elementwise_functor.h

/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.

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. */

#pragma once

#include "paddle/fluid/platform/complex.h"
#include "paddle/phi/core/utils/array.h"
#include "paddle/phi/kernels/funcs/elementwise_functor.h"

namespace paddle {
namespace operators {

// Define the binary functors used in elementwise ops.
// Note: InverseXxxFunctor is needed when calling ElementwiseComputeEx on CPU.

// Add
template <typename T>
using AddFunctor = phi::funcs::AddFunctor<T>;

template <typename T>
using InverseAddFunctor = phi::funcs::InverseAddFunctor<T>;

// Subtract
template <typename T>
using SubFunctor = phi::funcs::SubtractFunctor<T>;

template <typename T>
using InverseSubFunctor = phi::funcs::InverseSubtractFunctor<T>;

// Multiply
template <typename T>
using MulFunctor = phi::funcs::MultiplyFunctor<T>;

template <typename T>
using InverseMulFunctor = phi::funcs::InverseMultiplyFunctor<T>;

// Divide
template <typename T>
using DivFunctor = phi::funcs::DivideFunctor<T>;

template <typename T>
using InverseDivFunctor = phi::funcs::InverseDivideFunctor<T>;

// Floor Divide
template <typename T>
struct FloorDivFunctor {
  inline HOSTDEVICE T operator()(const T a, const T b) const {
    PADDLE_ENFORCE(b != 0, DIV_ERROR_INFO);
    return static_cast<T>(std::trunc(a / b));
  }
};

template <typename T>
struct InverseFloorDivFunctor {
  inline HOSTDEVICE T operator()(const T a, const T b) const {
    PADDLE_ENFORCE(a != 0, DIV_ERROR_INFO);
    return static_cast<T>(std::trunc(b / a));
  }
};

#undef DIV_ERROR_INFO

// Maximum
template <typename T>
struct MaxFunctor {
  inline HOSTDEVICE T operator()(const T a, const T b) const {
    return a > b ? a : b;
  }
};

// Minmum
template <typename T>
struct MinFunctor {
  inline HOSTDEVICE T operator()(const T a, const T b) const {
    return a < b ? a : b;
  }
};

template <typename T>
using Complex = paddle::platform::complex<T>;

// Fmax
template <typename T>
struct FMaxFunctor {
  inline HOSTDEVICE T operator()(const T a, const T b) const {
    return std::fmax(a, b);
  }
};

template <>
struct FMaxFunctor<paddle::platform::float16> {
  inline HOSTDEVICE paddle::platform::float16 operator()(
      const paddle::platform::float16 a,
      const paddle::platform::float16 b) const {
    float float_a = static_cast<float>(a);
    float float_b = static_cast<float>(b);
    auto result = std::fmax(float_a, float_b);
    return static_cast<paddle::platform::float16>(result);
  }
};

template <>
struct FMaxFunctor<int> {
  inline HOSTDEVICE int operator()(const int a, const int b) const {
    float float_a = static_cast<float>(a);
    float float_b = static_cast<float>(b);
    auto result = std::fmax(float_a, float_b);
    return std::lrint(result);
  }
};

template <>
struct FMaxFunctor<int64_t> {
  inline HOSTDEVICE int64_t operator()(const int64_t a, const int64_t b) const {
    double double_a = static_cast<double>(a);
    double double_b = static_cast<double>(b);
    auto result = std::fmax(double_a, double_b);
    return std::llrint(result);
  }
};

