1. Add unitest for empty sequence case

2. Fix comments and paddle enforce check

paddle/operators/seq_expand_op.cc

@@ -25,10 +25,8 @@ class SeqExpandOp : public framework::OperatorWithKernel {
 
  protected:
   void InferShape(framework::InferShapeContext* ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("X"),
-                   "Input(X) of SeqExpandOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasOutput("Out"),
-                   "Output(Out) of SeqExpandOp should not be null.");
+    PADDLE_ENFORCE(ctx->HasInput("X"));
+    PADDLE_ENFORCE(ctx->HasOutput("Out"));
     PADDLE_ENFORCE(
         ctx->HasInput("Y"),
         "Input(Y) of SeqExpandOp should not be null while repeat == 0.");
@@ -54,7 +52,7 @@ class SeqExpandOpMaker : public framework::OpProtoAndCheckerMaker {
              "The element numbers of last level in input('Y') "
              "must be equal to dims[0] of input('X').");
     AddOutput("Out",
-              "The output of seq_expand op."
+              "(LodTensor)The output of seq_expand op."
               "The lod of output will be as same as input(Y)'s lod.");
     AddComment(R"DOC(
 Expand input(X) according to LOD of input(Y).
@@ -69,6 +67,7 @@ Given 2-level a LoDTensor input(X)
 and input(Y)
     Y.lod = [[0,    2,    4],
              [0, 3, 6, 7, 8]]
+with condition len(Y.lod[-1]) -1 == X.dims[0]
 then we get 2-level LoDTensor
     Out.lod = [[0,                2,    4],
                [0,       3,       6, 7, 8]]
@@ -83,6 +82,7 @@ Given a 0-level LoDTensor input(X)
     X.dims = [3, 1]
 and input(Y)
     Y.lod = [[0, 2, 3, 6]]
+with condition len(Y.lod[-1]) -1 == X.dims[0]
 then we get 1-level LoDTensor
     Out.lod = [[0,    2, 3,      6]]
     Out.data = [a, a, b, c, c, c]
@@ -96,11 +96,29 @@ Given a 0-level LoDTensor input(X)
     X.dims = [3, 2]
 and input(Y)
     Y.lod = [[0, 2, 3, 6]]
+with condition len(Y.lod[-1]) -1 == X.dims[0]
 then we get 1-level LoDTensor
     Out.lod = [[0,           2,     3,                     6]]
     Out.data = [[a,b], [a,b] [c,d], [e, f], [e, f], [e, f]]
     Out.dims = [6, 2]
 
+Case 4:
+
+Given 2-level a LoDTensor input(X)
+    X.lod = [[0,       2, 3],
+             [0, 1,    3, 4]]
+    X.data = [a, b, c, d]
+    X.dims = [4, 1]
+and input(Y)
+    Y.lod = [[0,    2,    4],
+             [0, 3, 6, 6, 8]]
+with condition len(Y.lod[-1]) -1 == X.dims[0]
+then we get 2-level LoDTensor
+    Out.lod = [[0,                2,    4],
+               [0,       3,       6, 6, 8]]
+    Out.data = [a, a, a, b, b, b, d, d]
+    Out.dims = [8, 1]
+
 
 )DOC");
   }
@@ -112,8 +130,8 @@ class SeqExpandOpGrad : public framework::OperatorWithKernel {
 
  protected:
   void InferShape(framework::InferShapeContext* ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null");
-    PADDLE_ENFORCE(ctx->HasInput("Out"), "Input(Out) should not be null");
+    PADDLE_ENFORCE(ctx->HasInput("X"));
+    PADDLE_ENFORCE(ctx->HasInput("Out"));
     PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
                    "Input(Out@GRAD) should not be null");
     auto x_dims = ctx->GetInputDim("X");

paddle/operators/seq_expand_op.h

@@ -36,7 +36,6 @@ class SeqExpandKernel : public framework::OpKernel<T> {
                       "The size of last lod level in Input(Y)"
                       "must be equal to dims[0] of Input(X).");
     out->set_lod(y->lod());
-    out->Resize(y->dims());
     auto place = context.GetEigenDevice<Place>();
     size_t element_len = framework::product(x_dims) / x_dims[0];
     T* out_data = out->mutable_data<T>(context.GetPlace());
@@ -57,6 +56,18 @@ class SeqExpandKernel : public framework::OpKernel<T> {
   }
 };
 
+/*
+ *Given Grad(Out)
+ *
+ *    Grad(Out).lod = [[0,                            2],
+ *                     [0,              3,            6]]
+ *    Grad(Out).data = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6]
+ * Then
+ *    Grad(X).data = [(0.1 + 0.2 + 0.3), (0.4 + 0.5 + 0.6)]
+ *                 = [0.6, 1.5]
+ *    Grad(X).lod = Input(X).lod
+ *
+ * */
 template <typename Place, typename T>
 class SeqExpandGradKernel : public framework::OpKernel<T> {
  public:
@@ -68,10 +79,8 @@ class SeqExpandGradKernel : public framework::OpKernel<T> {
     auto out_last_level = out->lod().back();
     d_x->set_lod(x->lod());
     const T* d_out_data = d_out->data<T>();
-    auto d_out_dims = d_out->dims();
     T* d_x_data = d_x->mutable_data<T>(context.GetPlace());
-    size_t element_len = framework::product(d_out_dims) / d_out_dims[0];
-
+    size_t element_len = d_out->numel() / d_out->dims()[0];
     for (size_t i = 0; i < out_last_level.size() - 1; ++i) {
       size_t repeat = out_last_level[i + 1] - out_last_level[i];
       Eigen::TensorMap<