Rename MKL-related feature macros.

The existing feature macros are named INTEL_MKL to indicate that any flavor of
MKL is available, INTEL_MKL_ML to indicate that *only* MKL-ML is available
(i.e. MKL-DNN is not), and DO_NOT_USE_ML to indicate that *only* MKL-DNN is
available (i.e. MKL-ML is not).

This change renames INTEL_MKL_ML to INTEL_MKL_ML_ONLY and DO_NOT_USE_ML to
INTEL_MKL_DNN_ONLY. The meanings of the macros have not changed.

This change also adds a few sanity checks to mkl_util.h that ensures that the
combination of INTEL_MKL, INTEL_MKL_ML_ONLY, and INTEL_MKL_DNN_ONLY is
logically consistent: the *_ONLY macros may not both be defined, and if either
of them is defined, bare INTEL_MKL must also be defined.

PiperOrigin-RevId: 208313735

33 files changed, 125 insertions, 125 deletions

diff --git a/tensorflow/compiler/xla/service/cpu/runtime_matmul_mkl.cc b/tensorflow/compiler/xla/service/cpu/runtime_matmul_mkl.cc
index 997fdd2ab3..8dc5f3c93b 100644
--- a/tensorflow/compiler/xla/service/cpu/runtime_matmul_mkl.cc
+++ b/tensorflow/compiler/xla/service/cpu/runtime_matmul_mkl.cc
@@ -13,7 +13,7 @@ See the License for the specific language governing permissions and
 limitations under the License.
 ==============================================================================*/
 
-#if defined(INTEL_MKL) && !defined(DO_NOT_USE_ML)
+#if defined(INTEL_MKL) && !defined(INTEL_MKL_DNN_ONLY)
 #include "tensorflow/compiler/xla/service/cpu/runtime_matmul_mkl.h"
 #include "third_party/intel_mkl_ml/include/mkl_cblas.h"
 #include "third_party/intel_mkl_ml/include/mkl_service.h"
diff --git a/tensorflow/core/common_runtime/mkl_cpu_allocator.h b/tensorflow/core/common_runtime/mkl_cpu_allocator.h
index 94e10dbfa2..99bd43e090 100644
--- a/tensorflow/core/common_runtime/mkl_cpu_allocator.h
+++ b/tensorflow/core/common_runtime/mkl_cpu_allocator.h
@@ -28,7 +28,7 @@ limitations under the License.
 #include "tensorflow/core/lib/strings/str_util.h"
 #include "tensorflow/core/platform/mem.h"
 
-#ifndef DO_NOT_USE_ML
+#ifndef INTEL_MKL_DNN_ONLY
 #include "i_malloc.h"
 #endif
 
@@ -98,7 +98,7 @@ class MklCPUAllocator : public VisitableAllocator {
     VLOG(1) << "MklCPUAllocator: Setting max_mem_bytes: " << max_mem_bytes;
     allocator_ = new BFCAllocator(new MklSubAllocator, max_mem_bytes,
                                   kAllowGrowth, kName);
-#ifndef DO_NOT_USE_ML
+#ifndef INTEL_MKL_DNN_ONLY
     // For redirecting all allocations from MKL to this allocator
     // From: http://software.intel.com/en-us/node/528565
     i_malloc = MallocHook;
diff --git a/tensorflow/core/graph/mkl_layout_pass.cc b/tensorflow/core/graph/mkl_layout_pass.cc
index c22e0a3872..5683944e46 100644
--- a/tensorflow/core/graph/mkl_layout_pass.cc
+++ b/tensorflow/core/graph/mkl_layout_pass.cc
@@ -43,7 +43,7 @@ limitations under the License.
 
 namespace tensorflow {
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
 // This pass implements rewriting of graph to support following scenarios:
 // (A) Merging nodes in the graph
@@ -2211,7 +2211,7 @@ Status MklLayoutRewritePass::Run(const GraphOptimizationPassOptions& options) {
   return Status::OK();
 }
 
