From 87de31bf205a1ffb63c74f7f8b338bcce38dcb2c Mon Sep 17 00:00:00 2001 From: Yibing Liu Date: Thu, 14 Sep 2017 12:09:16 +0800 Subject: [PATCH] update doc information --- paddle/operators/rank_loss_op.cc | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/paddle/operators/rank_loss_op.cc b/paddle/operators/rank_loss_op.cc index 14cddb609f..66571bd9a6 100644 --- a/paddle/operators/rank_loss_op.cc +++ b/paddle/operators/rank_loss_op.cc @@ -48,9 +48,9 @@ class RankLossOpMaker : public framework::OpProtoAndCheckerMaker { RankLossOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker) : OpProtoAndCheckerMaker(proto, op_checker) { - AddInput("P", "The first input of RankLoss operator."); - AddInput("Oi", "The second input of RankLoss operator."); - AddInput("Oj", "The third input of RankLoss operator."); + AddInput("P", "The desired target values for posteriors."); + AddInput("Oi", "The model output for item i."); + AddInput("Oj", "The model output for item j."); AddOutput("Out", "The output tensor of RankLoss operator."); AddComment(R"DOC(RankLoss operator @@ -63,6 +63,8 @@ three inputs: P, Oi, and Oj, and the rank cost can be expressed as \tilde{P_{i,j}} = \left \{0, 0.5, 1 \right \} \ or \ \left \{0, 1 \right \} \f] +A detailed explanation about these notations can be found in + [1]. Chris Burges, Tal Shaked, Erin Renshaw, et al. Learning to Rank useing Gradient Descent. )DOC"); -- GitLab