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体验新版 GitCode,发现更多精彩内容 >>
提交
0ab012cf
编写于
10月 27, 2017
作者:
C
chengduoZH
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix doc
上级
25df8929
变更
9
隐藏空白更改
内联
并排
Showing
9 changed file
with
75 addition
and
101 deletion
+75
-101
paddle/operators/pool_cudnn_op.cc
paddle/operators/pool_cudnn_op.cc
+0
-9
paddle/operators/pool_cudnn_op.cu
paddle/operators/pool_cudnn_op.cu
+4
-7
paddle/operators/pool_op.cc
paddle/operators/pool_op.cc
+31
-39
paddle/operators/pool_op.h
paddle/operators/pool_op.h
+4
-4
paddle/operators/pool_with_index_op.cc
paddle/operators/pool_with_index_op.cc
+28
-34
paddle/operators/pool_with_index_op.h
paddle/operators/pool_with_index_op.h
+2
-2
python/paddle/v2/framework/tests/test_pool2d_cudnn_op.py
python/paddle/v2/framework/tests/test_pool2d_cudnn_op.py
+2
-2
python/paddle/v2/framework/tests/test_pool2d_op.py
python/paddle/v2/framework/tests/test_pool2d_op.py
+2
-2
python/paddle/v2/framework/tests/test_pool3d_op.py
python/paddle/v2/framework/tests/test_pool3d_op.py
+2
-2
未找到文件。
paddle/operators/pool_cudnn_op.cc
浏览文件 @
0ab012cf
...
@@ -23,12 +23,3 @@ REGISTER_OP_CPU_KERNEL(pool2d_cudnn,
...
@@ -23,12 +23,3 @@ REGISTER_OP_CPU_KERNEL(pool2d_cudnn,
ops
::
PoolKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
ops
::
PoolKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
REGISTER_OP_CPU_KERNEL
(
pool2d_cudnn_grad
,
REGISTER_OP_CPU_KERNEL
(
pool2d_cudnn_grad
,
ops
::
PoolGradKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
)
ops
::
PoolGradKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
)
// REGISTER_OP(pool3d_cudnn, ops::PoolOp, ops::Pool3dOpMaker, pool3d_cudnn_grad,
// ops::PoolOpGrad);
//
// REGISTER_OP_CPU_KERNEL(pool3d_cudnn,
// ops::PoolKernel<paddle::platform::CPUPlace, float>);
// REGISTER_OP_CPU_KERNEL(pool3d_cudnn_grad,
// ops::PoolGradKernel<paddle::platform::CPUPlace,
// float>);
paddle/operators/pool_cudnn_op.cu
浏览文件 @
0ab012cf
...
@@ -46,11 +46,11 @@ class PoolCudnnOpKernel : public framework::OpKernel<T> {
...
@@ -46,11 +46,11 @@ class PoolCudnnOpKernel : public framework::OpKernel<T> {
const
T
*
input_data
=
input
->
data
<
T
>
();
const
T
*
input_data
=
input
->
data
<
T
>
();
T
*
output_data
=
output
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
T
*
output_data
=
output
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
std
::
string
pooling_type
=
ctx
.
Attr
<
std
::
string
>
(
"pooling
_t
ype"
);
std
::
string
pooling_type
=
ctx
.
Attr
<
std
::
string
>
(
"pooling
T
ype"
);
std
::
vector
<
int
>
ksize
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"ksize"
);
std
::
vector
<
int
>
ksize
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"ksize"
);
std
::
vector
<
int
>
strides
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
strides
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
paddings
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
std
::
vector
<
int
>
paddings
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
if
(
ctx
.
Attr
<
bool
>
(
"global
_p
ooling"
))
{
if
(
ctx
.
Attr
<
bool
>
(
"global
P
ooling"
))
{
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
{
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
{
ksize
[
i
]
=
static_cast
<
int
>
(
input
->
dims
()[
i
+
2
]);
ksize
[
i
]
=
static_cast
<
int
>
(
input
->
dims
()[
i
+
2
]);
}
}
...
@@ -100,12 +100,12 @@ class PoolCudnnGradOpKernel : public framework::OpKernel<T> {
...
@@ -100,12 +100,12 @@ class PoolCudnnGradOpKernel : public framework::OpKernel<T> {
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
Tensor
*
input_grad
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
Tensor
*
input_grad
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
std
::
string
pooling_type
=
ctx
.