-#else   // INTEL_MKL_ML
+#else   // INTEL_MKL_ML_ONLY
 
 // This pass implements rewriting of graph to support following scenarios:
 // (A) Merging nodes in the graph
@@ -4474,7 +4474,7 @@ Status MklLayoutRewritePass::Run(const GraphOptimizationPassOptions& options) {
 
   return Status::OK();
 }
-#endif  // INTEL_MKL_ML
+#endif  // INTEL_MKL_ML_ONLY
 }  // namespace tensorflow
 
 #endif
diff --git a/tensorflow/core/graph/mkl_layout_pass_test.cc b/tensorflow/core/graph/mkl_layout_pass_test.cc
index a41f5861af..e8bac847e5 100644
--- a/tensorflow/core/graph/mkl_layout_pass_test.cc
+++ b/tensorflow/core/graph/mkl_layout_pass_test.cc
@@ -37,7 +37,7 @@ limitations under the License.
 
 namespace tensorflow {
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
 namespace {
 
@@ -1898,7 +1898,7 @@ BENCHMARK(BM_MklLayoutRewritePass)->Arg(1000)->Arg(10000);
 
 }  // namespace
 
-#else  // INTEL_MKL_ML
+#else  // INTEL_MKL_ML_ONLY
 
 // NOTE: Unit tests in this file rely on a topological sorted graph for
 // printing. But since sibling nodes of a node in the topologically sorted graph
@@ -3582,7 +3582,7 @@ BENCHMARK(BM_MklLayoutRewritePass)->Arg(1000)->Arg(10000);
 
 }  // namespace
 
-#endif  // INTEL_MKL_ML
+#endif  // INTEL_MKL_ML_ONLY
 
 }  // namespace tensorflow
 
diff --git a/tensorflow/core/kernels/batch_matmul_op_complex.cc b/tensorflow/core/kernels/batch_matmul_op_complex.cc
index b77c80c01f..54c45bfe63 100644
--- a/tensorflow/core/kernels/batch_matmul_op_complex.cc
+++ b/tensorflow/core/kernels/batch_matmul_op_complex.cc
@@ -17,7 +17,7 @@ limitations under the License.
 
 namespace tensorflow {
 
-#if !defined(INTEL_MKL) || defined(DO_NOT_USE_ML)
+#if !defined(INTEL_MKL) || defined(INTEL_MKL_DNN_ONLY)
 TF_CALL_complex64(REGISTER_BATCH_MATMUL_CPU);
 TF_CALL_complex128(REGISTER_BATCH_MATMUL_CPU);
 #endif
diff --git a/tensorflow/core/kernels/batch_matmul_op_real.cc b/tensorflow/core/kernels/batch_matmul_op_real.cc
index aa7a2752e8..584b507c70 100644
--- a/tensorflow/core/kernels/batch_matmul_op_real.cc
+++ b/tensorflow/core/kernels/batch_matmul_op_real.cc
@@ -21,7 +21,7 @@ limitations under the License.
 
 namespace tensorflow {
 
-#if !defined(INTEL_MKL) || defined(DO_NOT_USE_ML)
+#if !defined(INTEL_MKL) || defined(INTEL_MKL_DNN_ONLY)
 TF_CALL_float(REGISTER_BATCH_MATMUL_CPU);
 TF_CALL_double(REGISTER_BATCH_MATMUL_CPU);
 #endif
diff --git a/tensorflow/core/kernels/matmul_op.cc b/tensorflow/core/kernels/matmul_op.cc
index 5d4737549b..79967aab38 100644
--- a/tensorflow/core/kernels/matmul_op.cc
+++ b/tensorflow/core/kernels/matmul_op.cc
@@ -598,11 +598,11 @@ TF_CALL_float(REGISTER_CPU_EIGEN);
 // to use only opensource MKL DNN then use default implementation for these
 // types otherwise use GEMM from MKL ML binary
 
