Sadik Armagan | 62483be | 2020-10-23 17:14:43 +0100 | [diff] [blame] | 1 | // |
Ryan OShea | 3ad2e14 | 2023-01-13 10:19:20 +0000 | [diff] [blame^] | 2 | // Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved. |
Sadik Armagan | 62483be | 2020-10-23 17:14:43 +0100 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #pragma once |
| 7 | |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 8 | #include "DelegateUtils.hpp" |
Ryan OShea | 3ad2e14 | 2023-01-13 10:19:20 +0000 | [diff] [blame^] | 9 | #include "SharedFunctions.hpp" |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 10 | |
Sadik Armagan | 62483be | 2020-10-23 17:14:43 +0100 | [diff] [blame] | 11 | #include <tensorflow/lite/builtin_ops.h> |
| 12 | #include <tensorflow/lite/c/builtin_op_data.h> |
| 13 | #include <tensorflow/lite/c/common.h> |
| 14 | #include <tensorflow/lite/minimal_logging.h> |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 15 | #include "tensorflow/lite/kernels/internal/tensor.h" |
Sadik Armagan | 62483be | 2020-10-23 17:14:43 +0100 | [diff] [blame] | 16 | |
| 17 | namespace armnnDelegate |
| 18 | { |
| 19 | |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 20 | TfLiteStatus VisitConv2dOperator(DelegateData& delegateData, |
| 21 | TfLiteContext* tfLiteContext, |
| 22 | TfLiteNode* tfLiteNode, |
| 23 | int nodeIndex, |
| 24 | int32_t operatorCode) |
| 25 | { |
| 26 | auto numInputs = tfLiteNode->inputs->size; |
| 27 | if (numInputs < 2) |
| 28 | { |
| 29 | TF_LITE_MAYBE_KERNEL_LOG( |
| 30 | tfLiteContext, "TfLiteArmnnDelegate: Minimum number of inputs (%d != %d) in node #%d", |
| 31 | 2, numInputs, nodeIndex); |
| 32 | return kTfLiteError; |
| 33 | } |
| 34 | TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| 35 | |
| 36 | armnn::Convolution2dDescriptor descriptor; |
| 37 | const auto params = reinterpret_cast<TfLiteConvParams*>(tfLiteNode->builtin_data); |
| 38 | |
Mike Kelly | 84d6378 | 2022-05-06 12:14:16 +0100 | [diff] [blame] | 39 | bool biasEnabled = IsOptionalOperandPresent(tfLiteNode, 2); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 40 | descriptor.m_BiasEnabled = biasEnabled; |
| 41 | descriptor.m_StrideX = NonNegative(params->stride_width, nodeIndex); |
| 42 | descriptor.m_StrideY = NonNegative(params->stride_height, nodeIndex); |
| 43 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 44 | descriptor.m_DilationX = NonNegative(params->dilation_width_factor, nodeIndex); |
| 45 | descriptor.m_DilationY = NonNegative(params->dilation_height_factor, nodeIndex); |
| 46 | |
| 47 | const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; |
| 48 | const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]]; |
| 49 | if(!IsValid(&tfLiteTensors[tfLiteNode->inputs->data[0]])) |
| 50 | { |
| 51 | TF_LITE_MAYBE_KERNEL_LOG( |
| 52 | tfLiteContext, |
| 53 | "TfLiteArmnnDelegate: Invalid input tensor in operator #%d node #%d: ", |
| 54 | operatorCode, nodeIndex); |
| 55 | return kTfLiteError; |
| 56 | } |
| 57 | if (IsDynamicTensor(tfLiteInputTensor)) |
| 58 | { |
| 59 | TF_LITE_MAYBE_KERNEL_LOG( |
| 60 | tfLiteContext, |
| 61 | "TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ", |
| 62 | operatorCode, nodeIndex); |
| 63 | return kTfLiteError; |
| 64 | } |
| 65 | const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]]; |
| 66 | if(!IsValid(&tfLiteOutputTensor)) |
| 67 | { |
| 68 | TF_LITE_MAYBE_KERNEL_LOG( |
| 69 | tfLiteContext, |
| 70 | "TfLiteArmnnDelegate: Invalid output tensor in operator #%d node #%d: ", |
| 71 | operatorCode, nodeIndex); |
| 72 | return kTfLiteError; |
| 73 | } |
| 74 | if (IsDynamicTensor(tfLiteOutputTensor)) |
| 75 | { |
| 76 | TF_LITE_MAYBE_KERNEL_LOG( |
| 77 | tfLiteContext, |
| 78 | "TfLiteArmnnDelegate: Dynamic output tensors are not supported in operator #%d node #%d: ", |
| 79 | operatorCode, nodeIndex); |
| 80 | return kTfLiteError; |
| 81 | } |
| 82 | |
| 83 | const TfLiteTensor& tfLiteFilterTensor = tfLiteTensors[tfLiteNode->inputs->data[1]]; |
| 84 | if(!IsValid(&tfLiteFilterTensor)) |
| 85 | { |
| 86 | TF_LITE_MAYBE_KERNEL_LOG( |
| 87 | tfLiteContext, |
| 88 | "TfLiteArmnnDelegate: Invalid filter tensor in operator #%d node #%d: ", |
| 89 | operatorCode, nodeIndex); |
| 90 | return kTfLiteError; |
| 91 | } |
| 92 | if (IsDynamicTensor(tfLiteFilterTensor)) |
| 93 | { |
| 94 | TF_LITE_MAYBE_KERNEL_LOG( |
| 95 | tfLiteContext, |
| 96 | "TfLiteArmnnDelegate: Dynamic filter tensors are not supported in node #%d: ", |
| 97 | nodeIndex); |
| 98 | return kTfLiteError; |
| 99 | } |
| 100 | |
| 101 | const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor); |
Sadik Armagan | 90a119b | 2022-08-05 16:12:49 +0100 | [diff] [blame] | 102 | const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 103 | |
Ryan OShea | 3ad2e14 | 2023-01-13 10:19:20 +0000 | [diff] [blame^] | 104 | auto* tfLiteNodeParameters = reinterpret_cast<TfLiteConvParams*>(tfLiteNode->builtin_data); |
| 105 | TfLiteFusedActivation activationType; |
| 106 | if (tfLiteNodeParameters) |
| 107 | { |
