unpool_op.cc 5.7 KB
Newer Older
S
sweetsky0901 已提交
1
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
2 3 4 5 6 7 8 9 10 11 12 13

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
Indicesou 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. */
S
sweetsky0901 已提交
14 15 16 17 18 19 20

#include "paddle/operators/unpool_op.h"
namespace paddle {
namespace operators {

class Unpool2dOpMaker : public framework::OpProtoAndCheckerMaker {
 public:
21
  Unpool2dOpMaker(OpProto* proto, OpAttrChecker* op_checker)
S
sweetsky0901 已提交
22
      : OpProtoAndCheckerMaker(proto, op_checker) {
S
sweetsky0901 已提交
23 24
    AddInput(
        "X",
S
sweetsky0901 已提交
25 26 27
        "(Tensor) The input tensor of unpool operator. "
        "The format of input tensor is NCHW. Where N is batch size, C is the "
        "number of channels, H and W is the height and width of feature.");
S
sweetsky0901 已提交
28 29
    AddInput(
        "Indices",
S
sweetsky0901 已提交
30 31 32
        "(Tensor) The input tensor of the indices given out by MaxPool2d. "
        "The format of input tensor is NCHW. Where N is batch size, C is the "
        "number of channels, H and W is the height and width of feature.");
S
sweetsky0901 已提交
33
    AddOutput("Out",
S
sweetsky0901 已提交
34 35 36 37 38
              "(Tensor) The output tensor of unpool operator."
              "The format of output tensor is also NCHW."
              "Where N is batch size, C is "
              "the number of channels, H and W is the height and "
              "width of feature.");
S
sweetsky0901 已提交
39 40
    AddAttr<std::vector<int>>(
        "ksize",
S
sweetsky0901 已提交
41
        "(vector), the unpooling window size(height, width) "
S
sweetsky0901 已提交
42
        "of unpooling operator.");
S
sweetsky0901 已提交
43 44 45
    AddAttr<std::vector<int>>("strides",
                              "(vector, default:{1, 1}), "
                              "strides (height, width) of unpooling operator.")
S
sweetsky0901 已提交
46
        .SetDefault({1, 1});
S
sweetsky0901 已提交
47 48 49
    AddAttr<std::vector<int>>("paddings",
                              "(vector defalut:{0,0}), "
                              "paddings (height, width) of unpooling operator.")
S
sweetsky0901 已提交
50
        .SetDefault({0, 0});
S
sweetsky0901 已提交
51 52
    AddAttr<std::string>(
        "unpooling_type",
S
sweetsky0901 已提交
53 54
        "(string), unpooling type, can be \"max\" for max-unpooling ")
        .InEnum({"max"});
S
sweetsky0901 已提交
55
    AddComment(R"DOC(
Y
ying 已提交
56 57 58 59 60 61 62 63 64
"Input shape: $(N, C_{in}, H_{in}, W_{in})$, 
Output shape: $(N, C_{out}, H_{out}, W_{out})$
Where
$$
H_{out} = (H_{in}−1) * strides[0] − 2 * paddings[0] + ksize[0] \\
W_{out} = (W_{in}−1) * strides[1] − 2 * paddings[1] + ksize[1]
$$
Paper: http://www.matthewzeiler.com/wp-content/uploads/2017/07/iccv2011.pdf
)DOC");
S
sweetsky0901 已提交
65 66 67 68
  }
};

int OutputSize(int input_size, int ksize, int padding, int stride) {
S
sweetsky0901 已提交
69
  int output_size = (input_size - 1) * stride - 2 * padding + ksize;
S
sweetsky0901 已提交
70 71 72 73
  return output_size;
}

class UnpoolOp : public framework::OperatorWithKernel {
S
sweetsky0901 已提交
74 75
 protected:
  framework::OpKernelType GetKernelType(
S
sweetsky0901 已提交
76 77 78
      const framework::ExecutionContext& ctx) const override {
    return framework::OpKernelType(
        framework::ToDataType(ctx.Input<framework::Tensor>("X")->type()),
S
sweetsky0901 已提交
79
        ctx.device_context());
S
sweetsky0901 已提交
80
  }
S
sweetsky0901 已提交
81