-#if defined(DO_NOT_USE_ML)
+#if defined(INTEL_MKL_DNN_ONLY)
 TF_CALL_complex64(REGISTER_CPU);
 TF_CALL_complex128(REGISTER_CPU);
 TF_CALL_double(REGISTER_CPU);
-#else  // DO_NOT_USE_ML
+#else  // INTEL_MKL_DNN_ONLY
 TF_CALL_complex64(REGISTER_CPU_EIGEN);
 TF_CALL_complex128(REGISTER_CPU_EIGEN);
 TF_CALL_double(REGISTER_CPU_EIGEN);
diff --git a/tensorflow/core/kernels/mkl_aggregate_ops.cc b/tensorflow/core/kernels/mkl_aggregate_ops.cc
index 3d04aeeb3e..28edf51546 100644
--- a/tensorflow/core/kernels/mkl_aggregate_ops.cc
+++ b/tensorflow/core/kernels/mkl_aggregate_ops.cc
@@ -24,8 +24,7 @@ limitations under the License.
 #include "tensorflow/core/lib/gtl/inlined_vector.h"
 #include "tensorflow/core/platform/logging.h"
 
-
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 using mkldnn::stream;
 using mkldnn::sum;
@@ -38,7 +37,7 @@ using mkldnn::sum;
 namespace tensorflow {
 typedef Eigen::ThreadPoolDevice CPUDevice;
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
 template <typename Device, typename T>
 class MklAddNOp : public OpKernel {
@@ -286,7 +285,7 @@ class MklAddNOp : public OpKernel {
   } MklAddNOpContext;
 };
 
-#else  // INTEL_MKL_ML
+#else  // INTEL_MKL_ML_ONLY
 template <typename Device, typename T>
 class MklAddNOp : public OpKernel {
  public:
diff --git a/tensorflow/core/kernels/mkl_avgpooling_op.cc b/tensorflow/core/kernels/mkl_avgpooling_op.cc
index d3566c2e37..969baecc51 100644
--- a/tensorflow/core/kernels/mkl_avgpooling_op.cc
+++ b/tensorflow/core/kernels/mkl_avgpooling_op.cc
@@ -24,7 +24,7 @@
 
 #include "tensorflow/core/kernels/mkl_pooling_ops_common.h"
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 using mkldnn::algorithm;
 using mkldnn::engine;
@@ -40,7 +40,7 @@ namespace tensorflow {
 
 typedef Eigen::ThreadPoolDevice CPUDevice;
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
 template <typename Device, typename T>
 class MklAvgPoolingOp : public OpKernel {
@@ -664,7 +664,7 @@ class MklAvgPoolingGradOp : public MklPoolingBackwardOpBase<T> {
   }
 };  // MklAvgPoolingGradOp
 
-#endif  // INTEL_MKL_ML
+#endif  // INTEL_MKL_ML_ONLY
 
 REGISTER_KERNEL_BUILDER(Name("_MklAvgPool")
                             .Device(DEVICE_CPU)
diff --git a/tensorflow/core/kernels/mkl_batch_matmul_op.cc b/tensorflow/core/kernels/mkl_batch_matmul_op.cc
index 45328b03d6..0841395dc3 100644
--- a/tensorflow/core/kernels/mkl_batch_matmul_op.cc
+++ b/tensorflow/core/kernels/mkl_batch_matmul_op.cc
@@ -25,7 +25,7 @@ limitations under the License.
 
 #define EIGEN_USE_THREADS
 
-#if defined(INTEL_MKL) && !defined(DO_NOT_USE_ML)
+#if defined(INTEL_MKL) && !defined(INTEL_MKL_DNN_ONLY)
 #include <vector>
 #include "mkl_cblas.h"
 #include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
diff --git a/tensorflow/core/kernels/mkl_concat_op.cc b/tensorflow/core/kernels/mkl_concat_op.cc
index d8efb1be3e..8ad7ebb51f 100644
--- a/tensorflow/core/kernels/mkl_concat_op.cc
+++ b/tensorflow/core/kernels/mkl_concat_op.cc
@@ -27,8 +27,7 @@ limitations under the License.
 #include "tensorflow/core/lib/core/status.h"
 #include "tensorflow/core/platform/types.h"
 