| 108 | activationType = tfLiteNodeParameters->activation; |
| 109 | |
| 110 | const armnn::TensorInfo& activationOutputInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true); |
| 111 | TfLiteStatus activationStatus = ValidateFusedActivationOperator(delegateData, tfLiteContext, outputTensorInfo, |
| 112 | outputTensorInfo, activationType); |
| 113 | if(activationStatus != kTfLiteOk) |
| 114 | { |
| 115 | return kTfLiteError; |
| 116 | } |
| 117 | |
| 118 | } |
| 119 | |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 120 | armnn::TensorInfo filterTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteFilterTensor); |
| 121 | |
| 122 | armnn::TensorInfo biasTensorInfo; |
| 123 | if(biasEnabled) |
| 124 | { |
| 125 | const TfLiteTensor& tfLiteBiasTensor = tfLiteTensors[tfLiteNode->inputs->data[2]]; |
| 126 | if(!IsValid(&tfLiteBiasTensor)) |
| 127 | { |
| 128 | TF_LITE_MAYBE_KERNEL_LOG( |
| 129 | tfLiteContext, |
| 130 | "TfLiteArmnnDelegate: Invalid bias tensor in operator #%d node #%d: ", |
| 131 | operatorCode, nodeIndex); |
| 132 | return kTfLiteError; |
| 133 | } |
| 134 | if (IsDynamicTensor(tfLiteBiasTensor)) |
| 135 | { |
| 136 | TF_LITE_MAYBE_KERNEL_LOG( |
| 137 | tfLiteContext, |
| 138 | "TfLiteArmnnDelegate: Dynamic bias tensors are not supported in node #%d: ", |
| 139 | nodeIndex); |
| 140 | return kTfLiteError; |
| 141 | } |
| 142 | biasTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteBiasTensor); |
| 143 | } |
| 144 | else |
| 145 | { |
| 146 | biasTensorInfo = armnn::TensorInfo(armnn::TensorShape({1}), GetDataType(tfLiteInputTensor)); |
| 147 | } |
| 148 | |
| 149 | armnn::Optional<armnn::TensorInfo> optionalBiasInfo(biasTensorInfo); |
| 150 | |
| 151 | // TfLite uses NHWC tensors |
| 152 | const unsigned int inputHeight = inputTensorInfo.GetShape()[1]; |
| 153 | const unsigned int inputWidth = inputTensorInfo.GetShape()[2]; |
| 154 | |
| 155 | const unsigned int filterHeight = filterTensorInfo.GetShape()[1]; |
| 156 | const unsigned int filterWidth = filterTensorInfo.GetShape()[2]; |
| 157 | |
| 158 | // Calculate padding |
| 159 | CalcPadding(inputHeight, filterHeight, descriptor.m_StrideY, descriptor.m_DilationY, |
| 160 | descriptor.m_PadTop, descriptor.m_PadBottom, params->padding); |
| 161 | CalcPadding(inputWidth, filterWidth, descriptor.m_StrideX, descriptor.m_DilationX, |
| 162 | descriptor.m_PadLeft, descriptor.m_PadRight, params->padding); |
| 163 | |
Cathal Corbett | 5383767 | 2022-09-01 11:34:37 +0100 | [diff] [blame] | 164 | armnn::BackendId setBackend; |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 165 | if (!delegateData.m_Network) |
| 166 | { |
| 167 | bool isSupported = false; |
Sadik Armagan | bfa767c | 2022-02-09 14:58:03 +0000 | [diff] [blame] | 168 | FORWARD_LAYER_SUPPORT_FUNC("CONV2D", |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 169 | tfLiteContext, |
| 170 | IsConvolution2dSupported, |
| 171 | delegateData.m_Backends, |
| 172 | isSupported, |
Cathal Corbett | 5383767 | 2022-09-01 11:34:37 +0100 | [diff] [blame] | 173 | setBackend, |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 174 | inputTensorInfo, |
| 175 | outputTensorInfo, |
| 176 | descriptor, |
| 177 | filterTensorInfo, |
| 178 | optionalBiasInfo); |
| 179 | return isSupported ? kTfLiteOk : kTfLiteError; |
| 180 | } |
| 181 | |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 182 | // Set up filter and biases |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 183 | armnn::IConnectableLayer* layer = delegateData.m_Network->AddConvolution2dLayer(descriptor); |
Cathal Corbett | 5383767 | 2022-09-01 11:34:37 +0100 | [diff] [blame] | 184 | layer->SetBackendId(setBackend); |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 185 | |
Sadik Armagan | 90a119b | 2022-08-05 16:12:49 +0100 | [diff] [blame] | 186 | if(tflite::IsConstantTensor(&tfLiteContext->tensors[tfLiteNode->inputs->data[1]])) |
| 187 | { |
| 188 | auto filter = |
| 189 | CreateConstTensor(&tfLiteContext->tensors[tfLiteNode->inputs->data[1]], |
| 190 | filterTensorInfo, |
| 191 | armnn::Optional<armnn::PermutationVector &>()); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 192 | |
Sadik Armagan | 90a119b | 2022-08-05 16:12:49 +0100 | [diff] [blame] | 193 | armnn::IConnectableLayer *weightsLayer = delegateData.m_Network->AddConstantLayer(filter); |
| 194 | weightsLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(1u)); |
| 195 | weightsLayer->GetOutputSlot(0).SetTensorInfo(filterTensorInfo); |
| 196 | } |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 197 | |
| 198 | if (biasEnabled) |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 199 | { |
Keith Davis | b4dd5cc | 2022-04-07 11:32:00 +0100 | [diff] [blame] | 200 | const TfLiteTensor& tfLiteBiasTensor = tfLiteTensors[tfLiteNode->inputs->data[2]]; |
| 201 | if(tflite::IsConstantTensor(&tfLiteBiasTensor)) |
| 202 | { |
| 203 | auto biasTensor = CreateConstTensor(&tfLiteBiasTensor, biasTensorInfo); |
