cavis/libnd4j/blas/cpu/NDArrayLambda.hpp

template<typename T>
void NDArray::applyTriplewiseLambda(NDArray& second, NDArray& third, const std::function<T(T, T, T)>& func, NDArray& target) {

    if(dataType() != DataTypeUtils::fromT<T>())
        throw std::runtime_error("NDArray::applyTriplewiseLambda<T> method: wrong template parameter T, its type should be the same as type of this array!");
    if(dataType() != second.dataType() || dataType() != third.dataType() || dataType() != target.dataType())
        throw std::runtime_error("NDArray::applyTriplewiseLambda<T> method: bother four arrays (this, second, third, target) should have the same type !");

    if (this->lengthOf() != second.lengthOf() || this->lengthOf() != third.lengthOf() || !this->isSameShape(second) || !this->isSameShape(third)) {
        nd4j_printf("applyPairwiseLambda requires both operands to have the same shape\n","");
        throw std::runtime_error("Shapes mismach");
    }

    auto f = this->bufferAsT<T>();
    auto s = second.bufferAsT<T>();
    auto t = third.bufferAsT<T>();
    auto z = target.bufferAsT<T>();

    if (this->ordering() == second.ordering() && this->ordering() == third.ordering()  && this->ordering() == target.ordering() && (this->ews() == 1 && target.ews() == 1) && this->ews() == second.ews() && this->ews() == third.ews()) {

        auto loop = PRAGMA_THREADS_FOR {
            for (auto e = start; e < stop; e += increment)
                z[e] = func(f[e], s[e], t[e]);
        };

        samediff::Threads::parallel_for(loop, 0, _length);
    } else {
        if (f == z) {

            auto loop = PRAGMA_THREADS_FOR {
                for (auto e = start; e < stop; e += increment) {
                    auto tOffset = this->getOffset(e);
                    auto uOffset = second.getOffset(e);
                    auto vOffset = third.getOffset(e);

                    f[tOffset] = func(f[tOffset], s[uOffset], t[vOffset]);
                }
            };

            samediff::Threads::parallel_for(loop, 0, _length);
        } else {

            auto loop = PRAGMA_THREADS_FOR {
                for (auto e = start; e < stop; e += increment) {
                    auto tOffset = this->getOffset(e);
                    auto uOffset = second.getOffset(e);
                    auto vOffset = third.getOffset(e);
                    auto zOffset = target.getOffset(e);

                    z[zOffset] = func(f[tOffset], s[uOffset], t[vOffset]);
                }
            };

            samediff::Threads::parallel_for(loop, 0, _length);
        }
    }
}
template void NDArray::applyTriplewiseLambda(NDArray& second, NDArray &third, const std::function<double (double, double, double)>& func, NDArray& target);
template void NDArray::applyTriplewiseLambda(NDArray& second, NDArray &third, const std::function<float (float, float, float)>& func, NDArray& target);
template void NDArray::applyTriplewiseLambda(NDArray& second, NDArray &third, const std::function<float16 (float16, float16, float16)>& func, NDArray& target);
template void NDArray::applyTriplewiseLambda(NDArray& second, NDArray &third, const std::function<bfloat16 (bfloat16, bfloat16, bfloat16)>& func, NDArray& target);
template void NDArray::applyTriplewiseLambda(NDArray& second, NDArray &third, const std::function<Nd4jLong (Nd4jLong, Nd4jLong, Nd4jLong)>& func, NDArray& target);
template void NDArray::applyTriplewiseLambda(NDArray& second, NDArray &third, const std::function<int (int, int, int)>& func, NDArray& target);
template void NDArray::applyTriplewiseLambda(NDArray& second, NDArray &third, const std::function<int16_t (int16_t, int16_t, int16_t)>& func, NDArray& target);
template void NDArray::applyTriplewiseLambda(NDArray& second, NDArray &third, const std::function<uint8_t (uint8_t, uint8_t, uint8_t)>& func, NDArray& target);
template void NDArray::applyTriplewiseLambda(NDArray& second, NDArray &third, const std::function<uint16_t (uint16_t, uint16_t, uint16_t)>& func, NDArray& target);
template void NDArray::applyTriplewiseLambda(NDArray& second, NDArray &third, const std::function<uint32_t (uint32_t, uint32_t, uint32_t)>& func, NDArray& target);
template void NDArray::applyTriplewiseLambda(NDArray& second, NDArray &third, const std::function<uint64_t (uint64_t, uint64_t, uint64_t)>& func, NDArray& target);
template void NDArray::applyTriplewiseLambda(NDArray& second, NDArray &third, const std::function<int8_t (int8_t, int8_t, int8_t)>& func, NDArray& target);
template void NDArray::applyTriplewiseLambda(NDArray& second, NDArray &third, const std::function<bool (bool, bool, bool)>& func, NDArray& target);