-
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 
 using mkldnn::concat;
@@ -64,7 +63,7 @@ class EigenConcatBaseOp : public OpKernel {
   // we need to have empty Compute because Compute is pure virtual function.
   void Compute(OpKernelContext* c) {}
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
   void Compute(OpKernelContext* c, const std::vector<Tensor>& values) {
     const Tensor* concat_dim_tensor;
@@ -232,7 +231,7 @@ class EigenConcatBaseOp : public OpKernel {
 #endif
 };
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
 // --------------------------------------------------------------------------
 //                      Mkl Concat Op
diff --git a/tensorflow/core/kernels/mkl_conv_grad_bias_ops.cc b/tensorflow/core/kernels/mkl_conv_grad_bias_ops.cc
index f857be6c32..7c687f6581 100644
--- a/tensorflow/core/kernels/mkl_conv_grad_bias_ops.cc
+++ b/tensorflow/core/kernels/mkl_conv_grad_bias_ops.cc
@@ -18,7 +18,7 @@ limitations under the License.
 // bias.
 
 #ifdef INTEL_MKL
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
 #define USE_EIGEN_TENSOR
 #define EIGEN_USE_THREADS
@@ -39,7 +39,7 @@ limitations under the License.
 #include "tensorflow/core/util/use_cudnn.h"
 #include "tensorflow/core/util/work_sharder.h"
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 #include "mkl_dnn.h"
 #include "mkl_dnn_types.h"
 #endif
@@ -265,5 +265,5 @@ class MklConv2DCustomBackpropBiasOp : public OpKernel {
 TF_CALL_float(REGISTER_CPU_KERNELS);
 #undef REGISTER_CPU_KERNELS
 } /* namespace tensorflow */
-#endif /* INTEL_MKL_ML */
+#endif /* INTEL_MKL_ML_ONLY */
 #endif /* INTEL_MKL */
diff --git a/tensorflow/core/kernels/mkl_conv_grad_filter_ops.cc b/tensorflow/core/kernels/mkl_conv_grad_filter_ops.cc
index b73a119a88..50c25e1da7 100644
--- a/tensorflow/core/kernels/mkl_conv_grad_filter_ops.cc
+++ b/tensorflow/core/kernels/mkl_conv_grad_filter_ops.cc
@@ -38,8 +38,7 @@ limitations under the License.
 #include "tensorflow/core/util/use_cudnn.h"
 #include "tensorflow/core/util/work_sharder.h"
 
-
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 
 using mkldnn::convolution_backward_weights;
@@ -56,7 +55,7 @@ using mkldnn::stream;
 namespace tensorflow {
 typedef Eigen::ThreadPoolDevice CPUDevice;
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 
 struct MklConvBwdFilterParams {
   memory::dims src_dims;
@@ -358,7 +357,7 @@ class MklConv2DBwdFilterPrimitiveFactory : public MklPrimitiveFactory<T> {
 
 #endif
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
 template <typename Device, class T>
 class MklConv2DCustomBackpropFilterOp : public OpKernel {
@@ -1050,7 +1049,7 @@ class MklConv2DCustomBackpropFilterOp
 TF_CALL_float(REGISTER_MKL_FILTER_KERNELS);
 #undef REGISTER_MKL_FILTER_KERNELS
 
