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8a463939
编写于
12月 23, 2017
作者:
C
caoying03
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电子邮件补丁
差异文件
fix doc.
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fc5c432a
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8 deletion
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paddle/operators/mul_op.cc
paddle/operators/mul_op.cc
+1
-1
paddle/operators/positive_negative_pair_op.cc
paddle/operators/positive_negative_pair_op.cc
+8
-7
未找到文件。
paddle/operators/mul_op.cc
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8a463939
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@@ -113,7 +113,7 @@ This operator is used to perform matrix multiplication for input $X$ and $Y$.
The equation is:
$$Out = X * Y$$
$$Out = X * Y$$
Both the input $X$ and $Y$ can carry the LoD (Level of Details) information,
or not. But the output only shares the LoD information with input $X$.
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paddle/operators/positive_negative_pair_op.cc
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8a463939
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@@ -154,13 +154,14 @@ class PositiveNegativePairOpMaker : public framework::OpProtoAndCheckerMaker {
"Noting that reducing on the first dim will make the LoD info lost."
)
.
SetDefault
(
0
);
AddComment
(
R"DOC(
PositiveNegativePairOp can be used to evaluate Learning To Rank(LTR)
model performance.
Within some context, e.g. the "query", a LTR model generates scores
for a list of items, which gives a partial order of the items.
PositiveNegativePairOp takes a list of reference rank order
(Input("Label")) and the model generated scores (Input(Score)) as
inputs and counts the pairs that ranked correctly and incorrectly.
PositiveNegativePairOp can be used to evaluate Learning To Rank(LTR) model's
performance.
Within some context, e.g. the "query", a LTR model generates scores for a list
of items, which gives a partial order of the items. PositiveNegativePairOp
takes a list of reference rank order (Input("Label")) and the model generated
scores (Input(Score)) as inputs and counts the pairs that ranked correctly
and incorrectly.
)DOC"
);
}
};
...
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