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author | Teresa Charlin <teresa.charlinreyes@arm.com> | 2023-03-14 12:10:28 +0000 |
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committer | Teresa Charlin <teresa.charlinreyes@arm.com> | 2023-03-28 11:41:55 +0100 |
commit | ad1b3d7518429e2d16a2695d9b0bbf81b6565ac9 (patch) | |
tree | a5b8e1ad68a2437f007338f0b6195ca5ed2bddc3 /delegate/classic/src/StridedSlice.hpp | |
parent | 9cb3466b677a1048b8abb24661e92c4c83fdda04 (diff) | |
download | armnn-ad1b3d7518429e2d16a2695d9b0bbf81b6565ac9.tar.gz |
IVGCVSW-7555 Restructure Delegate
* New folders created:
* common is for common code where TfLite API is not used
* classic is for existing delegate implementations
* opaque is for new opaque delegate implementation,
* tests is for shared between existing Delegate and Opaque Delegate which have test utils to work which delegate to use.
* Existing delegate is built to libarmnnDelegate.so and opaque delegate is built as libarmnnOpaqueDelegate.so
* Opaque structure is introduced but no API is added yet.
* CmakeList.txt and delegate/CMakeList.txt have been modified and 2 new CmakeList.txt added
* Rename BUILD_ARMNN_TFLITE_DELEGATE as BUILD_CLASSIC_DELEGATE
* Rename BUILD_ARMNN_TFLITE_OPAQUE_DELEGATE as BUILD_OPAQUE_DELEGATE
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Ib682b9ad0ac8d8acdc4ec6d9099bb0008a9fe8ed
Diffstat (limited to 'delegate/classic/src/StridedSlice.hpp')
-rw-r--r-- | delegate/classic/src/StridedSlice.hpp | 156 |
1 files changed, 156 insertions, 0 deletions
diff --git a/delegate/classic/src/StridedSlice.hpp b/delegate/classic/src/StridedSlice.hpp new file mode 100644 index 0000000000..998e3d3e14 --- /dev/null +++ b/delegate/classic/src/StridedSlice.hpp @@ -0,0 +1,156 @@ +// +// Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#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> +#include <tensorflow/lite/minimal_logging.h> + +namespace armnnDelegate +{ + +TfLiteStatus VisitStridedSliceOperator(DelegateData& delegateData, + TfLiteContext* tfLiteContext, + TfLiteNode* tfLiteNode, + int nodeIndex, + int32_t sliceOperatorCode) +{ + TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 4, nodeIndex)); + TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); + + // Read inputs [input, begin, end, strides] + int numInputs = tfLiteNode->inputs->size; + std::vector<const TfLiteTensor*> tfLiteInputs; + tfLiteInputs.reserve(numInputs); + const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; + for (int i = 0; i < numInputs; i++) + { + const TfLiteTensor* inputTensor = &tfLiteTensors[tfLiteNode->inputs->data[i]]; + tfLiteInputs.push_back(inputTensor); + if (!IsValid(tfLiteContext, *inputTensor, sliceOperatorCode, nodeIndex)) + { + return kTfLiteError; + } + } + + // We save the begin, end and strides tensors in our descriptor. Therefore we have to read those values from inputs + int inputRank = tfLiteInputs[0]->dims->size; + auto ReadInt32Input = [&](int inputIndex, std::vector<int32_t>& outputData) -> TfLiteStatus + { + if (tfLiteInputs[inputIndex]->type != kTfLiteInt32) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: The Begin-, End- and Stride-Tensors of the StridedSlice operation need to " + "be of type int32. Operator: #%d node #%d: ", + sliceOperatorCode, nodeIndex); + return kTfLiteError; + } + int rank = tfLiteInputs[inputIndex]->dims->size; + if (rank != 1) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: The Begin-, End- and Stride-Tensors of the StridedSlice operation need to " + "be a 1D-Tensor. Operator: #%d node #%d: ", + sliceOperatorCode, nodeIndex); + return kTfLiteError; + } + int numValues = tfLiteInputs[inputIndex]->dims->data[0]; + if (numValues != inputRank) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: The number of values in the Begin-, End- and Stride-Tensors of the " + "StridedSlice operation need to be equal to the rank of the Input-Tensor. Operator: #%d node #%d: ", + sliceOperatorCode, nodeIndex); + return kTfLiteError; + } + // return tensor data + auto* tensorDataPtr = tflite::GetTensorData<int32_t>(tfLiteInputs[inputIndex]); + outputData.assign(tensorDataPtr, tensorDataPtr+numValues); + return kTfLiteOk; + }; + + std::vector<int32_t> beginData; + if (ReadInt32Input(1, beginData) != kTfLiteOk) + return kTfLiteError; + std::vector<int32_t> endData; + if (ReadInt32Input(2, endData) != kTfLiteOk) + return kTfLiteError; + std::vector<int32_t> strideData; + if (ReadInt32Input(3, strideData) != kTfLiteOk) + return kTfLiteError; + + // parse built in options + auto* stridedSliceParams = reinterpret_cast<TfLiteStridedSliceParams*>(tfLiteNode->builtin_data); + + // Write all data to the descriptor + armnn::StridedSliceDescriptor descriptor; + descriptor.m_Begin = std::move(beginData); + descriptor.m_End = std::move(endData); + descriptor.m_Stride = std::move(strideData); + descriptor.m_BeginMask = stridedSliceParams->begin_mask; + descriptor.m_EllipsisMask = stridedSliceParams->ellipsis_mask; + descriptor.m_EndMask = stridedSliceParams->end_mask; + descriptor.m_NewAxisMask = stridedSliceParams->new_axis_mask; + descriptor.m_ShrinkAxisMask = stridedSliceParams->shrink_axis_mask; + descriptor.m_DataLayout = armnn::DataLayout::NHWC; + + // Validate output + const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]]; + if (!IsValid(tfLiteContext, tfLiteOutputTensor, sliceOperatorCode, nodeIndex)) + { + return kTfLiteError; + } + + const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(*tfLiteInputs[0]); + const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor); + + bool isSupported = false; + armnn::BackendId setBackend; + auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported) + { + FORWARD_LAYER_SUPPORT_FUNC("STRIDED_SLICE", + tfLiteContext, + IsStridedSliceSupported, + delegateData.m_Backends, + isSupported, + setBackend, + inputTensorInfo, + outInfo, + descriptor); + }; + + if (!delegateData.m_Network) + { + validateFunc(outputTensorInfo, isSupported); + return isSupported ? kTfLiteOk : kTfLiteError; + } + + // Add a StridedSlice layer + armnn::IConnectableLayer* layer = delegateData.m_Network->AddStridedSliceLayer(descriptor); + layer->SetBackendId(setBackend); + ARMNN_ASSERT(layer != nullptr); + + armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); + outputSlot.SetTensorInfo(outputTensorInfo); + + // try to connect the Constant Inputs if there are any + if(ProcessInputs(layer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk ) + { + return kTfLiteError; + } + + // Connect + return Connect(layer, tfLiteNode, delegateData); +} + +} // namespace armnnDelegate + |