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
diff --git a/delegate/classic/src/Pack.hpp b/delegate/classic/src/Pack.hpp
new file mode 100644
index 0000000..99c8b80
--- /dev/null
+++ b/delegate/classic/src/Pack.hpp
@@ -0,0 +1,122 @@
+//
+// Copyright © 2021,2022-2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#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 VisitPackOperator(DelegateData& delegateData,
+ TfLiteContext* tfLiteContext,
+ TfLiteNode* tfLiteNode,
+ int nodeIndex,
+ int32_t operatorCode)
+{
+ unsigned int numInputs = tfLiteNode->inputs->size;
+ if (numInputs < 1)
+ {
+ TF_LITE_MAYBE_KERNEL_LOG(
+ tfLiteContext, "TfLiteArmnnDelegate: Must have at least one input in (%d != %d) in node #%d",
+ 1, numInputs, nodeIndex);
+ return kTfLiteError;
+ }
+
+ TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+
+ const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors;
+
+ // Validate all inputs and get TensorInfo
+ std::vector<armnn::TensorInfo> inputTensorInfos;
+ for (unsigned int i = 0; i < numInputs; ++i)
+ {
+ const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[i]];
+ if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex))
+ {
+ return kTfLiteError;
+ }
+
+ armnn::TensorInfo inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor);
+ inputTensorInfos.emplace_back(inputTensorInfo);
+ }
+
+ // Convert input tensors to const armnn::TensorInfo* type for FORWARD_LAYER_SUPPORT_FUNC.
+ std::vector<const armnn::TensorInfo*> inputConstTensorInfos;
+ std::transform(inputTensorInfos.begin(),
+ inputTensorInfos.end(),
+ std::back_inserter(inputConstTensorInfos),
+ [](armnn::TensorInfo& t)->const armnn::TensorInfo*{ return &t; });
+
+ // Validate output and get TensorInfo
+ const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]];
+ if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex))
+ {
+ return kTfLiteError;
+ }
+
+ const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true);
+
+ armnn::StackDescriptor desc;
+ desc.m_NumInputs = static_cast<uint32_t>(numInputs);
+
+ // Get axis from TfLite parameters
+ auto* params = reinterpret_cast<TfLitePackParams*>(tfLiteNode->builtin_data);
+ desc.m_Axis = static_cast<uint32_t>(params->axis);
+
+ // Use the tensor shape of the first input as the "correct" input shape in the descriptor
+ desc.m_InputShape = inputTensorInfos[0].GetShape();
+
+ // Check if supported
+ bool isSupported = false;
+ armnn::BackendId setBackend;
+ auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported)
+ {
+ FORWARD_LAYER_SUPPORT_FUNC("STACK",
+ tfLiteContext,
+ IsStackSupported,
+ delegateData.m_Backends,
+ isSupported,
+ setBackend,
+ inputConstTensorInfos,
+ outputTensorInfo,
+ desc);
+ };
+
+ // If the m_Network is a nullptr, this signals that a prerequisite TfLite callback is required to clarify the
+ // support for the operator
+ // If supported, VisitPackOperator will be called again to add the layer to the network as seen below
+ if (!delegateData.m_Network)
+ {
+ validateFunc(outputTensorInfo, isSupported);
+ return isSupported ? kTfLiteOk : kTfLiteError;
+ }
+
+ // The TfLite Pack operator is equivalent to the ArmNN Stack operator
+ armnn::IConnectableLayer* layer = delegateData.m_Network->AddStackLayer(desc);
+ layer->SetBackendId(setBackend);
+ ARMNN_ASSERT(layer != nullptr);
+
+ // Connect the Constant Inputs
+ auto inputsTensorsProcess = ProcessInputs(layer,
+ delegateData,
+ tfLiteContext,
+ tfLiteNode);
+ if (inputsTensorsProcess == kTfLiteError)
+ {
+ return inputsTensorsProcess;
+ }
+
+ armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0);
+ outputSlot.SetTensorInfo(outputTensorInfo);
+
+ // Connect
+ return Connect(layer, tfLiteNode, delegateData);
+}
+
+} // namespace armnnDelegate