/*******************************************************************************
* Copyright 2016-2018 Intel Corporation
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*     http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*******************************************************************************/

#ifndef NSTL_HPP
#define NSTL_HPP

#include <stdint.h>
#include <limits.h>
#include <float.h>

#include <vector>
#include <map>

#include "utils.hpp"

namespace mkldnn {
namespace impl {
namespace nstl {

template<typename T>
inline const T abs(const T& a) {
    return a >= 0 ? a : -a;
}

template<typename T>
inline const T& max(const T& a, const T& b) {
    return a > b ? a : b;
}

template<typename T>
inline const T& min(const T& a, const T& b) {
    return a < b ? a : b;
}

template<typename T> void swap(T& t1, T& t2) {
    T tmp(t1);
    t1=t2;
    t2=tmp;
}

// Rationale: MKL-DNN needs numeric limits implementation that does not
// generate dependencies on C++ run-time libraries.

template<typename T> struct numeric_limits;

template<> struct numeric_limits<float> {
    static constexpr float lowest() { return -FLT_MAX; }
    static constexpr float max() { return FLT_MAX; }
};

template<> struct numeric_limits<int32_t> {
    static constexpr int lowest() { return INT32_MIN; }
    static constexpr int max() { return INT32_MAX; }
};

template<> struct numeric_limits<int16_t> {
    static constexpr int16_t lowest() { return INT16_MIN; }
    static constexpr int16_t max() { return INT16_MAX; }
};

template<> struct numeric_limits<int8_t> {
    static constexpr int8_t lowest() { return INT8_MIN; }
    static constexpr int8_t max() { return INT8_MAX; }
};

template<> struct numeric_limits<uint8_t> {
    static constexpr uint8_t lowest() { return 0; }
    static constexpr uint8_t max() { return UINT8_MAX; }
};

template<typename T> struct is_integral
{ static constexpr bool value = false; };
template<> struct is_integral<int32_t> { static constexpr bool value = true; };
template<> struct is_integral<int16_t> { static constexpr bool value = true; };
template<> struct is_integral<int8_t> { static constexpr bool value = true; };
template<> struct is_integral<uint8_t> { static constexpr bool value = true; };

template <typename T, typename U> struct is_same
{ static constexpr bool value = false; };
template <typename T> struct is_same<T, T>
{ static constexpr bool value = true; };

// Rationale: MKL-DNN needs container implementations that do not generate
// dependencies on C++ run-time libraries.
//
// Implementation philosophy: caller is responsible to check if the operation
// is valid. The only functions that have to return status are those that
// depend on memory allocation or similar operations.
//
// This means that e.g. an operator [] does not have to check for boundaries.
// The caller should have checked the boundaries. If it did not we crash and
// burn: this is a bug in MKL-DNN and throwing an exception would not have been
// recoverable.
//
// On the other hand, insert() or resize() or a similar operation needs to
// return a status because the outcome depends on factors external to the
// caller. The situation is probably also not recoverable also, but MKL-DNN
// needs to be nice and report "out of memory" to the users.

enum nstl_status_t {
    success = 0,
    out_of_memory
};

template <typename T> class vector: public c_compatible {
private:
    std::vector<T> _impl;
public:
    typedef typename std::vector<T>::iterator iterator;
    typedef typename std::vector<T>::const_iterator const_iterator;
    typedef typename std::vector<T>::size_type size_type;
    vector() {}
    vector(size_type n): _impl(n) {}
    vector(size_type n, const T &value): _impl(n, value) {}
    template <typename input_iterator>
    vector(input_iterator first, input_iterator last): _impl(first, last) {}
    ~vector() {}
    size_type size() const { return _impl.size(); }
    T& operator[] (size_type i) { return _impl[i]; }
    const T& operator[] (size_type i) const { return _impl[i]; }
    iterator begin() { return _impl.begin(); }
    const_iterator begin() const { return _impl.begin(); }
    iterator end() { return _impl.end(); }
    const_iterator end() const { return _impl.end(); }
    template <typename input_iterator>
    nstl_status_t insert(iterator pos, input_iterator begin, input_iterator end)
    {
        _impl.insert(pos, begin, end);
        return success;
    }
    void clear() { _impl.clear(); }
    void push_back(const T& t) { _impl.push_back(t); }
    void resize(size_type count) { _impl.resize(count); }
    void reserve(size_type count) { _impl.reserve(count); }
};

template <typename Key, typename T> class map: public c_compatible {
private:
    std::map<Key, T> _impl;
public:
    typedef typename std::map<Key, T>::iterator iterator;
    typedef typename std::map<Key, T>::const_iterator const_iterator;
    typedef typename std::map<Key, T>::size_type size_type;
    map() {}
    ~map() {}
    size_type size() const { return _impl.size(); }
    T& operator[](const Key &k) { return _impl[k]; }
    const T& operator[](const Key &k) const { return _impl[k]; }
    iterator begin() { return _impl.begin(); }
    const_iterator begin() const { return _impl.begin(); }
    iterator end() { return _impl.end(); }
    const_iterator end() const { return _impl.end(); }
    template <typename input_iterator>
    void clear() { _impl.clear(); }
};

}
}
}

#endif

// vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s