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-rw-r--r--delegate/src/Redefine.hpp289
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diff --git a/delegate/src/Redefine.hpp b/delegate/src/Redefine.hpp
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-//
-// Copyright © 2022-2023 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 VisitCastOperator(DelegateData& delegateData,
- TfLiteContext* tfLiteContext,
- TfLiteNode* tfLiteNode,
- int nodeIndex,
- int32_t operatorCode)
-{
- TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
- TF_LITE_ENSURE_STATUS(ValidateNumOutputs(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;
- }
-
- const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]];
- if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex))
- {
- return kTfLiteError;
- }
-
- const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor);
- const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true);
-
- bool isSupported = false;
- armnn::BackendId setBackend;
- auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported)
- {
- FORWARD_LAYER_SUPPORT_FUNC("CAST",
- tfLiteContext,
- IsCastSupported,
- delegateData.m_Backends,
- isSupported,
- setBackend,
- inputTensorInfo,
- outInfo);
- };
-
- // 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, VisitCastOperator will be called again to add the layer to the network as seen further below
- if (!delegateData.m_Network)
- {
- validateFunc(outputTensorInfo, isSupported);
- return isSupported ? kTfLiteOk : kTfLiteError;
- }
-
- // Add a Cast layer
- armnn::IConnectableLayer* layer = delegateData.m_Network->AddCastLayer();
- 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);
-}
-
-
-TfLiteStatus CreateOutputTensorShape(const armnn::TensorInfo& inputTensorInfo,
- const std::vector<int32_t>& targetShape,
- armnn::ReshapeDescriptor& reshapeDesc)
-{
- std::vector<unsigned int> outputDims(targetShape.begin(), targetShape.end());
- const auto stretchDim = std::find(targetShape.begin(), targetShape.end(), -1);
-
- if (stretchDim != targetShape.end())
- {
- if (std::find(std::next(stretchDim), targetShape.end(), -1) != targetShape.end())
- {
- // Return kTfLiteError and log the error after returning
- return kTfLiteError;
- }
-
- auto targetNumElements =
- armnn::numeric_cast<unsigned int>(
- std::accumulate(targetShape.begin(), targetShape.end(), -1, std::multiplies<int32_t>()));
-
- auto stretchIndex = static_cast<size_t>(std::distance(targetShape.begin(), stretchDim));
- outputDims[stretchIndex] = inputTensorInfo.GetNumElements() / targetNumElements;
- }
-
- armnn::TensorShape outputShape = armnn::TensorShape(static_cast<unsigned int>(outputDims.size()),
- outputDims.data());
- reshapeDesc.m_TargetShape = outputShape;
- return kTfLiteOk;
-}
-
-TfLiteStatus VisitReshapeOperator(DelegateData& delegateData,
- TfLiteContext* tfLiteContext,
- TfLiteNode* tfLiteNode,
- int nodeIndex,
- int32_t operatorCode)
-{
- auto numInputs = tfLiteNode->inputs->size;
-
- if (numInputs == 2)
- {
- TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex));
- }
- else
- {
- TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
- }
- TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
-
- const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors;
- const TfLiteTensor& tfLiteInputTensor0 = tfLiteTensors[tfLiteNode->inputs->data[0]];
- if (!IsValid(tfLiteContext, tfLiteInputTensor0, operatorCode, nodeIndex))
- {
- return kTfLiteError;
- }
-
- const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]];
- if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex))
- {
- return kTfLiteError;
- }
-
- const armnn::TensorInfo& inputTensorInfo0 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor0);
- const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true);
-
- armnn::ReshapeDescriptor reshapeDesc;
- std::vector<int32_t> targetShape;
-
- TfLiteReshapeParams* reshapeOptions = reinterpret_cast<TfLiteReshapeParams*>(tfLiteNode->builtin_data);
-
- // The new shape can be defined by either a second input tensor or by a builtin option, we need to check for both.
- // Options might be set without valid data. we need to check the dimensions are in a valid range.
