diff --git a/paddle/function/BufferArg.h b/paddle/function/BufferArg.h
index 52494afed3b8554e9960f4ceccb86c9d94a6e91d..d787d2814d88bfc8753620e5f51d7a99936e432f 100644
--- a/paddle/function/BufferArg.h
+++ b/paddle/function/BufferArg.h
@@ -56,7 +56,7 @@ public:
       : buf_(buf), valueType_(valueType) {}
 
   BufferArg(const Matrix& matrix)
-      : buf_((void*)matrix.getData()),
+      : buf_(reinterpret_cast<void*>(matrix.getData())),
         valueType_(DataType<real>::value),
         shape_(2) {
     shape_.setDim(0, matrix.getHeight());
@@ -64,21 +64,23 @@ public:
   }
 
   BufferArg(const Matrix& matrix, const TensorShape& shape)
-      : buf_((void*)matrix.getData()),
+      : buf_(reinterpret_cast<void*>(matrix.getData())),
         valueType_(DataType<real>::value),
         shape_(shape) {
     CHECK_EQ(matrix.getElementCnt(), shape.getElements());
   }
 
   BufferArg(const Vector& vector)
-      : buf_((void*)vector.getData()),
+      : buf_(reinterpret_cast<void*>(vector.getData())),
         valueType_(DataType<real>::value),
         shape_(1) {
     shape_.setDim(0, vector.getSize());
   }
 
   BufferArg(const IVector& vector)
-      : buf_((void*)vector.getData()), valueType_(VALUE_TYPE_INT32), shape_(1) {
+      : buf_(reinterpret_cast<void*>(vector.getData())),
+        valueType_(VALUE_TYPE_INT32),
+        shape_(1) {
     shape_.setDim(0, vector.getSize());
   }
 
@@ -129,7 +131,7 @@ protected:
 // sequence start positions in a mini-batch of sequences
 // shape_.ndims() == 1
 // valueType_ = int32
-// if a < b than value_.buf_[a] < value_.buf_[b]
+// if a < b then value_.buf_[a] < value_.buf_[b]
 class SequenceIdArg : public BufferArg {
 public:
   SequenceIdArg(void* buf, const TensorShape& shape)
@@ -203,13 +205,13 @@ public:
 
   SparseMatrixArg(const CpuSparseMatrix& sparse)
       : BufferArg(sparse),
-        row_((void*)sparse.getRows(), VALUE_TYPE_INT32),
-        col_((void*)sparse.getCols(), VALUE_TYPE_INT32) {}
+        row_(reinterpret_cast<void*>(sparse.getRows()), VALUE_TYPE_INT32),
+        col_(reinterpret_cast<void*>(sparse.getCols()), VALUE_TYPE_INT32) {}
 
   SparseMatrixArg(const GpuSparseMatrix& sparse)
       : BufferArg(sparse),
-        row_((void*)sparse.getRows(), VALUE_TYPE_INT32),
-        col_((void*)sparse.getCols(), VALUE_TYPE_INT32) {}
+        row_(reinterpret_cast<void*>(sparse.getRows()), VALUE_TYPE_INT32),
+        col_(reinterpret_cast<void*>(sparse.getCols()), VALUE_TYPE_INT32) {}
 
   ~SparseMatrixArg() {}
 
diff --git a/paddle/function/TensorShape.h b/paddle/function/TensorShape.h
index e70484a1afd9926b93c298b0a090f321f6daef95..0333fe18316ba4a82bbdc2b1ef99e6d2186a234c 100644
--- a/paddle/function/TensorShape.h
+++ b/paddle/function/TensorShape.h
@@ -30,14 +30,14 @@ public:
   TensorShape(std::initializer_list<size_t> dims) {
     ndims_ = dims.size();
     initDims(ndims_);
-    std::copy(dims.begin(), dims.end(), dims_.begin());
+    dims_.assign(dims);
     numElements();
   };
 
   TensorShape(const TensorShape& t)
       : ndims_(t.ndims_), nelements_(t.nelements_) {
     initDims(ndims_);
-    std::copy(t.dims_.begin(), t.dims_.end(), dims_.begin());
+    dims_.assign(t.dims_.begin(), t.dims_.end());
   };
 
   // get the size of specified dimension