| 204 | armnn::IConnectableLayer* biasLayer = delegateData.m_Network->AddConstantLayer(biasTensor); |
| 205 | ARMNN_ASSERT(biasLayer != nullptr); |
| 206 | biasLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(2u)); |
| 207 | biasLayer->GetOutputSlot(0).SetTensorInfo(biasTensorInfo); |
| 208 | } |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 209 | } |
| 210 | |
| 211 | ARMNN_ASSERT(layer != nullptr); |
| 212 | |
| 213 | armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); |
| 214 | outputSlot.SetTensorInfo(outputTensorInfo); |
| 215 | |
| 216 | Connect(layer, tfLiteNode, delegateData); |
| 217 | |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 218 | if (!tfLiteNodeParameters) |
| 219 | { |
| 220 | // No Activation |
| 221 | return kTfLiteOk; |
| 222 | } |
Ryan OShea | 3ad2e14 | 2023-01-13 10:19:20 +0000 | [diff] [blame^] | 223 | // Check and Create activation |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 224 | return FusedActivation(tfLiteContext, tfLiteNode, activationType, layer, 0, delegateData); |
| 225 | |
| 226 | } |
| 227 | |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 228 | // Conv3d is only correctly supported for external delegates from TF Lite v2.6, as there was a breaking bug in v2.5. |
| 229 | #if defined(ARMNN_POST_TFLITE_2_5) |
| 230 | TfLiteStatus VisitConv3dOperator(DelegateData& delegateData, |
| 231 | TfLiteContext* tfLiteContext, |
| 232 | TfLiteNode* tfLiteNode, |
| 233 | int nodeIndex, |
| 234 | int32_t operatorCode) |
| 235 | { |
| 236 | auto numInputs = tfLiteNode->inputs->size; |
| 237 | if (numInputs < 2) |
| 238 | { |
| 239 | TF_LITE_MAYBE_KERNEL_LOG( |
| 240 | tfLiteContext, "TfLiteArmnnDelegate: Minimum number of inputs (%d != %d) in node #%d", |
| 241 | 2, numInputs, nodeIndex); |
| 242 | return kTfLiteError; |
| 243 | } |
| 244 | TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| 245 | |
| 246 | armnn::Convolution3dDescriptor descriptor; |
| 247 | const auto params = reinterpret_cast<TfLiteConv3DParams*>(tfLiteNode->builtin_data); |
| 248 | |
Mike Kelly | 84d6378 | 2022-05-06 12:14:16 +0100 | [diff] [blame] | 249 | bool biasEnabled = IsOptionalOperandPresent(tfLiteNode, 2); |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 250 | descriptor.m_BiasEnabled = biasEnabled; |
| 251 | descriptor.m_DataLayout = armnn::DataLayout::NDHWC; |
| 252 | descriptor.m_StrideX = NonNegative(params->stride_width, nodeIndex); |
| 253 | descriptor.m_StrideY = NonNegative(params->stride_height, nodeIndex); |
| 254 | descriptor.m_StrideZ = NonNegative(params->stride_depth, nodeIndex); |
| 255 | descriptor.m_DilationX = NonNegative(params->dilation_width_factor, nodeIndex); |
| 256 | descriptor.m_DilationY = NonNegative(params->dilation_height_factor, nodeIndex); |
| 257 | descriptor.m_DilationZ = NonNegative(params->dilation_depth_factor, nodeIndex); |
| 258 | |
| 259 | const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; |
| 260 | const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]]; |
| 261 | if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex)) |
| 262 | { |
| 263 | return kTfLiteError; |
| 264 | } |
| 265 | |
| 266 | const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]]; |
| 267 | if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex)) |
| 268 | { |
| 269 | return kTfLiteError; |
| 270 | } |
| 271 | |
| 272 | const TfLiteTensor& tfLiteFilterTensor = tfLiteTensors[tfLiteNode->inputs->data[1]]; |
| 273 | if (!IsValid(tfLiteContext, tfLiteFilterTensor, operatorCode, nodeIndex)) |
| 274 | { |
| 275 | return kTfLiteError; |
| 276 | } |
| 277 | |
| 278 | const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor); |
Sadik Armagan | 90a119b | 2022-08-05 16:12:49 +0100 | [diff] [blame] | 279 | const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true); |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 280 | |
Ryan OShea | 3ad2e14 | 2023-01-13 10:19:20 +0000 | [diff] [blame^] | 281 | auto* tfLiteNodeParameters = reinterpret_cast<TfLiteConv3DParams*>(tfLiteNode->builtin_data); |
| 282 | TfLiteFusedActivation activationType; |
| 283 | if (tfLiteNodeParameters) |
| 284 | { |
| 285 | activationType = tfLiteNodeParameters->activation; |
| 286 | |
| 287 | const armnn::TensorInfo& activationOutputInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true); |
| 288 | TfLiteStatus activationStatus = ValidateFusedActivationOperator(delegateData, tfLiteContext, outputTensorInfo, |
| 289 | outputTensorInfo, activationType); |
| 290 | if(activationStatus != kTfLiteOk) |
| 291 | { |
| 292 | return kTfLiteError; |
| 293 | } |
| 294 | |
| 295 | } |
| 296 | |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 297 | armnn::TensorInfo filterTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteFilterTensor); |
| 298 | |
| 299 | armnn::TensorInfo biasTensorInfo; |
| 300 | if(biasEnabled) |
| 301 | { |
| 302 | const TfLiteTensor& tfLiteBiasTensor = tfLiteTensors[tfLiteNode->inputs->data[2]]; |
| 303 | if (!IsValid(tfLiteContext, tfLiteBiasTensor, operatorCode, nodeIndex)) |
| 304 | { |