Attr
<
std
::
string
>
(
"pooling
_t
ype"
);
std
::
string
pooling_type
=
ctx
.
Attr
<
std
::
string
>
(
"pooling
T
ype"
);
std
::
vector
<
int
>
ksize
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"ksize"
);
std
::
vector
<
int
>
ksize
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"ksize"
);
std
::
vector
<
int
>
strides
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
strides
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
paddings
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
std
::
vector
<
int
>
paddings
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
if
(
ctx
.
Attr
<
bool
>
(
"global
_p
ooling"
))
{
if
(
ctx
.
Attr
<
bool
>
(
"global
P
ooling"
))
{
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
ksize
[
i
]
=
static_cast
<
int
>
(
input
->
dims
()[
i
+
2
]);
ksize
[
i
]
=
static_cast
<
int
>
(
input
->
dims
()[
i
+
2
]);
}
}
...
@@ -169,6 +169,3 @@ namespace ops = paddle::operators;
...
@@ -169,6 +169,3 @@ namespace ops = paddle::operators;
REGISTER_OP_GPU_KERNEL
(
pool2d_cudnn
,
ops
::
PoolCudnnOpKernel
<
float
>
);
REGISTER_OP_GPU_KERNEL
(
pool2d_cudnn
,
ops
::
PoolCudnnOpKernel
<
float
>
);
REGISTER_OP_GPU_KERNEL
(
pool2d_cudnn_grad
,
ops
::
PoolCudnnGradOpKernel
<
float
>
);
REGISTER_OP_GPU_KERNEL
(
pool2d_cudnn_grad
,
ops
::
PoolCudnnGradOpKernel
<
float
>
);
//
// REGISTER_OP_GPU_KERNEL(pool3d_cudnn, ops::PoolCudnnOpKernel<float>);
// REGISTER_OP_GPU_KERNEL(pool3d_cudnn_grad, ops::PoolCudnnGradOpKernel<float>);
paddle/operators/pool_op.cc
浏览文件 @
0ab012cf
...
@@ -29,7 +29,7 @@ void PoolOp::InferShape(framework::InferShapeContext *ctx) const {
...
@@ -29,7 +29,7 @@ void PoolOp::InferShape(framework::InferShapeContext *ctx) const {
auto
in_x_dims
=
ctx
->
GetInputDim
(
"X"
);
auto
in_x_dims
=
ctx
->
GetInputDim
(
"X"
);
std
::
string
pooling_type
=
ctx
->
Attrs
().
Get
<
std
::
string
>
(
"pooling
_t
ype"
);
std
::
string
pooling_type
=
ctx
->
Attrs
().
Get
<
std
::
string
>
(
"pooling
T
ype"
);
std
::
vector
<
int
>
ksize
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"ksize"
);
std
::
vector
<
int
>
ksize
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"ksize"
);
std
::
vector
<
int
>
strides
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
strides
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
paddings
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"paddings"
);
std
::
vector
<
int
>
paddings
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"paddings"
);
...
@@ -37,7 +37,7 @@ void PoolOp::InferShape(framework::InferShapeContext *ctx) const {
...
@@ -37,7 +37,7 @@ void PoolOp::InferShape(framework::InferShapeContext *ctx) const {
PADDLE_ENFORCE
(
in_x_dims
.
size
()
==
4
||
in_x_dims
.
size
()
==
5
,
PADDLE_ENFORCE
(
in_x_dims
.
size
()
==
4
||
in_x_dims
.
size
()
==
5
,
"Pooling intput should be 4-D or 5-D tensor."
);
"Pooling intput should be 4-D or 5-D tensor."
);
if
(
ctx
->
Attrs
().
Get
<
bool
>
(
"global
_p
ooling"
))
{
if
(
ctx
->
Attrs
().
Get
<
bool
>
(
"global
P
ooling"
))
{
ksize
.
resize
(
static_cast
<
size_t
>
(
in_x_dims
.
size
())
-
2
);
ksize
.
resize
(
static_cast
<
size_t
>
(
in_x_dims
.
size
())
-
2
);
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
ksize
[
i
]
=
static_cast
<
int
>
(
in_x_dims
[
i
+
2
]);
ksize
[
i
]
=
static_cast
<
int
>
(
in_x_dims
[
i
+
2
]);
...
@@ -80,34 +80,31 @@ Pool2dOpMaker::Pool2dOpMaker(framework::OpProto *proto,
...
