From 6a4282a20f1f9c110ea5aef5035a0b733da6db19 Mon Sep 17 00:00:00 2001
From: Luo Tao <luotao02@baidu.com>
Date: Mon, 16 Oct 2017 20:02:04 +0800
Subject: [PATCH] refine comments of sequence_pool_op

---
 paddle/operators/sequence_pool_op.cc | 7 ++++---
 paddle/operators/sequence_pool_op.h  | 4 ++--
 2 files changed, 6 insertions(+), 5 deletions(-)

diff --git a/paddle/operators/sequence_pool_op.cc b/paddle/operators/sequence_pool_op.cc
index 9b8d86b4042..8dc4a59ba86 100644
--- a/paddle/operators/sequence_pool_op.cc
+++ b/paddle/operators/sequence_pool_op.cc
@@ -36,9 +36,10 @@ class SequencePoolOpMaker : public framework::OpProtoAndCheckerMaker {
   SequencePoolOpMaker(framework::OpProto* proto,
                       framework::OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
-    AddInput("X", "A LoDTensor, the variable-length input of SequencePoolOp");
+    AddInput("X", "(LoDTensor), the variable-length input of SequencePoolOp");
     AddOutput("Out",
-              "A LoDTensor, the variable-length output of SequencePoolOp.");
+              "(Tensor), output of SequencePoolOp, which does not contain LoD "
+              "infomation.");
     AddAttr<int>(
         "strategy",
         "(int, default AVERAGE) the pooling strategy of SequencePoolOp.")
@@ -53,7 +54,7 @@ class SequencePoolOpMaker : public framework::OpProtoAndCheckerMaker {
     Besides, for the sake of simplicity, we assume M=1 and N=1,
     and the value of X = [[1, 3], [2, 4, 6], [5, 1]].
 
-    Thus, Out is a [3,1,1] LoDTensor, but Out->lod() is nullptr.
+    Thus, Out is a [3,1,1] Tensor without LoD infomation.
     And for different strategy, the value of Out is as follows:
 
     - AVERAGE: [2, 4, 3], where 2=(1+3)/2, 4=(2+4+6)/3, 3=(5+1)/2
diff --git a/paddle/operators/sequence_pool_op.h b/paddle/operators/sequence_pool_op.h
index 8bfb80c33fe..ce68204d416 100644
--- a/paddle/operators/sequence_pool_op.h
+++ b/paddle/operators/sequence_pool_op.h
@@ -109,8 +109,8 @@ class SequencePoolGradKernel : public framework::OpKernel<T> {
     int64_t w = in->numel() / dims[0];
 
     in_g->mutable_data<T>(context.GetPlace());
-    if (strategy > 2) {
-      // set X@Grad be zero at first when strategy is LAST/FIRST/MAX
+    if (strategy == LAST || strategy == FIRST) {
+      // set X@Grad be zero at first when strategy is LAST/FIRST
       math::SetConstant<Place, T>(context.device_context(), in_g, 0);
     }
     auto place = context.GetEigenDevice<Place>();
-- 
GitLab