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Paddle/paddle/fluid/operators/conj_op.h

86 lines
2.8 KiB

// 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