- if (reshapeOptions && reshapeOptions->num_dimensions > 0 && reshapeOptions->num_dimensions <= 8)
- {
- for (int i=0; i < reshapeOptions->num_dimensions; ++i)
- {
- targetShape.push_back(reshapeOptions->shape[i]);
- }
- }
- else if (numInputs == 2)
- {
- // Get shape from the second input tensor
- const TfLiteTensor& tfLiteShapeInputTensor = tfLiteTensors[tfLiteNode->inputs->data[1]];
- if (!IsValid(tfLiteContext, tfLiteShapeInputTensor, operatorCode, nodeIndex))
- {
- return kTfLiteError;
- }
-
- if (tfLiteShapeInputTensor.dims->size != 1)
- {
- TF_LITE_MAYBE_KERNEL_LOG(tfLiteContext,
- "TfLiteArmnnDelegate: Target 'shape' input is not a 1D tensor in "
- "operator #%d node #%d: Falling back to TfLiteOptions.",
- operatorCode, nodeIndex);
- }
- else
- {
- // Get the shape data out of the input tensor
- auto* shapeTensorDataPtr = tflite::GetTensorData<int32_t>(&tfLiteShapeInputTensor);
- auto shapeTensorNumValues = tfLiteShapeInputTensor.dims->data[0];
- for (auto i=0; i < shapeTensorNumValues; ++i)
- {
- targetShape.push_back(*(shapeTensorDataPtr+i));
- }
- }
- }
- else
- {
- TF_LITE_MAYBE_KERNEL_LOG(tfLiteContext,
- "Target shape not defined in reshape parameters or input tensor. "
- "At least one method required in operator #%d node #%d: ",
- operatorCode, nodeIndex);
- return kTfLiteError;
- }
-
- // Use the data to create the required tensor shape.
- if (CreateOutputTensorShape(inputTensorInfo0, targetShape, reshapeDesc) != kTfLiteOk)
- {
- TF_LITE_MAYBE_KERNEL_LOG(tfLiteContext,
- "TfLiteArmnnDelegate: At most one component of shape can be -1 in: "
- "operator #%d node #%d: ",
- operatorCode, nodeIndex);
- return kTfLiteError;
- }
-
- if (reshapeDesc.m_TargetShape.GetNumElements() != inputTensorInfo0.GetNumElements())
- {
- TF_LITE_MAYBE_KERNEL_LOG(
- tfLiteContext,
- "TfLiteArmnnDelegate: Reshape, number of elements in output shape does not match input "
- "operator #%d node #%d: ",
- operatorCode, nodeIndex);
- return kTfLiteError;
- }
-
- bool isSupported = false;
- armnn::BackendId setBackend;
- auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported)
- {
- FORWARD_LAYER_SUPPORT_FUNC("RESHAPE",
- tfLiteContext,
- IsReshapeSupported,
- delegateData.m_Backends,
- isSupported,
- setBackend,
- inputTensorInfo0,
- outInfo,
- reshapeDesc);
- };
-
- if (!delegateData.m_Network)
- {
- validateFunc(outputTensorInfo, isSupported);
- return isSupported ? kTfLiteOk : kTfLiteError;
- }
-
- armnn::IConnectableLayer* layer = delegateData.m_Network->AddReshapeLayer(reshapeDesc);
- 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);
-}
-
-TfLiteStatus VisitSqueezeOperator(DelegateData& delegateData,
- TfLiteContext* tfLiteContext,
- TfLiteNode* tfLiteNode,
- int nodeIndex,
- int32_t operatorCode)
-{
- armnn::IgnoreUnused(delegateData,
- tfLiteContext,
- tfLiteNode,
- nodeIndex,
- operatorCode);
-
- return kTfLiteError;
-}
-
-TfLiteStatus VisitExpandDimsOperator(DelegateData& delegateData,
- TfLiteContext* tfLiteContext,
- TfLiteNode* tfLiteNode,
- int nodeIndex,
- int32_t operatorCode)
-{
- armnn::IgnoreUnused(delegateData,
- tfLiteContext,
- tfLiteNode,
- nodeIndex,
- operatorCode);
-
- return kTfLiteError;
-}
-
-} // namespace armnnDelegate
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