seq_expand_op.cc 4.4 KB
Newer Older
W
wanghaoshuang 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
/* 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. */

#include "paddle/operators/seq_expand_op.h"

namespace paddle {
namespace operators {

using framework::Tensor;

class SeqExpandOp : public framework::OperatorWithKernel {
 public:
  using framework::OperatorWithKernel::OperatorWithKernel;

 protected:
  void InferShape(framework::InferShapeContext* ctx) const override {
    PADDLE_ENFORCE(ctx->HasInput("X"),
                   "Input(X) of SeqExpandOp should not be null.");
    PADDLE_ENFORCE(ctx->HasOutput("Out"),
31
                   "Output(Out) of SeqExpandOp should not be null.");
W
wanghaoshuang 已提交
32 33 34 35 36 37
    PADDLE_ENFORCE(
        ctx->HasInput("Y"),
        "Input(Y) of SeqExpandOp should not be null while repeat == 0.");
    framework::DDim out_dim;
    out_dim = ctx->GetInputDim("Y");
    ctx->ShareLoD("Y", "Out");
W
wanghaoshuang 已提交
38 39 40 41 42 43 44 45 46
    ctx->SetOutputDim("Out", out_dim);
  }
};

class SeqExpandOpMaker : public framework::OpProtoAndCheckerMaker {
 public:
  SeqExpandOpMaker(framework::OpProto* proto,
                   framework::OpAttrChecker* op_checker)
      : OpProtoAndCheckerMaker(proto, op_checker) {
W
wanghaoshuang 已提交
47 48 49 50 51 52 53 54 55
    AddInput("X",
             "(Tensor or LoDTensor) The input('X') of this operator can be a "
             "LoDTensor or a base Tensor.");
    AddInput("Y",
             "(LoDTensor)The reference input('Y') of seq_expand op."
             "It must be a LoDTensor with k-level(k>0)."
             "Input(X) will be expanded according to LOD of input(Y)."
             "The element numbers of last level in input('Y') "
             "must be equal to dims[0] of input('X').");
W
wanghaoshuang 已提交
56 57
    AddOutput("Out",
              "The output of seq_expand op."
W
wanghaoshuang 已提交
58
              "The lod of output will be as same as input(Y)'s lod.");
W
wanghaoshuang 已提交
59
    AddComment(R"DOC(
W
wanghaoshuang 已提交
60
Expand input(X) according to LOD of input(Y).
W
wanghaoshuang 已提交
61

W
wanghaoshuang 已提交
62
Case 1:
W
wanghaoshuang 已提交
63

W
wanghaoshuang 已提交
64 65 66 67 68 69 70 71 72 73 74 75 76
Given 2-level a LoDTensor input(X)
    X.lod = [[0,       2, 3],
             [0, 1,    3, 4]]
    X.data = [a, b, c, d]
    X.dims = [4, 1]
and input(Y)
    Y.lod = [[0,    2,    4],
             [0, 3, 6, 7, 8]]
then we get 2-level LoDTensor
    Out.lod = [[0,                2,    4],
               [0,       3,       6, 7, 8]]
    Out.data = [a, a, a, b, b, b, c, d]
    Out.dims = [8, 1]
W
wanghaoshuang 已提交
77 78 79

Case 2:

W
wanghaoshuang 已提交
80 81 82 83 84 85 86 87 88 89
Given a 0-level LoDTensor input(X)
    X.data = [a, b, c]
    X.lod = NULL
    X.dims = [3, 1]
and input(Y)
    Y.lod = [[0, 2, 3, 6]]
then we get 1-level LoDTensor
    Out.lod = [[0,    2, 3,      6]]
    Out.data = [a, a, b, c, c, c]
    Out.dims = [6, 1]
W
wanghaoshuang 已提交
90 91 92

Case 3:

W
wanghaoshuang 已提交
93 94
Given a 0-level LoDTensor input(X)
    X.data = [[a, b], [c, d], [e, f]]
W
wanghaoshuang 已提交
95
    X.lod = NULL
W
wanghaoshuang 已提交
96 97 98
    X.dims = [3, 2]
and input(Y)
    Y.lod = [[0, 2, 3, 6]]
W
wanghaoshuang 已提交
99
then we get 1-level LoDTensor
W
wanghaoshuang 已提交
100 101 102 103
    Out.lod = [[0,           2,     3,                     6]]
    Out.data = [[a,b], [a,b] [c,d], [e, f], [e, f], [e, f]]
    Out.dims = [6, 2]

W
wanghaoshuang 已提交
104 105 106 107 108 109 110 111 112 113 114 115

)DOC");
  }
};

class SeqExpandOpGrad : public framework::OperatorWithKernel {
 public:
  using framework::OperatorWithKernel::OperatorWithKernel;

 protected:
  void InferShape(framework::InferShapeContext* ctx) const override {
    PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null");
W
wanghaoshuang 已提交
116
    PADDLE_ENFORCE(ctx->HasInput("Out"), "Input(Out) should not be null");
W
wanghaoshuang 已提交
117 118 119 120 121 122 123 124 125 126 127 128 129 130
    PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
                   "Input(Out@GRAD) should not be null");
    auto x_dims = ctx->GetInputDim("X");
    auto x_grad_name = framework::GradVarName("X");
    if (ctx->HasOutput(x_grad_name)) {
      ctx->SetOutputDim(x_grad_name, x_dims);
    }
  }
};

}  // namespace operators
}  // namespace paddle

namespace ops = paddle::operators;
W
wanghaoshuang 已提交
131 132
REGISTER_OP(seq_expand, ops::SeqExpandOp, ops::SeqExpandOpMaker,
            seq_expand_grad, ops::SeqExpandOpGrad);
W
wanghaoshuang 已提交
133 134 135 136 137
REGISTER_OP_CPU_KERNEL(seq_expand,
                       ops::SeqExpandKernel<paddle::platform::CPUPlace, float>);
REGISTER_OP_CPU_KERNEL(
    seq_expand_grad,
    ops::SeqExpandGradKernel<paddle::platform::CPUPlace, float>);