@@ -80,34 +80,31 @@ Pool2dOpMaker::Pool2dOpMaker(framework::OpProto *proto,
"the number of channels, H and W is the height and "
"the number of channels, H and W is the height and "
"width of feature."
);
"width of feature."
);
AddAttr
<
std
::
string
>
(
"pooling
_t
ype"
,
AddAttr
<
std
::
string
>
(
"pooling
T
ype"
,
"
Pooling_t
ype of pooling operator."
"
(string), poolingT
ype of pooling operator."
"Str constant equal to 'max' or 'avg'."
)
"Str constant equal to 'max' or 'avg'."
)
.
InEnum
({
"max"
,
"avg"
});
.
InEnum
({
"max"
,
"avg"
});
AddAttr
<
std
::
vector
<
int
>>
(
AddAttr
<
std
::
vector
<
int
>>
(
"ksize"
,
"ksize"
,
"
T
he pooling window size(height, width) of pooling operator."
"
(vector ), t
he pooling window size(height, width) of pooling operator."
"If global
_p
ooling = true, ksize is ignored and need not be "
"If global
P
ooling = true, ksize is ignored and need not be "
"specified."
);
// TODO(Chengduo): Add checker. (Currently,
"specified."
);
// TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)
// TypedAttrChecker don't support vector type.)
AddAttr
<
bool
>
(
AddAttr
<
bool
>
(
"global_pooling"
,
"globalPooling"
,
"Whether to use the global_pooling."
"(bool default: false), whether to use the global pooling."
"Bool constant equal to false or true."
"If globalPooling = true, ksize is ignored and need not be specified."
)
"Default false."
"If global_pooling = true, ksize is ignored and need not be specified."
)
.
SetDefault
(
false
);
.
SetDefault
(
false
);
AddAttr
<
std
::
vector
<
int
>>
(
"strides"
,
AddAttr
<
std
::
vector
<
int
>>
(
"The strides(height, width) of pooling window."
"strides"
,
"Default {1,1}
."
)
"(vector, default:{1, 1}), strides(height, width) of pooling operator
."
)
.
SetDefault
({
1
,
1
});
// TODO(Chengduo): Add checker. (Currently,
.
SetDefault
({
1
,
1
});
// TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)
// TypedAttrChecker don't support vector type.)
AddAttr
<
std
::
vector
<
int
>>
(
"paddings"
,
AddAttr
<
std
::
vector
<
int
>>
(
"The zero padding(height, width) size on both sides"
"paddings"
,
"Default {0,0}
."
)
"(vector defalut:{0,0}), paddings(height, width) of pooling operator
."
)
.
SetDefault
({
0
,
0
});
// TODO(Chengduo): Add checker. (Currently,
.
SetDefault
({
0
,
0
});
// TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)
// TypedAttrChecker don't support vector type.)
AddComment
(
R"DOC(
AddComment
(
R"DOC(
The pooling2d operation calculates the output based on
The pooling2d operation calculates the output based on
...
@@ -123,7 +120,6 @@ Example:
...
@@ -123,7 +120,6 @@ Example:
X shape: (N, C, H_in, W_in)
X shape: (N, C, H_in, W_in)
Output:
Output:
Out shape: (N, C, H_out, W_out)
Out shape: (N, C, H_out, W_out)
Mask shape: (N, C, H_out, W_out)
where
where
H_out = (H_in - ksize[0] + 2 * paddings[0]) / strides[0] + 1;
H_out = (H_in - ksize[0] + 2 * paddings[0]) / strides[0] + 1;
W_out = (W_in - ksize[1] + 2 * paddings[1]) / strides[1] + 1;
W_out = (W_in - ksize[1] + 2 * paddings[1]) / strides[1] + 1;
...
@@ -146,33 +142,30 @@ Pool3dOpMaker::Pool3dOpMaker(framework::OpProto *proto,
...
@@ -146,33 +142,30 @@ Pool3dOpMaker::Pool3dOpMaker(framework::OpProto *proto,
"the number of channels, D, H and W is the depth, height and "
"the number of channels, D, H and W is the depth, height and "
"width of feature."
);
"width of feature."
);
AddAttr
<
std
::
string
>
(
"pooling
_t
ype"
,
AddAttr
<
std
::
string
>
(
"pooling
T
ype"
,
"
P
oolingType of pooling operator."
