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author | Narumol Prangnawarat <narumol.prangnawarat@arm.com> | 2020-12-17 12:17:58 +0000 |
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committer | Jim Flynn <jim.flynn@arm.com> | 2020-12-17 15:39:37 +0000 |
commit | 958024be8f5c54f6e2a2930d40da62fda451bba7 (patch) | |
tree | bf9cc93592a3a3fd9ca15d8a85edfda8204e67cf /delegate/src/Pad.hpp | |
parent | 019840d1161738aefd6ebd32ccf4e72e618cae15 (diff) | |
download | armnn-958024be8f5c54f6e2a2930d40da62fda451bba7.tar.gz |
IVGCVSW-5383 TfLiteDelegate: Implement Pad and PadV2 operators
* Add Pad and PadV2 operators support to Armnn Delegate
* Add dimension check to CompareOutputData test utility
* Unit tests
Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com>
Change-Id: I9d00eb08f71e791498908fcbdb9de561e1c01aef
Diffstat (limited to 'delegate/src/Pad.hpp')
-rw-r--r-- | delegate/src/Pad.hpp | 122 |
1 files changed, 113 insertions, 9 deletions
diff --git a/delegate/src/Pad.hpp b/delegate/src/Pad.hpp index 2134232b61..6149819950 100644 --- a/delegate/src/Pad.hpp +++ b/delegate/src/Pad.hpp @@ -5,8 +5,6 @@ #pragma once -#include <armnn/utility/IgnoreUnused.hpp> - #include <tensorflow/lite/builtin_ops.h> #include <tensorflow/lite/c/builtin_op_data.h> #include <tensorflow/lite/c/common.h> @@ -19,15 +17,121 @@ TfLiteStatus VisitPadOperator(DelegateData& delegateData, TfLiteContext* tfLiteContext, TfLiteNode* tfLiteNode, int nodeIndex, - int32_t padOperatorCode) + int32_t tfLitePadOperatorCode) { - armnn::IgnoreUnused(delegateData, - tfLiteContext, - tfLiteNode, - nodeIndex, - padOperatorCode); + TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); + + switch(tfLitePadOperatorCode) + { + case kTfLiteBuiltinPad: + TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex)); + break; + case kTfLiteBuiltinPadv2: + TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 3, nodeIndex)); + break; + default: + return kTfLiteError; + } + + const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; + const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]]; + const TfLiteTensor& tfLitepaddingTensor = tfLiteTensors[tfLiteNode->inputs->data[1]]; + + if (IsDynamicTensor(tfLiteInputTensor)) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ", + tfLitePadOperatorCode, nodeIndex); + return kTfLiteError; + } + + const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]]; + if (IsDynamicTensor(tfLiteOutputTensor)) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: Dynamic output tensors are not supported in operator #%d node #%d: ", + tfLitePadOperatorCode, nodeIndex); + return kTfLiteError; + } + + const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor); + const armnn::TensorInfo& paddingTensorInfo = GetTensorInfoForTfLiteTensor(tfLitepaddingTensor); + const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor); + + // Get the padding data from the input tensor + auto* paddingData = tflite::GetTensorData<int32_t>(&tfLitepaddingTensor); + + size_t step = 2; + armnn::PadDescriptor descriptor; + for (unsigned int i = 0; i < paddingTensorInfo.GetNumElements() / step; ++i) + { + descriptor.m_PadList.emplace_back(paddingData[i * step], paddingData[i * step + 1]); + } + + if (tfLitePadOperatorCode == kTfLiteBuiltinPad && inputTensorInfo.IsQuantized()) + { + descriptor.m_PadValue = inputTensorInfo.GetQuantizationOffset(); + } + else if (tfLitePadOperatorCode == kTfLiteBuiltinPadv2) + { + const TfLiteTensor& tfLitepaddingValue = tfLiteTensors[tfLiteNode->inputs->data[2]]; + armnn::TensorInfo paddingValueTensorInfo = GetTensorInfoForTfLiteTensor(tfLitepaddingValue); + if (paddingValueTensorInfo.GetNumElements() != 1) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: Multiple padding value are not supported in operator #%d node #%d: ", + tfLitePadOperatorCode, nodeIndex); + return kTfLiteError; + } + // Get the padding value from the input tensor + switch (tfLitepaddingValue.type) + { + case kTfLiteFloat32: + descriptor.m_PadValue = tflite::GetTensorData<float>(&tfLitepaddingValue)[0]; + break; + case kTfLiteUInt8: + descriptor.m_PadValue = tflite::GetTensorData<uint8>(&tfLitepaddingValue)[0]; + break; + case kTfLiteInt8: + descriptor.m_PadValue = tflite::GetTensorData<int8>(&tfLitepaddingValue)[0]; + break; + case kTfLiteInt16: + descriptor.m_PadValue = tflite::GetTensorData<int16>(&tfLitepaddingValue)[0]; + break; + default: + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: Padding value datatype is not supported in operator #%d node #%d: ", + tfLitePadOperatorCode, nodeIndex); + return kTfLiteError; + } + } + + if (!delegateData.m_Network) + { + bool isSupported = false; + FORWARD_LAYER_SUPPORT_FUNC(__func__, + tfLiteContext, + IsPadSupported, + delegateData.m_Backends, + isSupported, + inputTensorInfo, + outputTensorInfo, + descriptor); + + return isSupported ? kTfLiteOk : kTfLiteError; + } + + armnn::IConnectableLayer* padLayer = delegateData.m_Network->AddPadLayer(descriptor); + ARMNN_ASSERT(padLayer != nullptr); + + armnn::IOutputSlot& outputSlot = padLayer->GetOutputSlot(0); + outputSlot.SetTensorInfo(outputTensorInfo); - return kTfLiteError; + return Connect(padLayer, tfLiteNode, delegateData); } } // namespace armnnDelegate |