diff --git a/paddle/operators/bilinear_tensor_product_op.h b/paddle/operators/bilinear_tensor_product_op.h
index ffa4f43a327418498c1f110504127e7d2878409d..ee9636e9fb7cbef84c494bf2f46b0fcb189717d6 100644
--- a/paddle/operators/bilinear_tensor_product_op.h
+++ b/paddle/operators/bilinear_tensor_product_op.h
@@ -63,6 +63,7 @@ class BilinearTensorProductKernel : public framework::OpKernel<T> {
       math::gemm<Place, T>(ctx.device_context(), CblasNoTrans, CblasNoTrans,
                            batch_size, y_dim, x_dim, 1, x->data<T>(),
                            weight_mat.data<T>(), 0, left_mul.data<T>());
+      Eigen::array<int, 2> shape({{static_cast<int>(out->dims()[0]), 1}});
       output_col_vec.device(place) =
           (left_mul_mat * y_mat).sum(Eigen::DSizes<int, 1>(1));
     }
@@ -174,7 +175,7 @@ class BilinearTensorProductGradKernel : public framework::OpKernel<T> {
     // Caculate the gradient of Input(Bias).
     if (d_bias) {
       d_bias->mutable_data<T>(ctx.GetPlace());
-      auto d_bias_mat = EigenMatrix<T>::From(*d_bias);
+      auto d_bias_mat = framework::EigenVector<T>::Flatten(*d_bias);
       d_bias_mat.device(place) = d_out_mat.sum(Eigen::DSizes<int, 1>(0));
     }
   }