improve doc in margin_rank_loss_op

paddle/operators/margin_rank_loss_op.cc

@@ -22,7 +22,7 @@ class MarginRankLossOp : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
  protected:
-  void InferShape(framework::InferShapeContextBase *ctx) const override {
+  void InferShape(framework::InferShapeContext *ctx) const override {
     // input check
     PADDLE_ENFORCE(ctx->HasInput("Label"), "Input(Label) shouldn't be null.");
     PADDLE_ENFORCE(ctx->HasInput("X1"), "Input(X1) shouldn't be null.");
@@ -47,11 +47,11 @@ class MarginRankLossOpMaker : public framework::OpProtoAndCheckerMaker {
                         framework::OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X1",
-             "(2-D tensor with shape [batch_size x 1]) In pairwise ranking, "
-             "X1 is the score for one item to be ranked.");
+             "(2-D tensor with shape [batch_size x 1]) The score for "
+             "one item X1 to be ranked, from pairwise ranking model.");
     AddInput("X2",
-             "(2-D tensor with shape [batch_size x 1]) In pairwise ranking, "
-             "X2 is the score for another item to be ranked.");
+             "(2-D tensor with shape [batch_size x 1]) The score for "
+             "another item X2 to be ranked, from pairwise ranking model.");
     AddInput("Label",
              "(2-D tensor with shape [batch_size x 1]) "
              "The label indicating X1 ranked higher than X2 or not, "
@@ -63,19 +63,25 @@ class MarginRankLossOpMaker : public framework::OpProtoAndCheckerMaker {
               "to indicate whether each element of Output(Out) is activated.")
         .AsIntermediate();
     AddOutput("Out",
-              "(2-D tensor with shape [batch_size x 1])"
+              "(2-D tensor with shape [batch_size x 1]) "
               "The output loss of MarginRankLoss operator.");
     AddComment(R"DOC(
 
-MarginRankLoss operator measures the loss given a pair of input {`X1`, `X2`}
-and the `Label` with attribute `margin`, where `Label = +1` indicating X1 is
-ranked higher than `X2`, otherwise `Label = -1`. The loss turns out
+MarginRankLoss operator measures the loss given a pair of training sample
+{`X1`, `X2`} and the `Label` with attribute `margin`, where `Label = +1` 
+indicating X1 is ranked higher than `X2`, otherwise `Label = -1`. The loss 
+turns out
 
-loss(X1, X2, Label) = max(0, -Label * (X1 - X2) + margin)
+loss(X1, X2, Label) = max(0, -Label * (X1 - X2) + margin).
 
 The attribute `margin` involved here helps make the predictions more robust.
-Only when the difference between `X1` and `X2` is greater than `margin`, it is
-possible for these two items contribute to the final loss.
+Denote the item ranked higher as the positive sample, otherwise negative 
+sample. If the score of the two samples statisfies 
+
+positive sample - negative sample < margin,
+
+the pair of samples will contribute to the loss, which will backpropogate and 
+train the ranking model to enlarge the difference of the two score.
 
 For batch input with size `batch_size`, `X1`, `X2` and `Label`
 all have the same shape [batch_size x 1].
@@ -89,7 +95,7 @@ class MarginRankLossGradOp : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
  protected:
-  void InferShape(framework::InferShapeContextBase *ctx) const override {
+  void InferShape(framework::InferShapeContext *ctx) const override {
     PADDLE_ENFORCE(ctx->HasInput("Label"), "Input(Label) shouldn't be null.");
     PADDLE_ENFORCE(ctx->HasInput("X1"), "Input(X1) shouldn't be null.");
     PADDLE_ENFORCE(ctx->HasInput("X2"), "Input(X2) shouldn't be null.");

paddle/operators/margin_rank_loss_op.h

@@ -35,7 +35,7 @@ struct Heaviside {
 };
 
 template <typename Place, typename T>
-class MarginRankLossKernel : public framework::OpKernel {
+class MarginRankLossKernel : public framework::OpKernel<T> {
  public:
   void Compute(const framework::ExecutionContext& ctx) const {
     auto* out_t = ctx.Output<framework::Tensor>("Out");
@@ -63,7 +63,7 @@ class MarginRankLossKernel : public framework::OpKernel {
 };
 
 template <typename Place, typename T>
-class MarginRankLossGradKernel : public framework::OpKernel {
+class MarginRankLossGradKernel : public framework::OpKernel<T> {
  public:
   void Compute(const framework::ExecutionContext& ctx) const {
     auto* d_x1_t =