S
sweetsky0901 已提交
82 83 84
 public:
  using framework::OperatorWithKernel::OperatorWithKernel;
  void InferShape(framework::InferShapeContext* ctx) const override {
S
sweetsky0901 已提交
85 86 87 88 89
    PADDLE_ENFORCE(ctx->HasInput("X"),
                   "Input(X) of UnpoolOp"
                   "should not be null.");
    PADDLE_ENFORCE(ctx->HasInput("Indices"),
                   "Input(Indices) of UnpoolOp"
S
sweetsky0901 已提交
90
                   "should not be null.");
S
sweetsky0901 已提交
91
    PADDLE_ENFORCE(ctx->HasOutput("Out"),
S
sweetsky0901 已提交
92
                   "Output(Out) of UnpoolOp should not be null.");
S
sweetsky0901 已提交
93 94
    auto in_x_dims = ctx->GetInputDim("X");
    auto in_y_dims = ctx->GetInputDim("Indices");
S
sweetsky0901 已提交
95 96
    std::string unpooling_type =
        ctx->Attrs().Get<std::string>("unpooling_type");
S
sweetsky0901 已提交
97 98
    std::vector<int> ksize = ctx->Attrs().Get<std::vector<int>>("ksize");
    std::vector<int> strides = ctx->Attrs().Get<std::vector<int>>("strides");
S
sweetsky0901 已提交
99
    std::vector<int> paddings = ctx->Attrs().Get<std::vector<int>>("paddings");
S
sweetsky0901 已提交
100
    PADDLE_ENFORCE(in_x_dims.size() == 4,
S
sweetsky0901 已提交
101
                   "Unpooling intput must be of 4-dimensional.");
S
sweetsky0901 已提交
102 103 104 105
    PADDLE_ENFORCE_EQ(in_x_dims, in_y_dims);
    std::vector<int64_t> output_shape({in_x_dims[0], in_x_dims[1]});
    for (size_t i = 0; i < ksize.size(); ++i) {
      output_shape.push_back(
S
sweetsky0901 已提交
106
          OutputSize(in_x_dims[i + 2], ksize[i], paddings[i], strides[i]));
S
sweetsky0901 已提交
107 108 109
    }
    ctx->SetOutputDim("Out", framework::make_ddim(output_shape));
  }
S
sweetsky0901 已提交
110 111 112
};

class UnpoolOpGrad : public framework::OperatorWithKernel {
S
sweetsky0901 已提交
113 114
 protected:
  framework::OpKernelType GetKernelType(
S
sweetsky0901 已提交
115 116
      const framework::ExecutionContext& ctx) const override {
    return framework::OpKernelType(
S
sweetsky0901 已提交
117 118
        framework::ToDataType(ctx.Input<framework::Tensor>("X")->type()),
        ctx.device_context());
S
sweetsky0901 已提交
119
  }
S
sweetsky0901 已提交
120

S
sweetsky0901 已提交
121 122 123 124 125
 public:
  using framework::OperatorWithKernel::OperatorWithKernel;
  void InferShape(framework::InferShapeContext* ctx) const override {
    PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) must not be null.");
    PADDLE_ENFORCE(ctx->HasOutput(framework::GradVarName("X")),
S
sweetsky0901 已提交
126
                   "Input(X@GRAD) should not be null.");
S
sweetsky0901 已提交
127 128
    ctx->SetOutputDim(framework::GradVarName("X"), ctx->GetInputDim("X"));
  }
S
sweetsky0901 已提交
129
};
S
sweetsky0901 已提交
130 131
}  // namespace operators
}  // namespace paddle
S
sweetsky0901 已提交
132 133

namespace ops = paddle::operators;
S
sweetsky0901 已提交
134
REGISTER_OP(unpool, ops::UnpoolOp, ops::Unpool2dOpMaker, unpool_grad,
S
sweetsky0901 已提交
135
            ops::UnpoolOpGrad);
S
sweetsky0901 已提交
136
REGISTER_OP_CPU_KERNEL(
Q
QI JUN 已提交
137 138 139 140 141 142
    unpool, ops::UnpoolKernel<paddle::platform::CPUDeviceContext, float>,
    ops::UnpoolKernel<paddle::platform::CPUDeviceContext, double>);
REGISTER_OP_CPU_KERNEL(
    unpool_grad,
    ops::UnpoolGradKernel<paddle::platform::CPUDeviceContext, float>,
    ops::UnpoolGradKernel<paddle::platform::CPUDeviceContext, double>);