"
(string), p
oolingType of pooling operator."
"Str constant equal to 'max' or 'avg'."
)
"Str constant equal to 'max' or 'avg'."
)
.
InEnum
({
"max"
,
"avg"
});
.
InEnum
({
"max"
,
"avg"
});
AddAttr
<
std
::
vector
<
int
>>
(
AddAttr
<
std
::
vector
<
int
>>
(
"ksize"
,
"ksize"
,
"The pooling window size(depth, height, width) of pooling operator."
"(vector ), the pooling window size(depth, height, width) of pooling "
"If global_pooling = true, ksize is ignored and need not be "
"operator."
"If globalPooling = true, ksize is ignored and need not be "
"specified."
);
// TODO(Chengduo): Add checker. (Currently,
"specified."
);
// TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)
// TypedAttrChecker don't support vector type.)
AddAttr
<
bool
>
(
AddAttr
<
bool
>
(
"global_pooling"
,
"globalPooling"
,
"Whether to use the global_pooling."
"(bool default: false), whether to use the global pooling."
"Bool constant equal to false or true."
"If globalPooling = true, ksize is ignored and need not be specified."
)
"Default false."
"If global_pooling = true, ksize is ignored and need not be specified."
)
.
SetDefault
(
false
);
.
SetDefault
(
false
);
AddAttr
<
std
::
vector
<
int
>>
(
"strides"
,
AddAttr
<
std
::
vector
<
int
>>
(
"strides"
,
"
Strides(depth, height, width) of pooling operator.
"
"
(vector, default:{1,1,1}), strides(depth, height,
"
"
Default {1,1,1}
."
)
"
width) of pooling operator
."
)
.
SetDefault
({
1
,
1
,
1
});
// TODO(Chengduo): Add checker. (Currently,
.
SetDefault
({
1
,
1
,
1
});
// TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)
// TypedAttrChecker don't support vector type.)
AddAttr
<
std
::
vector
<
int
>>
(
AddAttr
<
std
::
vector
<
int
>>
(
"paddings"
,
"paddings"
,
"(vector defalut:{0,0,0}), paddings(depth, height, "
"Paddings(depth, height, width) of pooling operator."
"width) of pooling operator."
)
"Default {0,0,0}."
)
.
SetDefault
({
0
,
0
,
0
});
// TODO(Chengduo): Add checker. (Currently,
.
SetDefault
({
0
,
0
,
0
});
// TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)
// TypedAttrChecker don't support vector type.)
...
@@ -190,7 +183,6 @@ Example:
...
@@ -190,7 +183,6 @@ Example:
X shape: (N, C, D_in, H_in, W_in)
X shape: (N, C, D_in, H_in, W_in)
Output:
Output:
Out shape: (N, C, D_out, H_out, W_out)
Out shape: (N, C, D_out, H_out, W_out)
Mask shape: (N, C, D_out, H_out, W_out)
where
where
D_out = (D_in - ksize[0] + 2 * paddings[0]) / strides[0] + 1;
D_out = (D_in - ksize[0] + 2 * paddings[0]) / strides[0] + 1;
H_out = (H_in - ksize[1] + 2 * paddings[1]) / strides[1] + 1;
H_out = (H_in - ksize[1] + 2 * paddings[1]) / strides[1] + 1;
...
...
paddle/operators/pool_op.h
浏览文件 @
0ab012cf
...
@@ -57,11 +57,11 @@ class PoolKernel : public framework::OpKernel<T> {
...
@@ -57,11 +57,11 @@ class PoolKernel : public framework::OpKernel<T> {
const
Tensor
*
in_x
=
context
.
Input
<
Tensor
>
(
"X"
);
const
Tensor
*
in_x
=
context
.
Input
<
Tensor
>
(
"X"
);
Tensor
*
out
=
context
.
Output
<
Tensor
>
(
"Out"
);
Tensor
*
out
=
context
.
Output
<
Tensor
>
(
"Out"
);
std
::
string
pooling_type
=
context
.
Attr
<
std
::
string
>
(
"pooling
_t
ype"
);
std
::
string
pooling_type
=
context
.
Attr
<
std
::
string
>
(
"pooling
T
ype"
);
std
::
vector
<
int
>
ksize
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"ksize"
);
std
::
vector
<
int
>
ksize
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"ksize"
);
std
::
vector
<
int
>
strides
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
strides
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
paddings
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
std
::
vector
<
int
>
paddings
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
if
(
context
.
