conj_op.h

// Copyright (c) 2020 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/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/platform/for_range.h"

namespace paddle {
namespace operators {
using Tensor = framework::Tensor;

template <typename T>
using EnableComplex =
    typename std::enable_if<std::is_same<T, platform::complex64>::value ||
                            std::is_same<T, platform::complex128>::value>::type;

template <typename T>
using DisableComplex = typename std::enable_if<
    !std::is_same<T, platform::complex64>::value &&
    !std::is_same<T, platform::complex128>::value>::type;

template <typename T, typename Enable = void>
struct ConjFunctor;

template <typename T>
struct ConjFunctor<T, EnableComplex<T>> {
  ConjFunctor(const T* input, int64_t numel, T* output)
      : input_(input), numel_(numel), output_(output) {}

  HOSTDEVICE void operator()(size_t idx) const {
    output_[idx] = T(input_[idx].real, -input_[idx].imag);
  }
  const T* input_;
  int64_t numel_;
  T* output_;
};

template <typename T>
struct ConjFunctor<T, DisableComplex<T>> {
  ConjFunctor(const T* input, int64_t numel, T* output)
      : input_(input), numel_(numel), output_(output) {}

  HOSTDEVICE void operator()(size_t idx) const { output_[idx] = input_[idx]; }
  const T* input_;
  int64_t numel_;
  T* output_;
};

template <typename DeviceContext, typename T>
class ConjKernel : public framework::OpKernel<T> {
 public:
  void Compute(const framework::ExecutionContext& context) const override {
    const Tensor* x = context.Input<Tensor>("X");
    Tensor* out = context.Output<Tensor>("Out");

    auto numel = x->numel();
    auto* x_data = x->data<T>();
    auto* out_data = out->mutable_data<T>(context.GetPlace(),
                                          size_t(x->numel() * sizeof(T)));

    auto& dev_ctx = context.template device_context<DeviceContext>();
    platform::ForRange<DeviceContext> for_range(dev_ctx, numel);
    ConjFunctor<T> functor(x_data, numel, out_data);
    for_range(functor);
  }
};

DECLARE_INPLACE_OP_INFERER(ConjOpInplaceInferer, {"X", "Out"});

}  // namespace operators
}  // namespace paddle