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

1 files changed, 0 insertions, 214 deletions

diff --git a/delegate/src/Unpack.hpp b/delegate/src/Unpack.hpp
deleted file mode 100644
index ad541adccc..0000000000
--- a/delegate/src/Unpack.hpp
+++ /dev/null
@@ -1,214 +0,0 @@
-//
-// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#pragma once
-
-#include <armnn/utility/IgnoreUnused.hpp>
-
-#include "DelegateUtils.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>
-#include <numeric>
-
-namespace armnnDelegate
-{
-
-TfLiteStatus VisitUnpackOperator(DelegateData& delegateData,
-                                 TfLiteContext* tfLiteContext,
-                                 TfLiteNode* tfLiteNode,
-                                 int nodeIndex,
-                                 int32_t operatorCode)
-{
-    TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
-
-    const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors;
-    const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]];
-
-    if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex))
-    {
-        return kTfLiteError;
-    }
-
-    // Get Unpack Axis
-    const auto params = reinterpret_cast<TfLiteUnpackParams*>(tfLiteNode->builtin_data);
-
-    const unsigned int unpackAxis = NonNegative(params->axis, nodeIndex);
-
-    const armnn::TensorInfo& inputTensorInfo  = GetTensorInfoForTfLiteTensor(tfLiteInputTensor);
-
-    if (unpackAxis >= inputTensorInfo.GetNumDimensions())
-    {
-        TF_LITE_MAYBE_KERNEL_LOG(
-            tfLiteContext,
-            "TfLiteArmnnDelegate: The unpack axis #%d cannot be greater than or equal to "
-            "the number of input dimensions #%d in operator #%d node #%d",
-            unpackAxis, inputTensorInfo.GetNumDimensions(), operatorCode, nodeIndex);
-        return kTfLiteError;
-    }
-
-    // Get Unpack Num
-    unsigned int unpackNum = NonNegative(params->num, nodeIndex);
-
-    // If num is not defined, automatically infer from the length of the dimension axis.
-    if(unpackNum == 0)
-    {
-        unpackNum = inputTensorInfo.GetShape()[unpackAxis];
-    }
-
-    // If unpack number cannot be inferred and is still zero, return kTfLiteError.
-    if(unpackNum == 0)
-    {
-        TF_LITE_MAYBE_KERNEL_LOG(
-            tfLiteContext,
-            "TfLiteArmnnDelegate: Number to unpack must greater than zero in operator #%d node #%d: ",
-            operatorCode, nodeIndex);
-        return kTfLiteError;
-    }
-
-    // Check outputs
-    TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, unpackNum, nodeIndex));
-
-
-    auto inputDimSize = inputTensorInfo.GetNumDimensions();
-    std::vector<unsigned int> unpackDimSizes(inputDimSize);
-
-    // Add current input shape to unpackDimSizes
-    for (unsigned int i = 0; i < inputDimSize; ++i)
-    {
-        unpackDimSizes[i] = inputTensorInfo.GetShape()[i];
-    }
-
-    if (unpackDimSizes[unpackAxis] != unpackNum)
-    {
-        TF_LITE_MAYBE_KERNEL_LOG(
-            tfLiteContext,
-            "TfLiteArmnnDelegate: Number to unpack must be the same as length "
-            "of the dimension to unpack along in operator #%d node #%d: ",
-            operatorCode, nodeIndex);
-        return kTfLiteError;
-    }
-
-    unpackDimSizes[unpackAxis] /= unpackNum;
-
-    armnn::SplitterDescriptor splitDesc(unpackNum, static_cast<unsigned int>(unpackDimSizes.size()));
-    for (unsigned int j = 0; j < unpackNum; ++j)
-    {
-        // Set the size of the views.
