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//
// Copyright © 2020 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>
#include <tensorflow/lite/kernels/internal/tensor_ctypes.h>
namespace armnnDelegate
{
TfLiteStatus VisitTransposeOperator(DelegateData& delegateData,
TfLiteContext* tfLiteContext,
TfLiteNode* tfLiteNode,
int nodeIndex,
int32_t tfliteTransposeOperatorCode)
{
TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex));
TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
const TfLiteTensor *tfLiteTensors = tfLiteContext->tensors;
const TfLiteTensor& tfLiteInputTensor0 = tfLiteTensors[tfLiteNode->inputs->data[0]];
if (IsDynamicTensor(tfLiteInputTensor0))
{
TF_LITE_MAYBE_KERNEL_LOG(tfLiteContext,
"TfLiteArmnnDelegate: Dynamic input tensors are not supported in "
"operator #%d node #%d: ",
tfliteTransposeOperatorCode, nodeIndex);
return kTfLiteError;
}
const TfLiteTensor& tfLiteInputTensor1 = tfLiteTensors[tfLiteNode->inputs->data[1]];
if (IsDynamicTensor(tfLiteInputTensor1))
{
TF_LITE_MAYBE_KERNEL_LOG(tfLiteContext,
"TfLiteArmnnDelegate: Dynamic input tensors are not supported in "
"operator #%d node #%d: ",
tfliteTransposeOperatorCode, 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: ",
tfliteTransposeOperatorCode, nodeIndex);
return kTfLiteError;
}
const armnn::TensorInfo& inputTensorInfo0 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor0);
const armnn::TensorInfo& inputTensorInfo1 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor1); //permutation tensor
const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor);
auto* permTensorDataPtr = tflite::GetTensorData<int32_t>(&tfLiteInputTensor1);
unsigned int numEl = tfLiteInputTensor1.dims->data[0];
ARMNN_ASSERT( numEl <= armnn::MaxNumOfTensorDimensions);
ARMNN_ASSERT( tfLiteInputTensor1.dims->size == 1); // ensure only single dimension to the permutation tensor
armnn::TransposeDescriptor descriptor(armnn::PermutationVector(
reinterpret_cast<const armnn::PermutationVector::ValueType *> (permTensorDataPtr),
static_cast<armnn::PermutationVector::SizeType>(numEl)));
bool isSupported = false;
auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported)
{
FORWARD_LAYER_SUPPORT_FUNC(__func__,
tfLiteContext,
IsTransposeSupported,
delegateData.m_Backends,
isSupported,
inputTensorInfo0,
outputTensorInfo,
descriptor);
};
if (!delegateData.m_Network)
{
validateFunc(outputTensorInfo, isSupported);
return isSupported ? kTfLiteOk : kTfLiteError;
}
armnn::IConnectableLayer* transposeLayer = delegateData.m_Network->AddTransposeLayer(descriptor);
ARMNN_ASSERT(transposeLayer != nullptr);
ARMNN_ASSERT(transposeLayer->GetNumInputSlots() == 1); // permutation vector given to descriptor object
armnn::IOutputSlot& outputSlot = transposeLayer->GetOutputSlot(0);
outputSlot.SetTensorInfo(outputTensorInfo);
return Connect(transposeLayer, tfLiteNode, delegateData);
}
} // namespace armnnDelegate
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