// Fmin
template <typename T>
struct FMinFunctor {
  inline HOSTDEVICE T operator()(const T a, const T b) const {
    return std::fmin(a, b);
  }
};

template <>
struct FMinFunctor<paddle::platform::float16> {
  inline HOSTDEVICE paddle::platform::float16 operator()(
      const paddle::platform::float16 a,
      const paddle::platform::float16 b) const {
    float float_a = static_cast<float>(a);
    float float_b = static_cast<float>(b);
    auto result = std::fmin(float_a, float_b);
    return static_cast<paddle::platform::float16>(result);
  }
};

template <>
struct FMinFunctor<int> {
  inline HOSTDEVICE int operator()(const int a, const int b) const {
    float float_a = static_cast<float>(a);
    float float_b = static_cast<float>(b);
    auto result = std::fmin(float_a, float_b);
    return std::lrint(result);
  }
};

template <>
struct FMinFunctor<int64_t> {
  inline HOSTDEVICE int64_t operator()(const int64_t a, const int64_t b) const {
    double double_a = static_cast<double>(a);
    double double_b = static_cast<double>(b);
    auto result = std::fmin(double_a, double_b);
    return std::llrint(result);
  }
};

template <typename T>
struct MinGradXFunctor {
  inline HOSTDEVICE T operator()(const T x, const T y, const T dout) const {
    return dout * static_cast<T>(x < y);
  }
};
template <typename T>
struct MinGradYFunctor {
  inline HOSTDEVICE T operator()(const T x, const T y, const T dout) const {
    return dout * static_cast<T>(x >= y);
  }
};

template <typename InT, typename OutT>
struct MinGradXYFunctor {
  inline HOSTDEVICE phi::Array<OutT, 2> operator()(const InT x, const InT y,
                                                   const InT dout) {
    phi::Array<OutT, 2> outs;
    // dx = dout * (x < y)
    outs[0] = static_cast<OutT>(dout * static_cast<InT>(x < y));
    // dy = dout * (x >= y)
    outs[1] = static_cast<OutT>(dout * static_cast<InT>(x >= y));
    return outs;
  }
};

template <typename T>
struct MulGradFunctor {
  inline HOSTDEVICE T operator()(const T a, const T b) const { return a * b; }
};
template <typename T>
struct MulGradFunctor<Complex<T>> {
  inline HOSTDEVICE Complex<T> operator()(const Complex<T> a,
                                          const Complex<T> b) const {
    Complex<T> b_conj(b.real, -b.imag);
    return a * b_conj;
  }
};

template <typename InT, typename OutT>
struct MulGradXYFunctor {
  inline HOSTDEVICE phi::Array<OutT, 2> operator()(const InT a, const InT b,
                                                   const InT c) {
    phi::Array<OutT, 2> outs;
    // dx = dout * y
    outs[0] = a * b;
    // dy = dout * x
    outs[1] = a * c;
    return outs;
  }
};

template <typename InT, typename OutT>
struct MulGradXYFunctor<Complex<InT>, Complex<OutT>> {
  inline HOSTDEVICE phi::Array<Complex<OutT>, 2> operator()(
      const Complex<InT> a, const Complex<InT> b, const Complex<InT> c) {
    phi::Array<Complex<OutT>, 2> outs;
    // dx = dout * y
    Complex<InT> b_conj(b.real, -b.imag);
    outs[0] = a * b_conj;
    // dy = dout * x
    Complex<InT> c_conj(c.real, -c.imag);
    outs[1] = a * c_conj;
    return outs;
  }
};

// Ternary compare
template <typename T>
struct MaxGradXFunctor {
  inline HOSTDEVICE T operator()(const T x, const T y, const T dout) const {
    return dout * static_cast<T>(x > y);
  }
};
template <typename T>
struct MaxGradYFunctor {
  inline HOSTDEVICE T operator()(const T x, const T y, const T dout) const {
    return dout * static_cast<T>(x <= y);
  }
};

template <typename InT, typename OutT>
struct MaxGradXYFunctor {
  inline HOSTDEVICE phi::Array<OutT, 2> operator()(const InT x, const InT y,
                                                   const InT dout) {
    phi::Array<OutT, 2> outs;
    // dx = dout * (x > y)
    outs[0] = static_cast<OutT>(dout * static_cast<InT>(x > y));
    // dy = dout * (x <= y)
    outs[1] = static_cast<OutT>(dout * static_cast<InT>(x <= y));
    return outs;
  }
};

}  // namespace operators
}  // namespace paddle