diff --git a/tensorflow/core/kernels/mkl_fused_batch_norm_op.cc b/tensorflow/core/kernels/mkl_fused_batch_norm_op.cc
index 40e4825c0fa..115b3597964 100644
--- a/tensorflow/core/kernels/mkl_fused_batch_norm_op.cc
+++ b/tensorflow/core/kernels/mkl_fused_batch_norm_op.cc
@@ -1008,7 +1008,7 @@ class MklFusedBatchNormOp : public OpKernel {
                               tf_shape_scale, mkl_shape_saved_mean);
     DCHECK(*saved_mean_tensor);
 
-    // Set NAN mean value in case of empty input tensor
+    // Set 0 mean value in case of empty input tensor
     auto saved_mean_data = (*saved_mean_tensor)->flat<U>().data();
     std::fill_n(saved_mean_data, num_elements, static_cast<U>(0));
 
@@ -1019,7 +1019,7 @@ class MklFusedBatchNormOp : public OpKernel {
                               mkl_shape_saved_variance);
     DCHECK(*saved_variance_tensor);
 
-    // Set NAN variance value in case of empty input tensor
+    // Set 0 variance value in case of empty input tensor
     auto saved_variance_data = (*saved_variance_tensor)->flat<U>().data();
     std::fill_n(saved_variance_data, num_elements, static_cast<U>(0));
 
@@ -1346,16 +1346,12 @@ class MklFusedBatchNormGradOp : public OpKernel {
     mkl_shape_p.SetMklTensor(false);
     AllocateOutputSetMklShape(context, kP1Index, &p1_tensor, TensorShape({}),
                               mkl_shape_p);
-#ifndef ENABLE_MKLDNN_V1
     std::fill_n(p1_tensor->flat<U>().data(), p1_tensor->shape().num_elements(),
                 static_cast<U>(0));
-#endif  // !ENABLE_MKLDNN_V1
     AllocateOutputSetMklShape(context, kP2Index, &p2_tensor, TensorShape({}),
                               mkl_shape_p);
-#ifndef ENABLE_MKLDNN_V1
     std::fill_n(p2_tensor->flat<U>().data(), p2_tensor->shape().num_elements(),
                 static_cast<U>(0));
-#endif  // !ENABLE_MKLDNN_V1
   }
 
   memory::dims GetMeanVarianceDims() { return memory::dims({1, depth_}); }