Attr
<
bool
>
(
"global
_p
ooling"
))
{
if
(
context
.
Attr
<
bool
>
(
"global
P
ooling"
))
{
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
{
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
{
ksize
[
i
]
=
static_cast
<
int
>
(
in_x
->
dims
()[
i
+
2
]);
ksize
[
i
]
=
static_cast
<
int
>
(
in_x
->
dims
()[
i
+
2
]);
}
}
...
@@ -117,12 +117,12 @@ class PoolGradKernel : public framework::OpKernel<T> {
...
@@ -117,12 +117,12 @@ class PoolGradKernel : public framework::OpKernel<T> {
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
Tensor
*
in_x_grad
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
Tensor
*
in_x_grad
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
std
::
string
pooling_type
=
context
.
Attr
<
std
::
string
>
(
"pooling
_t
ype"
);
std
::
string
pooling_type
=
context
.
Attr
<
std
::
string
>
(
"pooling
T
ype"
);
std
::
vector
<
int
>
ksize
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"ksize"
);
std
::
vector
<
int
>
ksize
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"ksize"
);
std
::
vector
<
int
>
strides
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
strides
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
paddings
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
std
::
vector
<
int
>
paddings
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
if
(
context
.
Attr
<
bool
>
(
"global
_p
ooling"
))
{
if
(
context
.
Attr
<
bool
>
(
"global
P
ooling"
))
{
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
ksize
[
i
]
=
static_cast
<
int
>
(
in_x
->
dims
()[
i
+
2
]);
ksize
[
i
]
=
static_cast
<
int
>
(
in_x
->
dims
()[
i
+
2
]);
}
}
...
...
paddle/operators/pool_with_index_op.cc
浏览文件 @
0ab012cf
...
@@ -44,7 +44,7 @@ class MaxPoolWithIndexOp : public framework::OperatorWithKernel {
...
@@ -44,7 +44,7 @@ class MaxPoolWithIndexOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE
(
in_x_dims
.
size
()
==
4
||
in_x_dims
.
size
()
==
5
,
PADDLE_ENFORCE
(
in_x_dims
.
size
()
==
4
||
in_x_dims
.
size
()
==
5
,
"Pooling intput should be 4-D or 5-D tensor."
);
"Pooling intput should be 4-D or 5-D tensor."
);
if
(
ctx
->
Attrs
().
Get
<
bool
>
(
"global
_p
ooling"
))
{
if
(
ctx
->
Attrs
().
Get
<
bool
>
(
"global
P
ooling"
))
{
ksize
.
resize
(
static_cast
<
size_t
>
(
in_x_dims
.
size
())
-
2
);
ksize
.
resize
(
static_cast
<
size_t
>
(
in_x_dims
.
size
())
-
2
);
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
ksize
[
i
]
=
static_cast
<
int
>
(
in_x_dims
[
i
+
2
]);
ksize
[
i
]
=
static_cast
<
int
>
(
in_x_dims
[
i
+
2
]);
...
@@ -105,28 +105,25 @@ class MaxPool2dWithIndexOpMaker : public framework::OpProtoAndCheckerMaker {
...
@@ -105,28 +105,25 @@ class MaxPool2dWithIndexOpMaker : public framework::OpProtoAndCheckerMaker {
AddAttr
<
std
::
vector
<
int
>>
(
AddAttr
<
std
::
vector
<
int
>>
(
"ksize"
,
"ksize"
,
"
T
he pooling window size(height, width) of pooling operator."
"
(vector ), t
he pooling window size(height, width) of pooling operator."
"If global
_p
ooling = true, ksize is ignored and need not be "
"If global
P
ooling = true, ksize is ignored and need not be "
"specified."
);
// TODO(Chengduo): Add checker. (Currently,
"specified."
);
// TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)
// TypedAttrChecker don't support vector type.)
AddAttr
<
bool
>
(
AddAttr
<
bool
>
(
"global_pooling"
,
"globalPooling"
,
"Whether to use the global_pooling."
"(bool default: false), whether to use the global pooling."
"Bool constant equal to false or true."
"If globalPooling = true, ksize is ignored and need not be specified."
)
"Default false."
"If global_pooling = true, ksize is ignored and need not be specified."
)
.
SetDefault
(
false
);
.
