rowwise_add_op.h 2.2 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.

   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
16
#include "paddle/operators/type_alias.h"
17 18 19 20

namespace paddle {
namespace operators {

Q
qijun 已提交
21
template <typename Place, typename T>
D
dongzhihong 已提交
22
class RowwiseAddKernel : public OpKernel {
23
 public:
24 25
  void Compute(const ExecutionContext& context) const override {
    auto out = context.Output<Tensor>(0);
Q
qijun 已提交
26
    out->mutable_data<T>(context.GetPlace());
Q
qijun 已提交
27

28 29
    auto input = EigenMatrix<T>::From(*context.Input<Tensor>(0));
    auto bias = EigenVector<T>::From(*context.Input<Tensor>(1));
30
    auto output = EigenMatrix<T>::From(*out);
Q
qijun 已提交
31 32 33 34 35

    const int bias_size = bias.dimension(0);
    const int rest_size = input.size() / bias_size;
    Eigen::DSizes<int, 1> one_d(input.size());
    Eigen::DSizes<int, 1> bcast(rest_size);
36
    output.reshape(one_d).device(context.GetEigenDevice<Place>()) =
Q
qijun 已提交
37
        input.reshape(one_d) + bias.broadcast(bcast).reshape(one_d);
38 39 40
  }
};

D
dongzhihong 已提交
41
template <typename Place, typename T>
D
dongzhihong 已提交
42
class RowwiseAddGradKernel : public OpKernel {
43
 public:
D
dongzhihong 已提交
44 45 46 47 48 49 50 51 52 53
  void Compute(const ExecutionContext& context) const override {
    auto XGrad = context.Output<Tensor>(0);
    auto bGrad = context.Output<Tensor>(1);
    XGrad->mutable_data<T>(context.GetPlace());
    bGrad->mutable_data<T>(context.GetPlace());

    // I, O, OG  => [X, b], [Out], [OutGrad]
    auto OutGrad = EigenMatrix<T>::From(*context.Input<Tensor>(3));
    EigenMatrix<T>::From(*XGrad).device(*(context.GetEigenDevice<Place>())) =
        OutGrad;
D
dongzhihong 已提交
54

D
dongzhihong 已提交
55 56 57 58 59
    // https://eigen.tuxfamily.org/dox/unsupported/TensorBase_8h_source.html
    EigenVector<T>::Flatten(*bGrad).device(*(context.GetEigenDevice<Place>())) =
        OutGrad.cumsum(1);  // colwise add
  }
};
60 61
}  // namespace operators
}  // namespace paddle