Types.hpp

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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once

#include <array>
#include <functional>
#include <memory>
#include <stdint.h>
#include "BackendId.hpp"
#include "Exceptions.hpp"
#include "Deprecated.hpp"

namespace armnn
{

constexpr unsigned int MaxNumOfTensorDimensions = 5U;

// The lowest performance data capture interval we support is 10 miliseconds.
constexpr unsigned int LOWEST_CAPTURE_PERIOD = 10000u;

enum class Status
{
    Success = 0,
    Failure = 1
};

enum class DataType
{
    Float16 = 0,
    Float32 = 1,
    QAsymmU8 = 2,
    Signed32 = 3,
    Boolean = 4,
    QSymmS16 = 5,
    QuantizedSymm8PerAxis ARMNN_DEPRECATED_ENUM_MSG("Per Axis property inferred by number of scales in TensorInfo") = 6,
    QSymmS8 = 7,
    QAsymmS8 = 8,

    QuantisedAsymm8 ARMNN_DEPRECATED_ENUM_MSG("Use DataType::QAsymmU8 instead.") = QAsymmU8,
    QuantisedSymm16 ARMNN_DEPRECATED_ENUM_MSG("Use DataType::QSymmS16 instead.") = QSymmS16
};

enum class DataLayout
{
    NCHW = 1,
    NHWC = 2
};

enum class ActivationFunction
{
    Sigmoid     = 0,
    TanH        = 1,
    Linear      = 2,
    ReLu        = 3,
    BoundedReLu = 4, 
    SoftReLu    = 5,
    LeakyReLu   = 6,
    Abs         = 7,
    Sqrt        = 8,
    Square      = 9
};

enum class ArgMinMaxFunction
{
    Min = 0,
    Max = 1
};

enum class ComparisonOperation
{
    Equal          = 0,
    Greater        = 1,
    GreaterOrEqual = 2,
    Less           = 3,
    LessOrEqual    = 4,
    NotEqual       = 5
};

enum class UnaryOperation
{
    Abs   = 0,
    Exp   = 1,
    Sqrt  = 2,
    Rsqrt = 3,
    Neg   = 4
};

enum class PoolingAlgorithm
{
    Max     = 0,
    Average = 1,
    L2      = 2
};

enum class ResizeMethod
{
    Bilinear        = 0,
    NearestNeighbor = 1
};

enum class PaddingMethod
{
    IgnoreValue = 0,
    Exclude     = 1
};

enum class NormalizationAlgorithmChannel
{
    Across = 0,
    Within = 1
};

enum class NormalizationAlgorithmMethod
{
    LocalBrightness = 0,
    LocalContrast = 1
};

enum class OutputShapeRounding
{
    Floor       = 0,
    Ceiling     = 1
};

class IBackend
{
protected:
    IBackend() {}
    virtual ~IBackend() {}

public:
    virtual const BackendId& GetId() const = 0;
};

using IBackendSharedPtr = std::shared_ptr<IBackend>;
using IBackendUniquePtr = std::unique_ptr<IBackend, void(*)(IBackend* backend)>;

class IDeviceSpec
{
protected:
    IDeviceSpec() {}
    virtual ~IDeviceSpec() {}
public:
    virtual const BackendIdSet& GetSupportedBackends() const = 0;
};

using LayerBindingId = int;

class PermutationVector
{
public:
    using ValueType = unsigned int;
    using SizeType = unsigned int;
    using ArrayType = std::array<ValueType, MaxNumOfTensorDimensions>;
    using ConstIterator = typename ArrayType::const_iterator;

    PermutationVector(const ValueType *dimMappings, SizeType numDimMappings);

    PermutationVector(std::initializer_list<ValueType> dimMappings);

    ValueType operator[](SizeType i) const { return m_DimMappings.at(i); }

    SizeType GetSize() const { return m_NumDimMappings; }

    ConstIterator begin() const { return m_DimMappings.begin(); }
    ConstIterator end() const { return m_DimMappings.end(); }

    bool IsEqual(const PermutationVector& other) const
    {
        if (m_NumDimMappings != other.m_NumDimMappings) return false;
        for (unsigned int i = 0; i < m_NumDimMappings; ++i)
        {
            if (m_DimMappings[i] != other.m_DimMappings[i]) return false;
        }
        return true;
    }

    bool IsInverse(const PermutationVector& other) const
    {
        bool isInverse = (GetSize() == other.GetSize());
        for (SizeType i = 0; isInverse && (i < GetSize()); ++i)
        {
            isInverse = (m_DimMappings[other.m_DimMappings[i]] == i);
        }
        return isInverse;
    }

private:
    ArrayType m_DimMappings;
    SizeType m_NumDimMappings;
};

namespace profiling { class ProfilingGuid; }

using LayerGuid = profiling::ProfilingGuid;

class ITensorHandle;

using DebugCallbackFunction = std::function<void(LayerGuid guid, unsigned int slotIndex, ITensorHandle* tensorHandle)>;


namespace profiling
{

static constexpr uint64_t MIN_STATIC_GUID = 1llu << 63;

class ProfilingGuid
{
public:
    ProfilingGuid(uint64_t guid) : m_Guid(guid) {}

    operator uint64_t() const { return m_Guid; }

    bool operator==(const ProfilingGuid& other) const
    {
        return m_Guid == other.m_Guid;
    }

    bool operator!=(const ProfilingGuid& other) const
    {
        return m_Guid != other.m_Guid;
    }

    bool operator<(const ProfilingGuid& other) const
    {
        return m_Guid < other.m_Guid;
    }

    bool operator<=(const ProfilingGuid& other) const
    {
        return m_Guid <= other.m_Guid;
    }

    bool operator>(const ProfilingGuid& other) const
    {
        return m_Guid > other.m_Guid;
    }

    bool operator>=(const ProfilingGuid& other) const
    {
        return m_Guid >= other.m_Guid;
    }

protected:
    uint64_t m_Guid;
};

struct ProfilingDynamicGuid : public ProfilingGuid
{
    using ProfilingGuid::ProfilingGuid;
};

struct ProfilingStaticGuid : public ProfilingGuid
{
    using ProfilingGuid::ProfilingGuid;
};

} // namespace profiling

} // namespace armnn


namespace std
{
// make ProfilingGuid hashable
template<>
struct hash<armnn::profiling::ProfilingGuid>
{
    std::size_t operator()(armnn::profiling::ProfilingGuid const& guid) const noexcept
    {
        return hash<uint64_t>()(uint64_t(guid));
    }
};

// make ProfilingDynamicGuid hashable
template<>
struct hash<armnn::profiling::ProfilingDynamicGuid>
{
    std::size_t operator()(armnn::profiling::ProfilingDynamicGuid const& guid) const noexcept
    {
        return hash<uint64_t>()(uint64_t(guid));
    }
};

// make ProfilingStaticGuid hashable
template<>
struct hash<armnn::profiling::ProfilingStaticGuid>
{
    std::size_t operator()(armnn::profiling::ProfilingStaticGuid const& guid) const noexcept
    {
        return hash<uint64_t>()(uint64_t(guid));
    }
};
} // namespace std