SetDefault
(
false
);
AddAttr
<
std
::
vector
<
int
>>
(
"strides"
,
AddAttr
<
std
::
vector
<
int
>>
(
"The strides(height, width) of pooling window."
"strides"
,
"Default {1,1}
."
)
"(vector, default:{1, 1}), strides(height, width) of pooling operator
."
)
.
SetDefault
({
1
,
1
});
// TODO(Chengduo): Add checker. (Currently,
.
SetDefault
({
1
,
1
});
// TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)
// TypedAttrChecker don't support vector type.)
AddAttr
<
std
::
vector
<
int
>>
(
AddAttr
<
std
::
vector
<
int
>>
(
"paddings"
,
"paddings"
,
"The zero padding(height, width) size on both sides"
"(vector defalut:{0,0}), paddings(height, width) of pooling operator."
)
"Default {0,0}."
)
.
SetDefault
({
0
,
0
});
// TODO(Chengduo): Add checker. (Currently,
.
SetDefault
({
0
,
0
});
// TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)
// TypedAttrChecker don't support vector type.)
AddComment
(
R"DOC(
AddComment
(
R"DOC(
The maxPooling2d with index operation calculates the output and the mask
The maxPooling2d with index operation calculates the output and the mask
...
@@ -176,29 +173,26 @@ class MaxPool3dWithIndexOpMaker : public framework::OpProtoAndCheckerMaker {
...
@@ -176,29 +173,26 @@ class MaxPool3dWithIndexOpMaker : public framework::OpProtoAndCheckerMaker {
AddAttr
<
std
::
vector
<
int
>>
(
AddAttr
<
std
::
vector
<
int
>>
(
"ksize"
,
"ksize"
,
"The pooling window size(depth, height, width) of pooling operator."
"(vector ), the pooling window size(depth, height, width) of pooling "
"If global_pooling = true, ksize is ignored and need not be "
"operator."
"If globalPooling = true, ksize is ignored and need not be "
"specified."
);
// TODO(Chengduo): Add checker. (Currently,
"specified."
);
// TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)
// TypedAttrChecker don't support vector type.)
AddAttr
<
bool
>
(
AddAttr
<
bool
>
(
"global_pooling"
,
"globalPooling"
,
"Whether to use the global_pooling."
"(bool default: false), whether to use the global pooling."
"Bool constant equal to false or true."
"If globalPooling = true, ksize is ignored and need not be specified."
)
"Default false."
"If global_pooling = true, ksize is ignored and need not be specified."
)
.
SetDefault
(
false
);
.
SetDefault
(
false
);
AddAttr
<
std
::
vector
<
int
>>
(
AddAttr
<
std
::
vector
<
int
>>
(
"strides"
,
"strides"
,
"(vector, default:{1,1,1}), strides(depth, "
"Strides(depth, height, width) of pooling operator."
"height, width) of pooling operator."
)
"Default {1,1,1}."
)
.
SetDefault
({
1
,
1
,
1
});
// TODO(Chengduo): Add checker. (Currently,
.
SetDefault
({
1
,
1
,
1
});
// TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)
// TypedAttrChecker don't support vector type.)
AddAttr
<
std
::
vector
<
int
>>
(
AddAttr
<
std
::
vector
<
int
>>
(
"paddings"
,
"paddings"
,
"(vector defalut:{0,0,0}), paddings(depth, "
"Paddings(depth, height, width) of pooling operator."
"height, width) of pooling operator."
)
"Default {0,0,0}."
)
.
SetDefault
({
0
,
0
,
0
});
// TODO(Chengduo): Add checker. (Currently,
.
SetDefault
({
0
,
0
,
0
});
// TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)
// TypedAttrChecker don't support vector type.)
AddComment
(
R"DOC(
AddComment
(
R"DOC(
The maxpooling3d with index operation calculates the output and the mask
The maxpooling3d with index operation calculates the output and the mask
...
...
paddle/operators/pool_with_index_op.h
浏览文件 @
0ab012cf
...
@@ -35,7 +35,7 @@ class MaxPoolWithIndexKernel : public framework::OpKernel<T> {
...
@@ -35,7 +35,7 @@ class MaxPoolWithIndexKernel : public framework::OpKernel<T> {
std
::
vector
<
int
>
ksize
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"ksize"
);
std
::
vector
<
int
>
ksize
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"ksize"
);
std
::
vector
<
int
>
strides
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
strides
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
paddings
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
std
::
vector
<
int
>
paddings
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
if
(
context
.