| 305 | return kTfLiteError; |
| 306 | } |
| 307 | biasTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteBiasTensor); |
| 308 | } |
| 309 | else |
| 310 | { |
| 311 | biasTensorInfo = armnn::TensorInfo(armnn::TensorShape({1}), GetDataType(tfLiteInputTensor)); |
| 312 | } |
| 313 | |
| 314 | armnn::Optional<armnn::TensorInfo> optionalBiasInfo(biasTensorInfo); |
| 315 | |
| 316 | // TfLite uses NDHWC tensors |
| 317 | const unsigned int inputDepth = inputTensorInfo.GetShape()[1]; |
| 318 | const unsigned int inputHeight = inputTensorInfo.GetShape()[2]; |
| 319 | const unsigned int inputWidth = inputTensorInfo.GetShape()[3]; |
| 320 | |
| 321 | // Assuming the filter is DHWIO : Depth, Height, Width, OutputChannels, InputChannels |
| 322 | const unsigned int filterDepth = filterTensorInfo.GetShape()[0]; |
| 323 | const unsigned int filterHeight = filterTensorInfo.GetShape()[1]; |
| 324 | const unsigned int filterWidth = filterTensorInfo.GetShape()[2]; |
| 325 | |
| 326 | // Calculate padding |
| 327 | CalcPadding(inputDepth, filterDepth, descriptor.m_StrideZ, descriptor.m_DilationZ, |
| 328 | descriptor.m_PadFront, descriptor.m_PadBack, params->padding); |
| 329 | CalcPadding(inputHeight, filterHeight, descriptor.m_StrideY, descriptor.m_DilationY, |
| 330 | descriptor.m_PadTop, descriptor.m_PadBottom, params->padding); |
| 331 | CalcPadding(inputWidth, filterWidth, descriptor.m_StrideX, descriptor.m_DilationX, |
| 332 | descriptor.m_PadLeft, descriptor.m_PadRight, params->padding); |
| 333 | |
| 334 | // If the m_Network is a nullptr, this signals that a prerequisite TfLite callback is required to clarify the |
| 335 | // support for the operator |
| 336 | // If supported, VisitConvolutionOperator will be called again to add the layer to the network as seen below. |
Cathal Corbett | 5383767 | 2022-09-01 11:34:37 +0100 | [diff] [blame] | 337 | armnn::BackendId setBackend; |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 338 | if (!delegateData.m_Network) |
| 339 | { |
| 340 | bool isSupported = false; |
Sadik Armagan | bfa767c | 2022-02-09 14:58:03 +0000 | [diff] [blame] | 341 | FORWARD_LAYER_SUPPORT_FUNC("CONV3D", |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 342 | tfLiteContext, |
| 343 | IsConvolution3dSupported, |
| 344 | delegateData.m_Backends, |
| 345 | isSupported, |
Cathal Corbett | 5383767 | 2022-09-01 11:34:37 +0100 | [diff] [blame] | 346 | setBackend, |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 347 | inputTensorInfo, |
| 348 | outputTensorInfo, |
| 349 | descriptor, |
| 350 | filterTensorInfo, |
| 351 | optionalBiasInfo); |
| 352 | return isSupported ? kTfLiteOk : kTfLiteError; |
| 353 | } |
| 354 | |
| 355 | armnn::IConnectableLayer* layer = delegateData.m_Network->AddConvolution3dLayer(descriptor); |
Cathal Corbett | 5383767 | 2022-09-01 11:34:37 +0100 | [diff] [blame] | 356 | layer->SetBackendId(setBackend); |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 357 | ARMNN_ASSERT(layer != nullptr); |
| 358 | |
| 359 | // Add a constant layer for weights and biases if inputs are constant, |
| 360 | // which are connected to the Convolution3d layer as inputs. |
| 361 | if (tflite::IsConstantTensor(&tfLiteFilterTensor)) |
| 362 | { |
| 363 | auto filter = CreateConstTensor(&tfLiteFilterTensor, |
| 364 | filterTensorInfo, |
| 365 | armnn::Optional<armnn::PermutationVector&>()); |
| 366 | |
| 367 | armnn::IConnectableLayer* weightsLayer = delegateData.m_Network->AddConstantLayer(filter); |
| 368 | ARMNN_ASSERT(weightsLayer != nullptr); |
| 369 | |
| 370 | weightsLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(1u)); |
| 371 | weightsLayer->GetOutputSlot(0).SetTensorInfo(filterTensorInfo); |
| 372 | } |
| 373 | |
| 374 | if(biasEnabled) |
| 375 | { |
| 376 | const TfLiteTensor& tfLiteBiasTensor = tfLiteTensors[tfLiteNode->inputs->data[2]]; |
| 377 | if(tflite::IsConstantTensor(&tfLiteBiasTensor)) |
| 378 | { |
| 379 | auto biases = CreateConstTensor(&tfLiteBiasTensor, |
| 380 | biasTensorInfo, |
| 381 | armnn::Optional<armnn::PermutationVector&>()); |
| 382 | |
| 383 | armnn::IConnectableLayer* biasLayer = delegateData.m_Network->AddConstantLayer(biases); |
| 384 | ARMNN_ASSERT(biasLayer != nullptr); |
| 385 | |
| 386 | biasLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(2u)); |
| 387 | biasLayer->GetOutputSlot(0).SetTensorInfo(biasTensorInfo); |
| 388 | } |
| 389 | } |
| 390 | |
| 391 | armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); |
| 392 | outputSlot.SetTensorInfo(outputTensorInfo); |
| 393 | |
| 394 | Connect(layer, tfLiteNode, delegateData); |
| 395 | |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 396 | if (!tfLiteNodeParameters) |
| 397 | { |
| 398 | // No Activation |
| 399 | return kTfLiteOk; |
| 400 | } |
| 401 | |
Ryan OShea | 3ad2e14 | 2023-01-13 10:19:20 +0000 | [diff] [blame^] | 402 | // Check and create activation |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 403 | return FusedActivation(tfLiteContext, tfLiteNode, activationType, layer, 0, delegateData); |