//////////////////////////////////////////////////////////////////////////
template<typename T>
void NDArray::applyPairwiseLambda(const NDArray& other, const std::function<T(T, T)>& func, NDArray& target) {

    if(dataType() != DataTypeUtils::fromT<T>())
        throw std::runtime_error("NDArray::applyPairwiseLambda<T> method: wrong template parameter T, its type should be the same as type of this array!");
    if(dataType() != other.dataType() || dataType() != target.dataType())
        throw std::runtime_error("NDArray::applyPairwiseLambda<T> method: all three arrays (this, other, target) must have the same type !");

    if (this->lengthOf() != other.lengthOf()) {
        nd4j_printf("applyPairwiseLambda requires both operands to have the same shape\n","");
        throw std::runtime_error("Shapes mismach");
    }

    auto f = this->bufferAsT<T>();
    auto s = other.bufferAsT<T>();
    auto z = target.bufferAsT<T>();

    if (this->ordering() == other.ordering() && this->ordering() == target.ordering() && (this->ews() == 1 && target.ews() == 1) && this->ews() == other.ews()) {

        auto loop = PRAGMA_THREADS_FOR {
            for (auto e = start; e < stop; e += increment)
                z[e] = func(f[e], s[e]);
        };

        samediff::Threads::parallel_for(loop, 0, _length);
    } else {
        if (f == z) {

            auto loop = PRAGMA_THREADS_FOR {
                for (auto e = start; e < stop; e += increment) {
                    auto xOffset = this->getOffset(e);
                    auto yOffset = other.getOffset(e);

                    f[xOffset] = func(f[xOffset], s[yOffset]);
                }
            };

            samediff::Threads::parallel_for(loop, 0, _length);
        } else {

            auto loop = PRAGMA_THREADS_FOR {
                for (auto e = start; e < stop; e += increment) {
                    auto xOffset = this->getOffset(e);
                    auto yOffset = other.getOffset(e);
                    auto zOffset = target.getOffset(e);

                    z[zOffset] = func(f[xOffset], s[yOffset]);
                }
            };

