diff --git a/src/operator/nn/batch_norm.cc b/src/operator/nn/batch_norm.cc
index 6254a1e18662..50a331912697 100644
--- a/src/operator/nn/batch_norm.cc
+++ b/src/operator/nn/batch_norm.cc
@@ -112,7 +112,7 @@ void BatchNormForwardImpl(mshadow::Stream<cpu> *,
   AccReal *mean = meanVector.dptr<AccReal>();
   AccReal  *var = varianceVector.dptr<AccReal>();
 
-  const bool is_train_and_not_global_stats = ctx.is_train && !param_.use_global_stats;
+  const bool is_train_and_not_global_stats = ctx.need_grad && !param_.use_global_stats;
   const size_t channelCount = inputData.ChannelCount();
   const size_t itemCountPerChannel = inputData.Size() / channelCount;
 
@@ -226,7 +226,7 @@ void BatchNormBackwardImpl(mshadow::Stream<cpu> *,
   AccReal *gradWeightData = gradWeight.dptr<AccReal>();
   AccReal *gradBiasData = gradBias.dptr<AccReal>();
 
-  const bool is_train_and_not_global_stats = ctx.is_train && !param_.use_global_stats;
+  const bool is_train_and_not_global_stats = ctx.need_grad && !param_.use_global_stats;
 
   #pragma omp parallel for
   for (int channel = 0; channel < static_cast<int>(channelCount); ++channel) {
diff --git a/src/operator/nn/mkldnn/mkldnn_deconvolution.cc b/src/operator/nn/mkldnn/mkldnn_deconvolution.cc
index a6d6b24235c8..67316fb1efb3 100644
--- a/src/operator/nn/mkldnn/mkldnn_deconvolution.cc
+++ b/src/operator/nn/mkldnn/mkldnn_deconvolution.cc
@@ -251,7 +251,7 @@ void MKLDNNDeconvForward::SetDataHandle(const DeconvolutionParam& param,
   auto data_mem = in_data.GetMKLDNNDataReorder(
       fwd_pd.diff_dst_primitive_desc());
   const mkldnn::memory *weight_mem;
-  if (ctx.is_train) {
+  if (ctx.need_grad) {
     // TODO(zhengda) kvstore doesn't handle MKLDNN correctly. Let's reorder it
     // to the default format for now.
     if (weight.IsMKLDNNData())
diff --git a/src/operator/nn/mkldnn/mkldnn_lrn-inl.h b/src/operator/nn/mkldnn/mkldnn_lrn-inl.h
index 31b293a14c2c..325d0f6f3355 100644
--- a/src/operator/nn/mkldnn/mkldnn_lrn-inl.h
+++ b/src/operator/nn/mkldnn/mkldnn_lrn-inl.h
@@ -180,7 +180,7 @@ static MKLDNNLRNFwd &GetLRNFwd(const LRNParam& param,
                                             OpHash> lrn_fwds;
 #endif
   auto kind_ =
-      ctx.is_train ? prop_kind::forward_training : prop_kind::forward_scoring;
+      ctx.need_grad ? prop_kind::forward_training : prop_kind::forward_scoring;
 
   MKLDNNLRNSignature key(param);
   key.AddSign(kind_);
diff --git a/src/operator/nn/mkldnn/mkldnn_pooling.cc b/src/operator/nn/mkldnn/mkldnn_pooling.cc
index f4d681ded78d..994fc2b1310c 100644
--- a/src/operator/nn/mkldnn/mkldnn_pooling.cc
+++ b/src/operator/nn/mkldnn/mkldnn_pooling.cc
@@ -269,7 +269,7 @@ MKLDNNPoolingFwd &GetPoolingFwd(const PoolingParam &param,
 void MKLDNNPoolingCompute(const OpContext &ctx, const PoolingParam &param,
                           const NDArray &in_data, const OpReqType req,
                           const NDArray &out_data, const NDArray *workspace) {
-  auto &fwd = GetPoolingFwd(param, ctx.is_train, in_data, out_data);
+  auto &fwd = GetPoolingFwd(param, ctx.need_grad, in_data, out_data);
   fwd.SetNewMem(in_data, out_data, req, workspace);
   fwd.Execute(out_data);
 }