activation_impl.h

// Copyright (c) 2022 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/phi/core/dense_tensor.h"
#include "paddle/phi/kernels/funcs/activation_functor.h"
#include "paddle/phi/kernels/funcs/blas/blas.h"

#include "paddle/fluid/platform/device_context.h"

namespace phi {

#define ToString(x) #x

template <typename T, typename Context, typename Functor>
void ActivationImpl(const Context& dev_ctx,
                    const DenseTensor& X,
                    DenseTensor* Out,
                    const Functor& functor) {
  PADDLE_ENFORCE_NOT_NULL(Out,
                          errors::NotFound("Output Out should not be nullptr"));
  dev_ctx.template Alloc<T>(Out);
  auto x = phi::EigenVector<T>::Flatten(
      GET_DATA_SAFELY(&X, "Input", "X", "Activation"));
  auto out = phi::EigenVector<T>::Flatten(
      GET_DATA_SAFELY(Out, "Output", "Out", "Activation"));
  auto* place = dev_ctx.eigen_device();
  // use 32bit index to speed up computation
  bool use_32bit_index = out.size() < Eigen::NumTraits<int>::highest();
  bool is_gpu_place = paddle::platform::is_gpu_place(dev_ctx.GetPlace());
  if (use_32bit_index && is_gpu_place) {
    functor(*place, To32BitIndex(x), To32BitIndex(out));
  } else {
    functor(*place, x, out);
  }
}

template <typename T, typename Context>
void LogitKernel(const Context& dev_ctx,
                 const DenseTensor& x,
                 float eps,
                 DenseTensor* out) {
  dev_ctx.template Alloc<T>(out);

  auto eigen_out = EigenVector<T>::Flatten(*out);
  auto eigen_in = EigenVector<T>::Flatten(x);
  auto& place = *dev_ctx.eigen_device();
  auto eigen_p = EigenVector<T>::Flatten(*out);

  funcs::LogitFunctor<T> functor;
  functor(place, eigen_in, eigen_out, eigen_p, eps);
}

template <typename T, typename Context>
void PowKernel(const Context& dev_ctx,
               const DenseTensor& x,
               const Scalar& factor,
               DenseTensor* out) {
  PADDLE_ENFORCE_NOT_NULL(out,
                          errors::NotFound("Output Out should not be nullptr"));
  dev_ctx.template Alloc<T>(out);
  auto x_flatten = phi::EigenVector<T>::Flatten(
      GET_DATA_SAFELY(&x, "Input", "X", "Activation"));
  auto out_flatten = phi::EigenVector<T>::Flatten(
      GET_DATA_SAFELY(out, "Output", "Out", "Activation"));
  auto* place = dev_ctx.eigen_device();
  phi::funcs::PowFunctor<T> functor;
  auto attrs = functor.GetAttrs();
  *(attrs[0].second) = factor.to<float>();
  functor(*place, x_flatten, out_flatten);
}

}  // namespace phi