            samediff::Threads::parallel_for(loop, 0, _length);
        }
    }
}
template void NDArray::applyPairwiseLambda(const NDArray& other, const std::function<double (double, double)>& func, NDArray& target);
template void NDArray::applyPairwiseLambda(const NDArray& other, const std::function<float (float, float)>& func, NDArray& target);
template void NDArray::applyPairwiseLambda(const NDArray& other, const std::function<float16 (float16, float16)>& func, NDArray& target);
template void NDArray::applyPairwiseLambda(const NDArray& other, const std::function<bfloat16 (bfloat16, bfloat16)>& func, NDArray& target);
template void NDArray::applyPairwiseLambda(const NDArray& other, const std::function<Nd4jLong (Nd4jLong, Nd4jLong)>& func, NDArray& target);
template void NDArray::applyPairwiseLambda(const NDArray& other, const std::function<int (int, int)>& func, NDArray& target);
template void NDArray::applyPairwiseLambda(const NDArray& other, const std::function<int16_t (int16_t, int16_t)>& func, NDArray& target);
template void NDArray::applyPairwiseLambda(const NDArray& other, const std::function<uint8_t (uint8_t, uint8_t)>& func, NDArray& target);
template void NDArray::applyPairwiseLambda(const NDArray& other, const std::function<uint16_t (uint16_t, uint16_t)>& func, NDArray& target);
template void NDArray::applyPairwiseLambda(const NDArray& other, const std::function<uint32_t (uint32_t, uint32_t)>& func, NDArray& target);
template void NDArray::applyPairwiseLambda(const NDArray& other, const std::function<uint64_t (uint64_t, uint64_t)>& func, NDArray& target);
template void NDArray::applyPairwiseLambda(const NDArray& other, const std::function<int8_t (int8_t, int8_t)>& func, NDArray& target);
template void NDArray::applyPairwiseLambda(const NDArray& other, const std::function<bool (bool, bool)>& func, NDArray& target);

//////////////////////////////////////////////////////////////////////////
template<typename T>
void NDArray::applyLambda(const std::function<T(T)>& func, NDArray& target) {

    if(dataType() != DataTypeUtils::fromT<T>())
        throw std::runtime_error("NDArray::applyLambda<T> method: wrong template parameter T, its type should be the same as type of this array!");
    if(dataType() != target.dataType())
        throw std::runtime_error("NDArray::applyLambda<T> method: types of this and target array should match !");

    auto f = this->bufferAsT<T>();
    auto z = target.bufferAsT<T>();

    if (this->ordering() == target.ordering() && (this->ews() == 1 && target.ews() == 1)) {

        auto loop = PRAGMA_THREADS_FOR {
            for (auto e = start; e < stop; e += increment)
                z[e] = func(f[e]);
        };

        samediff::Threads::parallel_for(loop, 0, _length);
    } else {
        if (f == z) {

            auto loop = PRAGMA_THREADS_FOR {
                for (auto e = start; e < stop; e += increment) {
                    auto xOffset = this->getOffset(e);

                    f[xOffset] = func(f[xOffset]);
                }
            };

            samediff::Threads::parallel_for(loop, 0, _length);
        } else {

            auto loop = PRAGMA_THREADS_FOR {
                for (auto e = start; e < stop; e += increment) {
                    auto xOffset = this->getOffset(e);
                    auto zOffset = target.getOffset(e);

                    z[zOffset] = func(f[xOffset]);
                }
            };

            samediff::Threads::parallel_for(loop, 0, _length);
        }
    }
}
template void NDArray::applyLambda(const std::function<double(double)>& func, NDArray& target);
template void NDArray::applyLambda(const std::function<float(float)>& func, NDArray& target);
template void NDArray::applyLambda(const std::function<float16(float16)>& func, NDArray& target);
template void NDArray::applyLambda(const std::function<bfloat16(bfloat16)>& func, NDArray& target);
template void NDArray::applyLambda(const std::function<Nd4jLong(Nd4jLong)>& func, NDArray& target);
template void NDArray::applyLambda(const std::function<int16_t(int16_t)>& func, NDArray& target);
template void NDArray::applyLambda(const std::function<int32_t(int32_t)>& func, NDArray& target);
template void NDArray::applyLambda(const std::function<uint8_t(uint8_t)>& func, NDArray& target);
template void NDArray::applyLambda(const std::function<uint16_t(uint16_t)>& func, NDArray& target);
template void NDArray::applyLambda(const std::function<uint32_t(uint32_t)>& func, NDArray& target);
template void NDArray::applyLambda(const std::function<uint64_t(uint64_t)>& func, NDArray& target);
template void NDArray::applyLambda(const std::function<int8_t(int8_t)>& func, NDArray& target);
template void NDArray::applyLambda(const std::function<bool(bool)>& func, NDArray& target);

