | |
| 203 | // Use the data to create the required tensor shape. |
| 204 | if (CreateOutputTensorShape(inputTensorInfo0, targetShape, reshapeDesc) != kTfLiteOk) |
| 205 | { |
| 206 | TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| 207 | tfLiteContext, |
| 208 | "TfLiteArmnnOpaqueDelegate: At most one component of shape can be -1 in: " |
| 209 | "operator #%d node #%d: ", |
| 210 | operatorCode, nodeIndex); |
| 211 | return kTfLiteError; |
| 212 | } |
| 213 | |
| 214 | if (reshapeDesc.m_TargetShape.GetNumElements() != inputTensorInfo0.GetNumElements()) |
| 215 | { |
| 216 | TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| 217 | tfLiteContext, |
| 218 | "TfLiteArmnnOpaqueDelegate: Reshape, number of elements in output shape does not match input " |
| 219 | "operator #%d node #%d: ", |
| 220 | operatorCode, nodeIndex); |
| 221 | return kTfLiteError; |
| 222 | } |
| 223 | |
| 224 | bool isSupported = false; |
| 225 | armnn::BackendId setBackend; |
| 226 | auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported) |
| 227 | { |
| 228 | FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("RESHAPE", |
| 229 | tfLiteContext, |
| 230 | IsReshapeSupported, |
| 231 | delegateData.m_Backends, |
| 232 | isSupported, |
| 233 | setBackend, |
| 234 | inputTensorInfo0, |
| 235 | outInfo, |
| 236 | reshapeDesc); |
| 237 | }; |
| 238 | |
| 239 | if (!delegateData.m_Network) |
| 240 | { |
| 241 | validateFunc(outputTensorInfo, isSupported); |
| 242 | return isSupported ? kTfLiteOk : kTfLiteError; |
| 243 | } |
| 244 | |
| 245 | armnn::IConnectableLayer* layer = delegateData.m_Network->AddReshapeLayer(reshapeDesc); |
| 246 | layer->SetBackendId(setBackend); |
| 247 | ARMNN_ASSERT(layer != nullptr); |
| 248 | |
| 249 | armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); |
| 250 | outputSlot.SetTensorInfo(outputTensorInfo); |
| 251 | |
| 252 | // try to connect the Constant Inputs if there are any |
| 253 | if(ProcessInputs(layer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk ) |
| 254 | { |
| 255 | return kTfLiteError; |
| 256 | } |
| 257 | |
| 258 | // Connect |
| 259 | return Connect(layer, tfLiteContext, tfLiteNode, delegateData); |
| 260 | } |
| 261 | |
Ryan OShea | a37ccb0 | 2023-04-11 10:54:07 +0100 | [diff] [blame] | 262 | } |