| 404 | } |
| 405 | #endif |
| 406 | |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 407 | TfLiteStatus VisitDepthwiseConv2dOperator(DelegateData& delegateData, |
| 408 | TfLiteContext* tfLiteContext, |
| 409 | TfLiteNode* tfLiteNode, |
| 410 | int nodeIndex, |
| 411 | int32_t operatorCode) |
| 412 | { |
| 413 | auto numInputs = tfLiteNode->inputs->size; |
| 414 | if (numInputs < 2) |
| 415 | { |
| 416 | TF_LITE_MAYBE_KERNEL_LOG( |
| 417 | tfLiteContext, "TfLiteArmnnDelegate: Minimum number of inputs (%d != %d) in node #%d", |
| 418 | 2, numInputs, nodeIndex); |
| 419 | return kTfLiteError; |
| 420 | } |
| 421 | TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| 422 | |
Mike Kelly | 84d6378 | 2022-05-06 12:14:16 +0100 | [diff] [blame] | 423 | bool biasEnabled = IsOptionalOperandPresent(tfLiteNode, 2); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 424 | |
| 425 | armnn::DepthwiseConvolution2dDescriptor descriptor; |
| 426 | const auto params = reinterpret_cast<TfLiteDepthwiseConvParams*>(tfLiteNode->builtin_data); |
| 427 | |
| 428 | descriptor.m_BiasEnabled = biasEnabled; |
| 429 | descriptor.m_StrideX = NonNegative(params->stride_width, nodeIndex); |
| 430 | descriptor.m_StrideY = NonNegative(params->stride_height, nodeIndex); |
| 431 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 432 | descriptor.m_DilationX = NonNegative(params->dilation_width_factor, nodeIndex); |
| 433 | descriptor.m_DilationY = NonNegative(params->dilation_height_factor, nodeIndex); |
| 434 | |
| 435 | const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; |
| 436 | const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]]; |
| 437 | if(!IsValid(&tfLiteInputTensor)) |
| 438 | { |
| 439 | TF_LITE_MAYBE_KERNEL_LOG( |
| 440 | tfLiteContext, |
| 441 | "TfLiteArmnnDelegate: Invalid input tensor in operator #%d node #%d: ", |
| 442 | operatorCode, nodeIndex); |
| 443 | return kTfLiteError; |
| 444 | } |
| 445 | if (IsDynamicTensor(tfLiteInputTensor)) |
| 446 | { |
| 447 | TF_LITE_MAYBE_KERNEL_LOG( |
| 448 | tfLiteContext, |
| 449 | "TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ", |
| 450 | operatorCode, nodeIndex); |
| 451 | return kTfLiteError; |
| 452 | } |
| 453 | const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]]; |
| 454 | if(!IsValid(&tfLiteOutputTensor)) |
| 455 | { |
| 456 | TF_LITE_MAYBE_KERNEL_LOG( |
| 457 | tfLiteContext, |
| 458 | "TfLiteArmnnDelegate: Invalid output tensor in operator #%d node #%d: ", |
| 459 | operatorCode, nodeIndex); |
| 460 | return kTfLiteError; |
| 461 | } |
| 462 | if (IsDynamicTensor(tfLiteOutputTensor)) |
| 463 | { |
| 464 | TF_LITE_MAYBE_KERNEL_LOG( |
| 465 | tfLiteContext, |
| 466 | "TfLiteArmnnDelegate: Dynamic output tensors are not supported in operator #%d node #%d: ", |
| 467 | operatorCode, nodeIndex); |
| 468 | return kTfLiteError; |
| 469 | } |
| 470 | |
| 471 | const TfLiteTensor& tfLiteFilterTensor = tfLiteTensors[tfLiteNode->inputs->data[1]]; |
| 472 | if(!IsValid(&tfLiteFilterTensor)) |
| 473 | { |
| 474 | TF_LITE_MAYBE_KERNEL_LOG( |
| 475 | tfLiteContext, |
| 476 | "TfLiteArmnnDelegate: Invalid filter tensor in operator #%d node #%d: ", |
| 477 | operatorCode, nodeIndex); |
| 478 | return kTfLiteError; |
| 479 | } |
| 480 | if (IsDynamicTensor(tfLiteFilterTensor)) |
| 481 | { |
| 482 | TF_LITE_MAYBE_KERNEL_LOG( |
| 483 | tfLiteContext, |
| 484 | "TfLiteArmnnDelegate: Dynamic filter tensors are not supported in node #%d: ", |
| 485 | nodeIndex); |
| 486 | return kTfLiteError; |
| 487 | } |
| 488 | |
| 489 | const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor); |
Sadik Armagan | 90a119b | 2022-08-05 16:12:49 +0100 | [diff] [blame] | 490 | const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 491 | |
Ryan OShea | 3ad2e14 | 2023-01-13 10:19:20 +0000 | [diff] [blame^] | 492 | auto* tfLiteNodeParameters = reinterpret_cast<TfLiteDepthwiseConvParams *>(tfLiteNode->builtin_data); |
| 493 | TfLiteFusedActivation activationType; |
| 494 | if (tfLiteNodeParameters) |
| 495 | { |
| 496 | activationType = tfLiteNodeParameters->activation; |
| 497 | |
| 498 | const armnn::TensorInfo& activationOutputInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true); |
| 499 | TfLiteStatus activationStatus = ValidateFusedActivationOperator(delegateData, tfLiteContext, outputTensorInfo, |
| 500 | outputTensorInfo, activationType); |
| 501 | if(activationStatus != kTfLiteOk) |
| 502 | { |
| 503 | return kTfLiteError; |
| 504 | } |
| 505 | |
| 506 | } |
| 507 | |
Jan Eilers | 7612bd6 | 2021-04-06 17:29:03 +0100 | [diff] [blame] | 508 | armnn::TensorInfo filterTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteFilterTensor); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 509 | |
| 510 | // Assuming input is NHWC |
| 511 | unsigned int inputHeight = inputTensorInfo.GetShape()[1]; |
| 512 | unsigned int inputWidth = inputTensorInfo.GetShape()[2]; |
| 513 | |
| 514 | // TensorflowLite weights come in the format [1, H, W, I * M] |
