diff --git a/paddle/operators/accuracy_op.cc b/paddle/operators/accuracy_op.cc
index 32479ae5a35194e942fb4012c268c534200e1db6..391258b40ba5e091ba05525babbda7f5ebac7b2b 100644
--- a/paddle/operators/accuracy_op.cc
+++ b/paddle/operators/accuracy_op.cc
@@ -55,15 +55,15 @@ class AccuracyOpMaker : public framework::OpProtoAndCheckerMaker {
     // TODO(typhoonzero): AddInput("Weight", ...
     AddOutput("Accuracy", "The accuracy of current batch");
 
-    AddComment(
-        R"DOC(Accuracy. It will print accuracy rate for classification.
+    AddComment(R"DOC(
+Accuracy. It will print accuracy rate for classification.
 The accuracy is:
 ..  math::
 accuracy = \\frac{NumOfCorrectPredicts}{NumOfAllSamples})
 
 Both the input `Inference` and `Label` can carry the LoD (Level of Details)
 information, or not. But the output only shares the LoD with input `Inference`.
-DOC");
+)DOC");
   }
 };
 
diff --git a/paddle/operators/dropout_op.cc b/paddle/operators/dropout_op.cc
index b111b9fccb2310bd5fb92bda878a497c51f62ce0..bfa1992d79f7c1e30a0ddfa203c90afd75934bf9 100644
--- a/paddle/operators/dropout_op.cc
+++ b/paddle/operators/dropout_op.cc
@@ -38,6 +38,7 @@ class DropoutOp : public framework::OperatorWithKernel {
     if (ctx.Attr<int>("is_training") == 1) {
       ctx.Output<LoDTensor>("Mask")->Resize(dims);
     }
+    ctx.ShareLoD("X", "Out");
   }
 };
 
diff --git a/paddle/operators/fc_op.cc b/paddle/operators/fc_op.cc
index 56fe654d1e8df9ce2978dde4eb653bcfe38ebd02..5ac0e8cc45f007d42f1b6d7f86333f5cbedb3ea8 100644
--- a/paddle/operators/fc_op.cc
+++ b/paddle/operators/fc_op.cc
@@ -189,7 +189,6 @@ Activation type can be set to `identity` (default), `sigmoid` or `softmax`.
 
 All the inputs can carry the LoD (Level of Details) information,
 or not. But the output only shares the LoD with first input (`X[0]`).
-)DOC");
 )DOC");
   }
 };
diff --git a/paddle/operators/pad_op.cc b/paddle/operators/pad_op.cc
index a0b1c6b631d97a40d774f7d2ff9550fda9c32db4..98de18fb9f6189ce2646c1ec06a28d2ca992aeec 100644
--- a/paddle/operators/pad_op.cc
+++ b/paddle/operators/pad_op.cc
@@ -41,6 +41,11 @@ class PadOp : public framework::OperatorWithKernel {
     }
     ctx.Output<framework::LoDTensor>("Out")->Resize(
         framework::make_ddim(out_dims));
+    if (out_dims[0] == x_dim[0]) {
+      // Only pass LoD when the first dimension is equal between
+      // output and input.
+      ctx.ShareLoD("X", "Out");
+    }
   }
 };
 
diff --git a/paddle/operators/reshape_op.cc b/paddle/operators/reshape_op.cc
index 0d05e344148c68f5625dd819ec59c5991892e4ce..c0907586199ec9212f038c5ca5f029485ce1cb77 100644
--- a/paddle/operators/reshape_op.cc
+++ b/paddle/operators/reshape_op.cc
@@ -51,6 +51,11 @@ class ReshapeOp : public framework::OperatorWithKernel {
                    [](int a) { return static_cast<int64_t>(a); });
     auto out_dims = framework::make_ddim(shape_int64);
     ctx.Output<framework::LoDTensor>("Out")->Resize(out_dims);
+    if (shape[0] == in->dims()[0]) {
+      // Only pass LoD when the first dimension is equal between
+      // output and input.
+      ctx.ShareLoD("X", "Out");
+    }
   }
 };