diff --git a/paddle/fluid/operators/batch_norm_op.cc b/paddle/fluid/operators/batch_norm_op.cc
index f6295337d1f1042f021f7b0de15f476225beb3a2..56111c66339f2835d0202a108230cb8de7c985e6 100644
--- a/paddle/fluid/operators/batch_norm_op.cc
+++ b/paddle/fluid/operators/batch_norm_op.cc
@@ -245,8 +245,8 @@ class BatchNormKernel<platform::CPUDeviceContext, T>
           variance_out->mutable_data<T>(ctx.GetPlace()), C);
 
       if ((N * sample_size) == 1) {
-        LOG(WARNING) << "Only 1 element in normalization dimension, "
-                     << "we skip the batch norm calculation, let y = x.";
+        // Only 1 element in normalization dimension,
+        // we skip the batch norm calculation, let y = x.
         framework::TensorCopy(*x, ctx.GetPlace(), y);
         return;
       }
diff --git a/paddle/fluid/operators/batch_norm_op.cu b/paddle/fluid/operators/batch_norm_op.cu
index 9b50a4a61a87a61088d8c34ebcc06a2a281a01c0..49ff7069ba075fa156fa2f875684d0786af8e82b 100644
--- a/paddle/fluid/operators/batch_norm_op.cu
+++ b/paddle/fluid/operators/batch_norm_op.cu
@@ -152,8 +152,8 @@ class BatchNormKernel<platform::CUDADeviceContext, T>
       functor(dev_ctx, saved_variance, static_cast<BatchNormParamType<T>>(0));
 
       if ((N * H * W * D) == 1) {
-        LOG(WARNING) << "Only 1 element in normalization dimension, "
-                     << "we skip the batch norm calculation, let y = x.";
+        // Only 1 element in normalization dimension,
+        // skip the batch norm calculation, let y = x.
         framework::TensorCopy(*x, ctx.GetPlace(), y);
       } else {
         double this_factor = 1. - momentum;