Merge pull request #16256 from tensor-tang/refine/seqenum

refine sequence enumerate op

paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cc

@@ -30,13 +30,6 @@ class SequenceEnumerateOp : public framework::OperatorWithKernel {
         "Output(X) of SequenceEnumerate operator should not be null.");
 
     const auto x_dims = ctx->GetInputDim("X");
-    PADDLE_ENFORCE_EQ(
-        x_dims.size(), 2,
-        "Input(X) of SequenceEnumerate operator's rank should be 2.");
-    PADDLE_ENFORCE_EQ(x_dims[1], 1,
-                      "Input(X) of SequenceEnumerate operator's 2nd "
-                      "dimension should be 1.");
-
     const auto win_size = ctx->Attrs().Get<int>("win_size");
     ctx->SetOutputDim("Out", {x_dims[0], win_size});
     ctx->ShareLoD("X", "Out");

paddle/fluid/operators/sequence_ops/sequence_enumerate_op.h

@@ -27,30 +27,47 @@ class SequenceEnumerateKernel : public framework::OpKernel<T> {
     auto* in = context.Input<LoDTensor>("X");
     auto* out = context.Output<LoDTensor>("Out");
     int win_size = context.Attr<int>("win_size");
-    int pad_value = context.Attr<int>("pad_value");
+    auto pad_value = static_cast<T>(context.Attr<int>("pad_value"));
 
     auto in_dims = in->dims();
-    auto in_lod = in->lod();
-
+    auto lod0 = in->lod()[0];
     PADDLE_ENFORCE_EQ(
-        static_cast<uint64_t>(in_dims[0]), in_lod[0].back(),
+        static_cast<uint64_t>(in_dims[0]), lod0.back(),
         "The actual input data's size mismatched with LoD information.");
+    PADDLE_ENFORCE_EQ(
+        in_dims.size(), 2UL,
+        "Input(X) of SequenceEnumerate operator's rank should be 2.");
+    PADDLE_ENFORCE_EQ(in_dims[1], 1,
+                      "Input(X) of SequenceEnumerate operator's 2nd "
+                      "dimension should be 1.");
 
     // Generate enumerate sequence set
-    auto lod0 = in_lod[0];
     auto in_data = in->data<T>();
     out->Resize({in_dims[0], win_size});
+    out->set_lod(in->lod());
     auto out_data = out->mutable_data<T>(context.GetPlace());
     for (size_t i = 0; i < lod0.size() - 1; ++i) {
-      for (size_t idx = lod0[i]; idx < lod0[i + 1]; ++idx) {
-        for (int word_idx = 0; word_idx < win_size; ++word_idx) {
-          size_t word_pos = idx + word_idx;
-          out_data[win_size * idx + word_idx] =
-              word_pos < lod0[i + 1] ? in_data[word_pos] : pad_value;
+      int start = lod0[i];
+      int end = lod0[i + 1];
+      int copy_size = win_size < end - start + 1 ? win_size : end - start + 1;
+      int mid = end + 1 - copy_size;
+      int pad_num = win_size - copy_size;
+      copy_size *= sizeof(T);
+      for (int idx = start; idx < mid; ++idx) {
+        std::memcpy(out_data, in_data + idx, copy_size);
+        out_data += win_size;
+      }
+      for (int idx = mid; idx < end; ++idx) {
+        copy_size -= sizeof(T);
+        pad_num++;
+        std::memcpy(out_data, in_data + idx, copy_size);
+        T* pdata = out_data + copy_size / sizeof(T);
+        for (int i = 0; i < pad_num; ++i) {
+          pdata[i] = pad_value;
         }
+        out_data += win_size;
       }
     }
-    out->set_lod(in->lod());
   }
 };