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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include <backendsCommon/Workload.hpp>
#include <aclCommon/ArmComputeTensorUtils.hpp>
#include <neon/NeonTensorHandle.hpp>
#include <neon/NeonTimer.hpp>
#include <backendsCommon/CpuTensorHandle.hpp>
#include <Half.hpp>
#define ARMNN_SCOPED_PROFILING_EVENT_NEON(name) \
ARMNN_SCOPED_PROFILING_EVENT_WITH_INSTRUMENTS(armnn::Compute::CpuAcc, \
name, \
armnn::NeonTimer(), \
armnn::WallClockTimer())
using namespace armnn::armcomputetensorutils;
namespace armnn
{
template <typename T>
void CopyArmComputeTensorData(arm_compute::Tensor& dstTensor, const T* srcData)
{
InitialiseArmComputeTensorEmpty(dstTensor);
CopyArmComputeITensorData(srcData, dstTensor);
}
inline void InitializeArmComputeTensorData(arm_compute::Tensor& tensor,
const ConstCpuTensorHandle* handle)
{
BOOST_ASSERT(handle);
switch(handle->GetTensorInfo().GetDataType())
{
case DataType::Float16:
CopyArmComputeTensorData(tensor, handle->GetConstTensor<armnn::Half>());
break;
case DataType::Float32:
CopyArmComputeTensorData(tensor, handle->GetConstTensor<float>());
break;
case DataType::QAsymmU8:
CopyArmComputeTensorData(tensor, handle->GetConstTensor<uint8_t>());
break;
case DataType::QuantizedSymm8PerAxis:
CopyArmComputeTensorData(tensor, handle->GetConstTensor<int8_t>());
break;
case DataType::Signed32:
CopyArmComputeTensorData(tensor, handle->GetConstTensor<int32_t>());
break;
default:
BOOST_ASSERT_MSG(false, "Unexpected tensor type.");
}
};
inline auto SetNeonStridedSliceData(const std::vector<int>& m_begin,
const std::vector<int>& m_end,
const std::vector<int>& m_stride)
{
arm_compute::Coordinates starts;
arm_compute::Coordinates ends;
arm_compute::Coordinates strides;
unsigned int num_dims = static_cast<unsigned int>(m_begin.size());
for (unsigned int i = 0; i < num_dims; i++)
{
unsigned int revertedIndex = num_dims - i - 1;
starts.set(i, static_cast<int>(m_begin[revertedIndex]));
ends.set(i, static_cast<int>(m_end[revertedIndex]));
strides.set(i, static_cast<int>(m_stride[revertedIndex]));
}
return std::make_tuple(starts, ends, strides);
}
inline auto SetNeonSliceData(const std::vector<unsigned int>& m_begin,
const std::vector<unsigned int>& m_size)
{
// This function must translate the size vector given to an end vector
// expected by the ACL NESlice workload
arm_compute::Coordinates starts;
arm_compute::Coordinates ends;
unsigned int num_dims = static_cast<unsigned int>(m_begin.size());
// For strided slices, we have the relationship size = (end - begin) / stride
// For slice, we assume stride to be a vector of all ones, yielding the formula
// size = (end - begin) therefore we know end = size + begin
for (unsigned int i = 0; i < num_dims; i++)
{
unsigned int revertedIndex = num_dims - i - 1;
starts.set(i, static_cast<int>(m_begin[revertedIndex]));
ends.set(i, static_cast<int>(m_begin[revertedIndex] + m_size[revertedIndex]));
}
return std::make_tuple(starts, ends);
}
} //namespace armnn
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