//////////////////////////////////////////////////////////////////////////
template<typename T>
void NDArray::applyIndexedLambda(const std::function<T(Nd4jLong, T)>& func, NDArray& target) {

    if(dataType() != DataTypeUtils::fromT<T>())
        throw std::runtime_error("NDArray::applyIndexedLambda<T> method: wrong template parameter T, its type should be the same as type of this array!");
    if(dataType() != target.dataType())
        throw std::runtime_error("NDArray::applyIndexedLambda<T> method: types of this and target array should match !");

    auto f = this->bufferAsT<T>();
    auto z = target.bufferAsT<T>();

    if (this->ordering() == target.ordering() && (this->ews() == 1 && target.ews() == 1)) {

        auto loop = PRAGMA_THREADS_FOR {
            for (auto e = start; e < stop; e += increment)
                z[e] = func(e, f[e]);
        };

        samediff::Threads::parallel_for(loop, 0, _length);
    } else {
        if (f == z) {

            auto loop = PRAGMA_THREADS_FOR {
                for (auto e = start; e < stop; e += increment) {
                    auto xOffset = this->getOffset(e);

                    f[xOffset] = func(e, f[xOffset]);
                }
            };

            samediff::Threads::parallel_for(loop, 0, _length);
        } else {

            auto loop = PRAGMA_THREADS_FOR {
                for (auto e = start; e < stop; e += increment) {
                    auto xOffset = this->getOffset(e);
                    auto zOffset = target.getOffset(e);

                    z[zOffset] = func(e, f[xOffset]);
                }
            };

            samediff::Threads::parallel_for(loop, 0, _length);
        }
    }
}
template void NDArray::applyIndexedLambda(const std::function<double(Nd4jLong, double)>& func, NDArray& target);
template void NDArray::applyIndexedLambda(const std::function<float(Nd4jLong, float)>& func, NDArray& target);
template void NDArray::applyIndexedLambda(const std::function<float16(Nd4jLong, float16)>& func, NDArray& target);
template void NDArray::applyIndexedLambda(const std::function<bfloat16(Nd4jLong, bfloat16)>& func, NDArray& target);
template void NDArray::applyIndexedLambda(const std::function<Nd4jLong(Nd4jLong, Nd4jLong)>& func, NDArray& target);
template void NDArray::applyIndexedLambda(const std::function<int(Nd4jLong, int)>& func, NDArray& target);
template void NDArray::applyIndexedLambda(const std::function<int16_t(Nd4jLong, int16_t)>& func, NDArray& target);
template void NDArray::applyIndexedLambda(const std::function<uint8_t (Nd4jLong, uint8_t)>& func, NDArray& target);
template void NDArray::applyIndexedLambda(const std::function<uint16_t (Nd4jLong, uint16_t)>& func, NDArray& target);
template void NDArray::applyIndexedLambda(const std::function<uint32_t (Nd4jLong, uint32_t)>& func, NDArray& target);
template void NDArray::applyIndexedLambda(const std::function<uint64_t (Nd4jLong, uint64_t)>& func, NDArray& target);
template void NDArray::applyIndexedLambda(const std::function<int8_t(Nd4jLong, int8_t)>& func, NDArray& target);
template void NDArray::applyIndexedLambda(const std::function<bool(Nd4jLong, bool)>& func, NDArray& target);

