提交 f2ccc11f 编写于 作者: C chengduoZH

fix pool doc (pool_op.cc)

上级 c2c2d610
......@@ -32,10 +32,7 @@ class PoolOp : public framework::OperatorWithKernel {
"X(Input) of Pooling should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Out(Output) of Pooling should not be null.");
// PADDLE_ENFORCE_NOT_NULL(Attr<std::string>("poolingType"),
// "pooling_type should not be null.");
// PADDLE_ENFORCE_NOT_NULL(Attr<std::vector<int>>("ksize"), "ksize should
// not be null.");
auto in_X = ctx.Input<Tensor>("X");
auto out = ctx.Output<Tensor>("Out");
int global_pooling = Attr<int>("globalPooling");
......@@ -56,11 +53,15 @@ class PoolOp : public framework::OperatorWithKernel {
}
if (ksize.size() == 2) {
PADDLE_ENFORCE_EQ(strides.size(), 2, "Pool2DOp strides should be 2-D.");
PADDLE_ENFORCE_EQ(paddings.size(), 2, "Pool2DOp paddings should be 2-D.");
PADDLE_ENFORCE_EQ(strides.size(), 2,
"Pool2DOp strides size should be 2 elements.");
PADDLE_ENFORCE_EQ(paddings.size(), 2,
"Pool2DOp paddings size should be 2 elements");
} else {
PADDLE_ENFORCE_EQ(strides.size(), 3, "Pool3DOp strides should be 3-D.");
PADDLE_ENFORCE_EQ(paddings.size(), 3, "Pool3DOp paddings should be 3-D.");
PADDLE_ENFORCE_EQ(strides.size(), 3,
"Pool3DOp strides should be 3 elements.");
PADDLE_ENFORCE_EQ(paddings.size(), 3,
"Pool3DOp paddings should be 3 elements.");
}
std::vector<int64_t> output_shape({in_X->dims()[0], in_X->dims()[1]});
for (size_t i = 0; i < ksize.size(); ++i) {
......@@ -83,76 +84,84 @@ class PoolOpGrad : public framework::OperatorWithKernel {
}
};
class Pool3dOpMaker : public framework::OpProtoAndCheckerMaker {
class Pool2dOpMaker : public framework::OpProtoAndCheckerMaker {
public:
Pool3dOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
Pool2dOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput(
"X",
"The input tensor of pooling operator. "
"The format of input tensor is NCDHW. Where N is batch size, C is the "
"number of channels, D, H and W is the depth, height and width of "
"image.");
"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 image.");
AddOutput("Out",
"The output tensor of pooling operator."
"The format of output tensor is also NCDHW.");
"The format of output tensor is also NCHW.");
AddAttr<std::string>("poolingType",
"poolingType of pooling operator.['max' or 'ave']");
"poolingType of pooling operator."
"str constant equal to 'max' or 'ave'");
AddAttr<std::vector<int>>(
"ksize", "pooling size(depth, height, width) of pooling operator.");
AddAttr<int>("globalPooling",
"default 0"
"whether to use the globalPooling.")
"ksize", "pooling size(height, width) of pooling operator.");
AddAttr<int>(
"globalPooling",
"whether to use the globalPooling."
"int constant equal to 0 or 1"
"default 0"
"If globalPooling = 1, ksize is ignored and need not be specified.")
.SetDefault(0);
AddAttr<std::vector<int>>(
"strides",
"default {1,1,1}"
"strides(depth, height, width) of pooling operator.")
.SetDefault({1, 1, 1});
AddAttr<std::vector<int>>(
"paddings",
"default {0,0,0}"
"paddings(depth, height, width) of pooling operator.")
.SetDefault({0, 0, 0});
AddAttr<std::vector<int>>("strides",
"strides(height, width) of pooling operator."
"default {1,1}")
.SetDefault({1, 1});
AddAttr<std::vector<int>>("paddings",
"paddings(height, width) of pooling operator."
"default {0,0}")
.SetDefault({0, 0});
AddComment(R"DOC(
The pooling3d operation calculates the output based on
The pooling2d operation calculates the output based on
the input, poolingType and ksize, strides, paddings parameters.
)DOC");
}
};
class Pool2dOpMaker : public framework::OpProtoAndCheckerMaker {
class Pool3dOpMaker : public framework::OpProtoAndCheckerMaker {
public:
Pool2dOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
Pool3dOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput(
"X",
"The input tensor of pooling 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 image.");
AddInput("X",
"The input tensor of pooling operator. "
"The format of input tensor is NCDHW. Where N is batch size, C is "
"the "
"number of channels, D, H and W is the depth, height and width of "
"image.");
AddOutput("Out",
"The output tensor of pooling operator."
"The format of output tensor is also NCHW.");
"The format of output tensor is also NCDHW.");
AddAttr<std::string>("poolingType",
"poolingType of pooling operator.['max' or 'ave']");
"poolingType of pooling operator."
"str constant equal to 'max' or 'ave'");
AddAttr<std::vector<int>>(
"ksize", "pooling size(height, width) of pooling operator.");
AddAttr<int>("globalPooling",
"default 0"
"whether to use the globalPooling.[0 or 1]")
"ksize", "pooling size(depth, height, width) of pooling operator.");
AddAttr<int>(
"globalPooling",
"whether to use the globalPooling."
"int constant equal to 0 or 1"
"default 0"
"If globalPooling = 1, ksize is ignored and need not be specified.")
.SetDefault(0);
AddAttr<std::vector<int>>("strides",
"default {1, 1}"
"strides(height, width) of pooling operator.")
.SetDefault({1, 1});
AddAttr<std::vector<int>>("paddings",
"default {0, 0}"
"paddings(height, width) of pooling operator.")
.SetDefault({0, 0});
AddAttr<std::vector<int>>(
"strides",
"strides(depth, height, width) of pooling operator."
"default {1,1,1}")
.SetDefault({1, 1, 1});
AddAttr<std::vector<int>>(
"paddings",
"paddings(depth, height, width) of pooling operator."
"default {0,0,0}")
.SetDefault({0, 0, 0});
AddComment(R"DOC(
The pooling2d operation calculates the output based on
The pooling3d operation calculates the output based on
the input, poolingType and ksize, strides, paddings parameters.
)DOC");
}
......
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