Attr
<
bool
>
(
"global
_p
ooling"
))
{
if
(
context
.
Attr
<
bool
>
(
"global
P
ooling"
))
{
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
{
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
{
ksize
[
i
]
=
static_cast
<
int
>
(
in_x
->
dims
()[
i
+
2
]);
ksize
[
i
]
=
static_cast
<
int
>
(
in_x
->
dims
()[
i
+
2
]);
}
}
...
@@ -70,7 +70,7 @@ class MaxPoolWithIndexGradKernel : public framework::OpKernel<T> {
...
@@ -70,7 +70,7 @@ class MaxPoolWithIndexGradKernel : public framework::OpKernel<T> {
std
::
vector
<
int
>
ksize
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"ksize"
);
std
::
vector
<
int
>
ksize
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"ksize"
);
std
::
vector
<
int
>
strides
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
strides
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
paddings
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
std
::
vector
<
int
>
paddings
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
if
(
context
.
Attr
<
bool
>
(
"global
_p
ooling"
))
{
if
(
context
.
Attr
<
bool
>
(
"global
P
ooling"
))
{
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
{
for
(
size_t
i
=
0
;
i
<
ksize
.
size
();
++
i
)
{
ksize
[
i
]
=
static_cast
<
int
>
(
in_x_grad
->
dims
()[
i
+
2
]);
ksize
[
i
]
=
static_cast
<
int
>
(
in_x_grad
->
dims
()[
i
+
2
]);
}
}
...
...
python/paddle/v2/framework/tests/test_pool2d_cudnn_op.py
浏览文件 @
0ab012cf
...
@@ -56,8 +56,8 @@ class TestPool2d_cudnn_Op(OpTest):
...
@@ -56,8 +56,8 @@ class TestPool2d_cudnn_Op(OpTest):
'strides'
:
self
.
strides
,
'strides'
:
self
.
strides
,
'paddings'
:
self
.
paddings
,
'paddings'
:
self
.
paddings
,
'ksize'
:
self
.
ksize
,
'ksize'
:
self
.
ksize
,
'pooling
_t
ype'
:
self
.
pool_type
,
'pooling
T
ype'
:
self
.
pool_type
,
'global
_p
ooling'
:
self
.
global_pool
,
'global
P
ooling'
:
self
.
global_pool
,
}
}
self
.
outputs
=
{
'Out'
:
output
}
self
.
outputs
=
{
'Out'
:
output
}
...
...
python/paddle/v2/framework/tests/test_pool2d_op.py
浏览文件 @
0ab012cf
...
@@ -56,8 +56,8 @@ class TestPool2d_Op(OpTest):
...
@@ -56,8 +56,8 @@ class TestPool2d_Op(OpTest):
'strides'
:
self
.
strides
,
'strides'
:
self
.
strides
,
'paddings'
:
self
.
paddings
,
'paddings'
:
self
.
paddings
,
'ksize'
:
self
.
ksize
,
'ksize'
:
self
.
ksize
,
'pooling
_t
ype'
:
self
.
pool_type
,
'pooling
T
ype'
:
self
.
pool_type
,
'global
_p
ooling'
:
self
.
global_pool
,
'global
P
ooling'
:
self
.
global_pool
,
}
}
self
.
outputs
=
{
'Out'
:
output
}
self
.
outputs
=
{
'Out'
:
output
}
...
...
python/paddle/v2/framework/tests/test_pool3d_op.py
浏览文件 @
0ab012cf
...
@@ -64,8 +64,8 @@ class TestPool3d_Op(OpTest):
...
@@ -64,8 +64,8 @@ class TestPool3d_Op(OpTest):
'strides'
:
self
.
strides
,
'strides'
:
self
.
strides
,
'paddings'
:
self
.
paddings
,
'paddings'
:
self
.
paddings
,
'ksize'
:
self
.
ksize
,
'ksize'
:
self
.
ksize
,
'pooling
_t
ype'
:
self
.
pool_type
,
'pooling
T
ype'
:
self
.
pool_type
,
'global
_p
ooling'
:
self
.
global_pool
,
'global
P
ooling'
:
self
.
global_pool
,
}
}
self
.
outputs
=
{
'Out'
:
output
}
self
.
outputs
=
{
'Out'
:
output
}
...
...
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