| 515 | unsigned int filterHeight = filterTensorInfo.GetShape()[1]; |
| 516 | unsigned int filterWidth = filterTensorInfo.GetShape()[2]; |
| 517 | |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 518 | // Calculate padding |
| 519 | CalcPadding(inputHeight, filterHeight, descriptor.m_StrideY, descriptor.m_DilationY, |
| 520 | descriptor.m_PadTop, descriptor.m_PadBottom, params->padding); |
| 521 | CalcPadding(inputWidth, filterWidth, descriptor.m_StrideX, descriptor.m_DilationX, |
| 522 | descriptor.m_PadLeft, descriptor.m_PadRight, params->padding); |
| 523 | |
| 524 | armnn::TensorInfo biasTensorInfo; |
| 525 | if(biasEnabled) |
| 526 | { |
| 527 | const TfLiteTensor& tfLiteBiasTensor = tfLiteTensors[tfLiteNode->inputs->data[2]]; |
| 528 | if(!IsValid(&tfLiteBiasTensor)) |
| 529 | { |
| 530 | TF_LITE_MAYBE_KERNEL_LOG( |
| 531 | tfLiteContext, |
| 532 | "TfLiteArmnnDelegate: Invalid bias tensor in operator #%d node #%d: ", |
| 533 | operatorCode, nodeIndex); |
| 534 | return kTfLiteError; |
| 535 | } |
| 536 | if (IsDynamicTensor(tfLiteBiasTensor)) |
| 537 | { |
| 538 | TF_LITE_MAYBE_KERNEL_LOG( |
| 539 | tfLiteContext, |
| 540 | "TfLiteArmnnDelegate: Dynamic bias tensors are not supported in node #%d: ", |
| 541 | nodeIndex); |
| 542 | return kTfLiteError; |
| 543 | } |
| 544 | biasTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteBiasTensor); |
| 545 | } |
| 546 | else |
| 547 | { |
| 548 | biasTensorInfo = armnn::TensorInfo(armnn::TensorShape({1}), GetDataType(tfLiteInputTensor)); |
| 549 | } |
| 550 | |
Cathal Corbett | 5383767 | 2022-09-01 11:34:37 +0100 | [diff] [blame] | 551 | armnn::BackendId setBackend; |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 552 | if (!delegateData.m_Network) |
| 553 | { |
| 554 | bool isSupported = false; |
Sadik Armagan | bfa767c | 2022-02-09 14:58:03 +0000 | [diff] [blame] | 555 | FORWARD_LAYER_SUPPORT_FUNC("DEPTHWISE_CONV2D", |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 556 | tfLiteContext, |
| 557 | IsDepthwiseConvolutionSupported, |
| 558 | delegateData.m_Backends, |
| 559 | isSupported, |
Cathal Corbett | 5383767 | 2022-09-01 11:34:37 +0100 | [diff] [blame] | 560 | setBackend, |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 561 | inputTensorInfo, |
| 562 | outputTensorInfo, |
| 563 | descriptor, |
Sadik Armagan | 90a119b | 2022-08-05 16:12:49 +0100 | [diff] [blame] | 564 | filterTensorInfo, |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 565 | armnn::Optional<armnn::TensorInfo>(biasTensorInfo)); |
| 566 | return isSupported ? kTfLiteOk : kTfLiteError; |
| 567 | } |
| 568 | |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 569 | armnn::IConnectableLayer* layer = delegateData.m_Network->AddDepthwiseConvolution2dLayer(descriptor); |
Cathal Corbett | 5383767 | 2022-09-01 11:34:37 +0100 | [diff] [blame] | 570 | layer->SetBackendId(setBackend); |
Narumol Prangnawarat | 1672542 | 2020-11-20 16:17:48 +0000 | [diff] [blame] | 571 | |
Sadik Armagan | 90a119b | 2022-08-05 16:12:49 +0100 | [diff] [blame] | 572 | if(tflite::IsConstantTensor(&tfLiteFilterTensor)) |
| 573 | { |
| 574 | // For depthwise the weights layout is the same as for tflite [1, H, W, I*M]. No permutation required. |
| 575 | auto filter = CreateConstTensor(&tfLiteFilterTensor, filterTensorInfo); |
| 576 | |
| 577 | armnn::IConnectableLayer* weightsLayer = delegateData.m_Network->AddConstantLayer(filter); |
| 578 | weightsLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(1u)); |
| 579 | weightsLayer->GetOutputSlot(0).SetTensorInfo(filterTensorInfo); |
| 580 | } |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 581 | |
| 582 | if (biasEnabled) |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 583 | { |
Cathal Corbett | 0690265 | 2022-04-14 17:55:11 +0100 | [diff] [blame] | 584 | const TfLiteTensor& tfLiteBiasTensor = tfLiteTensors[tfLiteNode->inputs->data[2]]; |
| 585 | if(tflite::IsConstantTensor(&tfLiteBiasTensor)) |
| 586 | { |
| 587 | auto biasTensor = CreateConstTensor(&tfLiteBiasTensor, biasTensorInfo); |
| 588 | armnn::IConnectableLayer* biasLayer = delegateData.m_Network->AddConstantLayer(biasTensor); |
| 589 | ARMNN_ASSERT(biasLayer != nullptr); |
| 590 | biasLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(2u)); |
| 591 | biasLayer->GetOutputSlot(0).SetTensorInfo(biasTensorInfo); |
| 592 | } |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 593 | } |
| 594 | |
| 595 | ARMNN_ASSERT(layer != nullptr); |
| 596 | |
| 597 | armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); |
| 598 | outputSlot.SetTensorInfo(outputTensorInfo); |
| 599 | |
| 600 | Connect(layer, tfLiteNode, delegateData); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 601 | if (!tfLiteNodeParameters) |
| 602 | { |
| 603 | // No Activation |
| 604 | return kTfLiteOk; |
| 605 | } |
Ryan OShea | 3ad2e14 | 2023-01-13 10:19:20 +0000 | [diff] [blame^] | 606 | // Check and create activation |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 607 | return FusedActivation(tfLiteContext, tfLiteNode, activationType, layer, 0, delegateData); |
