diff --git a/paddle/fluid/operators/array_to_lod_tensor_op.cc b/paddle/fluid/operators/array_to_lod_tensor_op.cc
index 9379ec2dd67f27299ead85c52a10cbdc4fc13932..f9222207d580b648b2cdb8482cfa762e2f29bea8 100644
--- a/paddle/fluid/operators/array_to_lod_tensor_op.cc
+++ b/paddle/fluid/operators/array_to_lod_tensor_op.cc
@@ -211,7 +211,7 @@ class ArrayToLoDTensorInferShape : public framework::InferShapeBase {
     PADDLE_ENFORCE_EQ(
         context->HasInput("X"), true,
         platform::errors::NotFound("Input(X) of BmmOp should not be null"));
-    PADDLE_ENFORCE_EQ(context->HasInput("RankTable", true),
+    PADDLE_ENFORCE_EQ(context->HasInput("RankTable"), true,
                       platform::errors::NotFound(
                           "Input(RankTable) of BmmOp should not be null"));
     // For compile-time, the first dim of input X and output Out should be -1.
diff --git a/paddle/fluid/operators/lod_tensor_to_array_op.cc b/paddle/fluid/operators/lod_tensor_to_array_op.cc
index df26680a9e21bc21b5ad2c55a26c2bb3788d7ac1..5df675803167bcc5ab48e6ec8ee444cd86bdba1d 100644
--- a/paddle/fluid/operators/lod_tensor_to_array_op.cc
+++ b/paddle/fluid/operators/lod_tensor_to_array_op.cc
@@ -108,11 +108,12 @@ class LoDTensorToArrayOp : public framework::OperatorBase {
     auto max_seq_len = items[0].length;
     auto rank_level = rank_table.level();
 
-    PADDLE_ENFORCE_LT(rank_level, x.lod().size(),
-                      platform::errors::InvalidArgument(
-            `"Input should be a LoDTensor, and its lod_level should be at "
-              "least %d",
-                          rank_level + 1));
+    PADDLE_ENFORCE_LT(
+        rank_level, x.lod().size(),
+        platform::errors::InvalidArgument(
+            "Input should be a LoDTensor, and its lod_level should be at "
+            "least %d",
+            rank_level + 1));
     out.resize(max_seq_len);
     std::vector<std::vector<CopyRange>> copy_ranges(max_seq_len);