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PaddleDetection
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530df1b2
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530df1b2
编写于
1月 22, 2018
作者:
D
dangqingqing
浏览文件
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浏览文件
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电子邮件补丁
差异文件
Fix the naming.
上级
07908686
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
9 addition
and
9 deletion
+9
-9
paddle/operators/bipartite_match_op.cc
paddle/operators/bipartite_match_op.cc
+9
-9
未找到文件。
paddle/operators/bipartite_match_op.cc
浏览文件 @
530df1b2
...
...
@@ -28,11 +28,11 @@ class BipartiteMatchOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"DisMat"
),
"Input(DisMat) of BipartiteMatch should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Dis
t
Mat"
),
"Input(Dis
t
Mat) of BipartiteMatch should not be null."
);
auto
dims
=
ctx
->
GetInputDim
(
"DisMat"
);
PADDLE_ENFORCE_EQ
(
dims
.
size
(),
2
,
"The rank of Input(DisMat) must be 2."
);
auto
dims
=
ctx
->
GetInputDim
(
"Dis
t
Mat"
);
PADDLE_ENFORCE_EQ
(
dims
.
size
(),
2
,
"The rank of Input(Dis
t
Mat) must be 2."
);
ctx
->
SetOutputDim
(
"ColToRowMatchIndices"
,
dims
);
ctx
->
SetOutputDim
(
"ColToRowMatchDis"
,
dims
);
...
...
@@ -90,7 +90,7 @@ class BipartiteMatchKernel : public framework::OpKernel<T> {
}
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
*
dist_mat
=
context
.
Input
<
LoDTensor
>
(
"DisMat"
);
auto
*
dist_mat
=
context
.
Input
<
LoDTensor
>
(
"Dis
t
Mat"
);
auto
*
match_indices
=
context
.
Output
<
Tensor
>
(
"ColToRowMatchIndices"
);
auto
*
match_dist
=
context
.
Output
<
Tensor
>
(
"ColToRowMatchDis"
);
...
...
@@ -132,12 +132,12 @@ class BipartiteMatchOpMaker : public framework::OpProtoAndCheckerMaker {
BipartiteMatchOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"DisMat"
,
"Dis
t
Mat"
,
"(LoDTensor or Tensor) this input is a 2-D LoDTensor with shape "
"[K, M]. It is pair-wise distance matrix between the entities "
"represented by each row and each column. For example, assumed one "
"entity is A with shape [K], another entity is B with shape [M]. The "
"DisMat[i][j] is the distance between A[i] and B[j]. The bigger "
"Dis
t
Mat[i][j] is the distance between A[i] and B[j]. The bigger "
"the distance is, the better macthing the pairs are. Please note, "
"This tensor can contain LoD information to represent a batch of "
"inputs. One instance of this batch can contain different numbers of "
...
...
@@ -155,7 +155,7 @@ class BipartiteMatchOpMaker : public framework::OpProtoAndCheckerMaker {
"ColToRowMatchDis[i][j] is also -1.0. Otherwise, assumed "
"ColToRowMatchIndices[i][j] = d, and the row offsets of each "
"instance are called LoD. Then "
"ColToRowMatchDis[i][j] = DisMat[d+LoD[i]][j]"
);
"ColToRowMatchDis[i][j] = Dis
t
Mat[d+LoD[i]][j]"
);
AddComment
(
R"DOC(
This operator is a greedy bipartite matching algorithm, which is used to
obtain the matching with the maximum distance based on the input
...
...
@@ -171,7 +171,7 @@ row entity to the column entity and the matched indices are not duplicated
in each row of ColToRowMatchIndices. If the column entity is not matched
any row entity, set -1 in ColToRowMatchIndices.
Please note that the input DisMat can be LoDTensor (with LoD) or Tensor.
Please note that the input Dis
t
Mat can be LoDTensor (with LoD) or Tensor.
If LoDTensor with LoD, the height of ColToRowMatchIndices is batch size.
If Tensor, the height of ColToRowMatchIndices is 1.
...
...
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