| 608 | } |
| 609 | |
| 610 | TfLiteStatus VisitTransposeConv2dOperator(DelegateData& delegateData, |
| 611 | TfLiteContext* tfLiteContext, |
| 612 | TfLiteNode* tfLiteNode, |
| 613 | int nodeIndex, |
| 614 | int32_t operatorCode) |
| 615 | { |
| 616 | TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 3, nodeIndex)); |
| 617 | TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| 618 | |
| 619 | armnn::TransposeConvolution2dDescriptor descriptor; |
| 620 | auto* parameters = reinterpret_cast<TfLiteTransposeConvParams*>(tfLiteNode->builtin_data); |
| 621 | descriptor.m_BiasEnabled = false; |
| 622 | descriptor.m_StrideX = NonNegative(parameters->stride_width, nodeIndex); |
| 623 | descriptor.m_StrideY = NonNegative(parameters->stride_height, nodeIndex); |
| 624 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 625 | |
| 626 | const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; |
| 627 | const TfLiteTensor& tfLiteOutputShapeTensor = tfLiteTensors[tfLiteNode->inputs->data[0]]; |
| 628 | if(!IsValid(&tfLiteOutputShapeTensor)) |
| 629 | { |
| 630 | TF_LITE_MAYBE_KERNEL_LOG( |
| 631 | tfLiteContext, |
| 632 | "TfLiteArmnnDelegate: Invalid input tensor in operator #%d node #%d: ", |
| 633 | operatorCode, nodeIndex); |
| 634 | return kTfLiteError; |
| 635 | } |
| 636 | if (IsDynamicTensor(tfLiteOutputShapeTensor)) |
| 637 | { |
| 638 | TF_LITE_MAYBE_KERNEL_LOG( |
| 639 | tfLiteContext, |
| 640 | "TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ", |
| 641 | operatorCode, nodeIndex); |
| 642 | return kTfLiteError; |
| 643 | } |
| 644 | |
| 645 | armnn::TensorInfo tensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputShapeTensor); |
| 646 | std::vector<int32_t> outputShape(tensorInfo.GetNumElements()); |
| 647 | if (tensorInfo.GetDataType() == armnn::DataType::Signed32) |
| 648 | { |
| 649 | for(unsigned int i=0; i < tensorInfo.GetNumElements(); i++) |
| 650 | { |
| 651 | outputShape[i] = ::tflite::GetTensorData<int32_t>(&tfLiteOutputShapeTensor)[i]; |
| 652 | } |
| 653 | } |
| 654 | |
| 655 | if (tensorInfo.GetDataType() == armnn::DataType::QAsymmU8) |
| 656 | { |
| 657 | for(unsigned int i=0; i < tensorInfo.GetNumElements(); i++) |
| 658 | { |
| 659 | outputShape[i] = ::tflite::GetTensorData<uint8_t>(&tfLiteOutputShapeTensor)[i]; |
| 660 | } |
| 661 | } |
| 662 | // Change from signed to unsigned int to store in TransposeConvolution2dDescriptor. |
| 663 | for (int dimension : outputShape) |
| 664 | { |
| 665 | descriptor.m_OutputShape.push_back(static_cast<unsigned int>(dimension)); |
| 666 | } |
| 667 | descriptor.m_OutputShapeEnabled = true; |
| 668 | |
| 669 | const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[2]]; |
| 670 | if(!IsValid(&tfLiteInputTensor)) |
| 671 | { |
| 672 | TF_LITE_MAYBE_KERNEL_LOG( |
| 673 | tfLiteContext, |
| 674 | "TfLiteArmnnDelegate: Invalid input tensor in operator #%d node #%d: ", |
| 675 | operatorCode, nodeIndex); |
| 676 | return kTfLiteError; |
| 677 | } |
| 678 | if (IsDynamicTensor(tfLiteInputTensor)) |
| 679 | { |
| 680 | TF_LITE_MAYBE_KERNEL_LOG( |
| 681 | tfLiteContext, |
| 682 | "TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ", |
| 683 | operatorCode, nodeIndex); |
| 684 | return kTfLiteError; |
| 685 | } |
| 686 | |
| 687 | const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]]; |
| 688 | if(!IsValid(&tfLiteOutputTensor)) |
| 689 | { |
| 690 | TF_LITE_MAYBE_KERNEL_LOG( |
| 691 | tfLiteContext, |
| 692 | "TfLiteArmnnDelegate: Invalid output tensor in operator #%d node #%d: ", |
| 693 | operatorCode, nodeIndex); |
| 694 | return kTfLiteError; |
| 695 | } |
| 696 | if (IsDynamicTensor(tfLiteOutputTensor)) |
| 697 | { |
| 698 | TF_LITE_MAYBE_KERNEL_LOG( |
| 699 | tfLiteContext, |
| 700 | "TfLiteArmnnDelegate: Dynamic output tensors are not supported in operator #%d node #%d: ", |
| 701 | operatorCode, nodeIndex); |
| 702 | return kTfLiteError; |
| 703 | } |
| 704 | |
| 705 | const TfLiteTensor& tfLiteFilterTensor = tfLiteTensors[tfLiteNode->inputs->data[1]]; |
| 706 | if(!IsValid(&tfLiteFilterTensor)) |
| 707 | { |
| 708 | TF_LITE_MAYBE_KERNEL_LOG( |
| 709 | tfLiteContext, |
| 710 | "TfLiteArmnnDelegate: Invalid filter tensor in operator #%d node #%d: ", |
| 711 | operatorCode, nodeIndex); |
| 712 | return kTfLiteError; |
| 713 | } |
| 714 | if (IsDynamicTensor(tfLiteFilterTensor)) |
| 715 | { |
| 716 | TF_LITE_MAYBE_KERNEL_LOG( |
| 717 | tfLiteContext, |
| 718 | "TfLiteArmnnDelegate: Dynamic filter tensors are not supported in operator #%d node #%d: ", |
| 719 | operatorCode, nodeIndex); |
| 720 | return kTfLiteError; |
| 721 | } |
| 722 | |
| 723 | const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor); |
Sadik Armagan | 90a119b | 2022-08-05 16:12:49 +0100 | [diff] [blame] | 724 | const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 725 | armnn::TensorInfo filterTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteFilterTensor); |