-        for (unsigned int dimIdx = 0; dimIdx < unpackDimSizes.size(); ++dimIdx)
-        {
-            splitDesc.SetViewSize(j, dimIdx, unpackDimSizes[dimIdx]);
-        }
-        splitDesc.SetViewOriginCoord(j, unpackAxis, unpackDimSizes[unpackAxis] * j);
-    }
-
-    std::vector<armnn::TensorInfo> outputs;
-    for (unsigned int i = 0; i < unpackNum; ++i)
-    {
-        const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[i]];
-        if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex))
-        {
-            return kTfLiteError;
-        }
-        outputs.push_back(GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true));
-    }
-    const std::vector<std::reference_wrapper<armnn::TensorInfo>> outputTensorInfos(outputs.begin(), outputs.end());
-
-    // Determine the shape of the Splitter layer outputs for validation
-    armnn::TensorShape splitOutShape = armnn::TensorShape(static_cast<unsigned int>(unpackDimSizes.size()),
-                                                          unpackDimSizes.data());
-
-    std::vector<armnn::TensorInfo> splitterOutputs;
-    for (unsigned int outputIndex = 0; outputIndex < outputTensorInfos.size(); ++outputIndex)
-    {
-        splitterOutputs.push_back(armnn::TensorInfo(splitOutShape,
-                                                    outputTensorInfos[outputIndex].get().GetDataType(),
-                                                    outputTensorInfos[outputIndex].get().GetQuantizationScale(),
-                                                    outputTensorInfos[outputIndex].get().GetQuantizationOffset()));
-    }
-    std::vector<std::reference_wrapper<armnn::TensorInfo>> splitterOutputTensorInfos(splitterOutputs.begin(),
-                                                                                     splitterOutputs.end());
-
-    armnn::BackendId setBackendSplit;
-    if (!delegateData.m_Network)
-    {
-        // Check if splitter is supported
-        bool isSupported = false;
-        FORWARD_LAYER_SUPPORT_FUNC("UNPACK",
-                                   tfLiteContext,
-                                   IsSplitterSupported,
-                                   delegateData.m_Backends,
-                                   isSupported,
-                                   setBackendSplit,
-                                   inputTensorInfo,
-                                   splitterOutputTensorInfos,
-                                   splitDesc);
-        return isSupported ? kTfLiteOk : kTfLiteError;
-    }
-
-    // Create Reshape descriptor from the first outputTensorInfo to validate a single Reshape layer
-    // Use this descriptor later when creating every ReshapeLayer as all Reshape Layers should be the same
-    armnn::ReshapeDescriptor reshapeDescriptor;
-    reshapeDescriptor.m_TargetShape = outputTensorInfos[0].get().GetShape();
-
-    armnn::BackendId setBackendReshape;
-    if (!delegateData.m_Network)
-    {
-        bool isSupported = false;
-        FORWARD_LAYER_SUPPORT_FUNC("RESHAPE",
-                                   tfLiteContext,
-                                   IsReshapeSupported,
-                                   delegateData.m_Backends,
-                                   isSupported,
-                                   setBackendReshape,
-                                   splitterOutputTensorInfos[0],
-                                   outputTensorInfos[0],
-                                   reshapeDescriptor);
-        return isSupported ? kTfLiteOk : kTfLiteError;
-    };
-
-    std::string splitterLayerName("Unpack Splitter");
-
-    armnn::IConnectableLayer* splitterLayer = delegateData.m_Network->AddSplitterLayer(splitDesc,
-                                                                                       splitterLayerName.c_str());
-    splitterLayer->SetBackendId(setBackendSplit);
-    ARMNN_ASSERT(splitterLayer != nullptr);
-
-    for (unsigned int k = 0; k < splitterLayer->GetNumOutputSlots(); ++k)
-    {
-        splitterLayer->GetOutputSlot(k).SetTensorInfo(outputs[k]);
-    }
-
-    // Connect the input slots
-    delegateData.m_OutputSlotForNode[tfLiteNode->inputs->data[0]]->Connect(splitterLayer->GetInputSlot(0));
-
-    // Create reshape to remove the unpacked dimension for unpack operator of each output from Splitter.
-    for (unsigned int outputIndex = 0; outputIndex < splitterLayer->GetNumOutputSlots(); ++outputIndex)
-    {
-        std::string reshapeLayerName("Unpack Reshape");
-        armnn::IConnectableLayer* reshapeLayer = delegateData.m_Network->AddReshapeLayer(reshapeDescriptor,
-                                                                                         reshapeLayerName.c_str());
-        reshapeLayer->SetBackendId(setBackendReshape);
-        ARMNN_ASSERT(reshapeLayer != nullptr);
-
-        splitterLayer->GetOutputSlot(outputIndex).SetTensorInfo(splitterOutputTensorInfos[outputIndex]);
-        splitterLayer->GetOutputSlot(outputIndex).Connect(reshapeLayer->GetInputSlot(0));
-
-        armnn::TensorInfo outputTensorInfo  = outputTensorInfos[outputIndex];
-        reshapeLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
-        armnn::IOutputSlot& slot = reshapeLayer->GetOutputSlot(0);
-
-        delegateData.m_OutputSlotForNode[
-            static_cast<unsigned long>(tfLiteNode->outputs->data[outputIndex])] = &slot;
-
-    }
-
-    return kTfLiteOk;
-}
-
-} // namespace armnnDelegate