//////////////////////////////////////////////////////////////////////////
template<typename T>
void NDArray::applyIndexedPairwiseLambda(NDArray& other, const std::function<T(Nd4jLong, T, T)>& func, NDArray& target) {

    if(dataType() != DataTypeUtils::fromT<T>())
        throw std::runtime_error("NDArray::applyIndexedPairwiseLambda<T> method: wrong template parameter T, its type should be the same as type of this array!");
    if(dataType() != target.dataType())
        throw std::runtime_error("NDArray::applyIndexedPairwiseLambda<T> method: types of this and target array should match !");
    if (this->lengthOf() != other.lengthOf()) {
        nd4j_printf("applyIndexedPairwiseLambda requires both operands to have the same shape\n","");
        throw std::runtime_error("Shapes mismach");
    }

    auto f = this->bufferAsT<T>();
    auto s = other.bufferAsT<T>();
    auto z = target.bufferAsT<T>();

    if (this->ordering() == other.ordering() && this->ordering() == target.ordering() && (this->ews() == 1 && target.ews() == 1) && this->ews() == other.ews()) {

        auto loop = PRAGMA_THREADS_FOR {
            for (auto e = start; e < stop; e += increment)
                z[e] = func((Nd4jLong) e, f[e], s[e]);
        };

        samediff::Threads::parallel_for(loop, 0, _length);
    } else {
        if (f == z) {

            auto loop = PRAGMA_THREADS_FOR {
                for (auto e = start; e < stop; e += increment) {
                    auto xOffset = this->getOffset(e);
                    auto yOffset = other.getOffset(e);

                    f[xOffset] = func((Nd4jLong) e, f[xOffset], s[yOffset]);
                }
            };

            samediff::Threads::parallel_for(loop, 0, _length);
        } else {

            auto loop = PRAGMA_THREADS_FOR {
                for (auto e = start; e < stop; e += increment) {
                    auto xOffset = this->getOffset(e);
                    auto yOffset = other.getOffset(e);
                    auto zOffset = target.getOffset(e);

                    z[zOffset] = func((Nd4jLong) e, f[xOffset], s[yOffset]);
                }
            };

            samediff::Threads::parallel_for(loop, 0, _length);
        }
    }
}
template void NDArray::applyIndexedPairwiseLambda(NDArray& other, const std::function<double (Nd4jLong, double, double)>& func, NDArray& target);
template void NDArray::applyIndexedPairwiseLambda(NDArray& other, const std::function<float (Nd4jLong, float, float)>& func, NDArray& target);
template void NDArray::applyIndexedPairwiseLambda(NDArray& other, const std::function<float16 (Nd4jLong, float16, float16)>& func, NDArray& target);
template void NDArray::applyIndexedPairwiseLambda(NDArray& other, const std::function<bfloat16 (Nd4jLong, bfloat16, bfloat16)>& func, NDArray& target);
template void NDArray::applyIndexedPairwiseLambda(NDArray& other, const std::function<Nd4jLong (Nd4jLong, Nd4jLong, Nd4jLong)>& func, NDArray& target);
template void NDArray::applyIndexedPairwiseLambda(NDArray& other, const std::function<int (Nd4jLong, int, int)>& func, NDArray& target);
template void NDArray::applyIndexedPairwiseLambda(NDArray& other, const std::function<int16_t (Nd4jLong, int16_t, int16_t)>& func, NDArray& target);
template void NDArray::applyIndexedPairwiseLambda(NDArray& other, const std::function<uint8_t (Nd4jLong, uint8_t, uint8_t)>& func, NDArray& target);
template void NDArray::applyIndexedPairwiseLambda(NDArray& other, const std::function<uint16_t (Nd4jLong, uint16_t, uint16_t)>& func, NDArray& target);
template void NDArray::applyIndexedPairwiseLambda(NDArray& other, const std::function<uint32_t (Nd4jLong, uint32_t, uint32_t)>& func, NDArray& target);
template void NDArray::applyIndexedPairwiseLambda(NDArray& other, const std::function<uint64_t (Nd4jLong, uint64_t, uint64_t)>& func, NDArray& target);
template void NDArray::applyIndexedPairwiseLambda(NDArray& other, const std::function<int8_t (Nd4jLong, int8_t, int8_t)>& func, NDArray& target);
template void NDArray::applyIndexedPairwiseLambda(NDArray& other, const std::function<bool (Nd4jLong, bool, bool)>& func, NDArray& target);