| 726 | |
| 727 | // TfLite uses NHWC tensors |
| 728 | const unsigned int inputHeight = inputTensorInfo.GetShape()[1]; |
| 729 | const unsigned int inputWidth = inputTensorInfo.GetShape()[2]; |
| 730 | |
| 731 | const unsigned int filterHeight = filterTensorInfo.GetShape()[1]; |
| 732 | const unsigned int filterWidth = filterTensorInfo.GetShape()[2]; |
| 733 | |
| 734 | // Calculate padding |
| 735 | CalcPadding(inputHeight, |
| 736 | filterHeight, |
| 737 | descriptor.m_StrideY, |
| 738 | 1, // dilation y |
| 739 | descriptor.m_PadTop, |
| 740 | descriptor.m_PadBottom, |
| 741 | parameters->padding); |
| 742 | CalcPadding(inputWidth, |
| 743 | filterWidth, |
| 744 | descriptor.m_StrideX, |
| 745 | 1, // dilation x |
| 746 | descriptor.m_PadLeft, |
| 747 | descriptor.m_PadRight, |
| 748 | parameters->padding); |
| 749 | |
| 750 | // Set up filter |
| 751 | auto filterTensor = CreateConstTensor(&tfLiteFilterTensor, |
| 752 | filterTensorInfo, |
| 753 | armnn::Optional<armnn::PermutationVector&>()); |
Cathal Corbett | 5383767 | 2022-09-01 11:34:37 +0100 | [diff] [blame] | 754 | armnn::BackendId setBackend; |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 755 | if (!delegateData.m_Network) |
| 756 | { |
| 757 | bool isSupported = false; |
Sadik Armagan | bfa767c | 2022-02-09 14:58:03 +0000 | [diff] [blame] | 758 | FORWARD_LAYER_SUPPORT_FUNC("TRANSPOSE_CONV2D", |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 759 | tfLiteContext, |
| 760 | IsTransposeConvolution2dSupported, |
| 761 | delegateData.m_Backends, |
| 762 | isSupported, |
Cathal Corbett | 5383767 | 2022-09-01 11:34:37 +0100 | [diff] [blame] | 763 | setBackend, |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 764 | inputTensorInfo, |
| 765 | outputTensorInfo, |
| 766 | descriptor, |
| 767 | filterTensorInfo, |
| 768 | armnn::EmptyOptional()); |
| 769 | return isSupported ? kTfLiteOk : kTfLiteError; |
| 770 | } |
| 771 | |
| 772 | armnn::IConnectableLayer* layer = delegateData.m_Network->AddTransposeConvolution2dLayer(descriptor, |
| 773 | filterTensor, |
| 774 | armnn::EmptyOptional()); |
Cathal Corbett | 5383767 | 2022-09-01 11:34:37 +0100 | [diff] [blame] | 775 | layer->SetBackendId(setBackend); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 776 | ARMNN_ASSERT(layer != nullptr); |
| 777 | |
| 778 | armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); |
| 779 | outputSlot.SetTensorInfo(outputTensorInfo); |
| 780 | |
| 781 | // Connect |
Keith Davis | 892fafe | 2020-11-26 17:40:35 +0000 | [diff] [blame] | 782 | if (delegateData.m_OutputSlotForNode[static_cast<unsigned int>(tfLiteNode->inputs->data[2])] != nullptr) |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 783 | { |
Keith Davis | 892fafe | 2020-11-26 17:40:35 +0000 | [diff] [blame] | 784 | delegateData.m_OutputSlotForNode[static_cast<unsigned int>(tfLiteNode->inputs->data[2])]-> |
| 785 | Connect(layer->GetInputSlot(0)); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 786 | } |
| 787 | |
| 788 | // Prepare output slots |
| 789 | for (unsigned int outputIndex = 0; outputIndex < layer->GetNumOutputSlots(); ++outputIndex) |
| 790 | { |
| 791 | armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(outputIndex); |
Keith Davis | 892fafe | 2020-11-26 17:40:35 +0000 | [diff] [blame] | 792 | delegateData.m_OutputSlotForNode[static_cast<unsigned int>(tfLiteNode->outputs->data[outputIndex])] = |
| 793 | &outputSlot; |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 794 | } |
| 795 | return kTfLiteOk; |
| 796 | } |
| 797 | |
Sadik Armagan | 62483be | 2020-10-23 17:14:43 +0100 | [diff] [blame] | 798 | TfLiteStatus VisitConvolutionOperator(DelegateData& delegateData, |
| 799 | TfLiteContext* tfLiteContext, |
| 800 | TfLiteNode* tfLiteNode, |
| 801 | int nodeIndex, |
| 802 | int32_t operatorCode) |
| 803 | { |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 804 | switch(operatorCode) |
| 805 | { |
| 806 | case kTfLiteBuiltinConv2d: |
| 807 | return VisitConv2dOperator(delegateData, tfLiteContext, tfLiteNode, nodeIndex, operatorCode); |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 808 | // Conv3d is only correctly supported for external delegates from TF Lite v2.6, as there was a breaking bug in v2.5. |
| 809 | #if defined(ARMNN_POST_TFLITE_2_5) |
| 810 | case kTfLiteBuiltinConv3d: |
| 811 | return VisitConv3dOperator(delegateData, tfLiteContext, tfLiteNode, nodeIndex, operatorCode); |
| 812 | #endif |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 813 | case kTfLiteBuiltinDepthwiseConv2d: |
| 814 | return VisitDepthwiseConv2dOperator(delegateData, tfLiteContext, tfLiteNode, nodeIndex, operatorCode); |
| 815 | case kTfLiteBuiltinTransposeConv: |
| 816 | return VisitTransposeConv2dOperator(delegateData, tfLiteContext, tfLiteNode, nodeIndex, operatorCode); |
| 817 | default: |
| 818 | return kTfLiteError; |
| 819 | } |
Sadik Armagan | 62483be | 2020-10-23 17:14:43 +0100 | [diff] [blame] | 820 | } |
| 821 | |
| 822 | } // namespace armnnDelegate |