-#endif  // INTEL_MKL_ML
+#endif  // INTEL_MKL_ML_ONLY
 
 }  // namespace tensorflow
 
diff --git a/tensorflow/core/kernels/mkl_conv_grad_input_ops.cc b/tensorflow/core/kernels/mkl_conv_grad_input_ops.cc
index 39498f1a80..38e014d68e 100644
--- a/tensorflow/core/kernels/mkl_conv_grad_input_ops.cc
+++ b/tensorflow/core/kernels/mkl_conv_grad_input_ops.cc
@@ -23,7 +23,7 @@ limitations under the License.
 #define EIGEN_USE_THREADS
 #include <algorithm>
 #include <vector>
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 #include "mkl_dnn.h"
 #include "mkl_dnn_types.h"
 #endif
@@ -46,7 +46,7 @@ limitations under the License.
 #include "tensorflow/core/util/use_cudnn.h"
 #include "tensorflow/core/util/work_sharder.h"
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 
 using mkldnn::convolution_backward_data;
@@ -57,7 +57,7 @@ using mkldnn::stream;
 namespace tensorflow {
 typedef Eigen::ThreadPoolDevice CPUDevice;
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 
 /// utility classes enabling primitive reuse for backward conv2d ops.
 struct MklConvBwdInputParams {
@@ -294,7 +294,7 @@ class MklConv2DBwdInputPrimitiveFactory : public MklPrimitiveFactory<T> {
 
 #endif
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
 template <typename Device, class T>
 class MklConv2DCustomBackpropInputOp : public OpKernel {
@@ -839,7 +839,7 @@ class MklConv2DCustomBackpropInputOp
   }
 };
 
-#endif  // INTEL_MKL_ML
+#endif  // INTEL_MKL_ML_ONLY
 
 #define REGISTER_MKL_CPU_KERNELS(T)                                 \
   REGISTER_KERNEL_BUILDER(Name("_MklConv2DBackpropInput")           \
diff --git a/tensorflow/core/kernels/mkl_conv_ops.cc b/tensorflow/core/kernels/mkl_conv_ops.cc
index 62396eeb8b..bca1aa21a8 100644
--- a/tensorflow/core/kernels/mkl_conv_ops.cc
+++ b/tensorflow/core/kernels/mkl_conv_ops.cc
@@ -42,7 +42,7 @@ limitations under the License.
 
 #include "tensorflow/core/util/mkl_util.h"
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 
 using mkldnn::prop_kind;
@@ -57,7 +57,7 @@ using mkldnn::convolution_direct;
 
 namespace tensorflow {
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 
 // This structure aggregates multiple inputs to Conv2DFwd* methods.
 struct MklConvFwdParams {
@@ -329,7 +329,7 @@ class MklConv2DFwdPrimitiveFactory : public MklPrimitiveFactory<T> {
 typedef Eigen::ThreadPoolDevice CPUDevice;
 
 // For now, MKL-ML is default. So making MKL-DNN not a default choice.
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 template <typename Device, typename T, bool biasEnabled>
 class MklConv2DOp : public OpKernel {
  public:
diff --git a/tensorflow/core/kernels/mkl_conv_ops.h b/tensorflow/core/kernels/mkl_conv_ops.h
index 3f154ff33b..838c06f49d 100644
--- a/tensorflow/core/kernels/mkl_conv_ops.h
+++ b/tensorflow/core/kernels/mkl_conv_ops.h
@@ -40,7 +40,7 @@ limitations under the License.
 
 #include "tensorflow/core/util/mkl_util.h"
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 
 using mkldnn::prop_kind;
@@ -52,7 +52,7 @@ using mkldnn::convolution_forward;
 
 namespace tensorflow {
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 
 class MklDnnConvUtil {
  protected:
@@ -397,8 +397,7 @@ class MklConv2DBackpropCommonOp : public OpKernel {
   TensorFormat data_format_;  // NCHW or NHWC
 };
 
-#endif  // INTEL_MKL_ML
-
+#endif  // INTEL_MKL_ML_ONLY
 
 /////////////////////////////////////////////////////////////////////
 ///  Dummy Mkl op that is just used for operators that are intermediate
diff --git a/tensorflow/core/kernels/mkl_fused_batch_norm_op.cc b/tensorflow/core/kernels/mkl_fused_batch_norm_op.cc
index aa572fb0a3..2ec6c8fa89 100644
--- a/tensorflow/core/kernels/mkl_fused_batch_norm_op.cc
+++ b/tensorflow/core/kernels/mkl_fused_batch_norm_op.cc
@@ -21,8 +21,7 @@ limitations under the License.
 #include "tensorflow/core/framework/tensor_types.h"
 #include "tensorflow/core/util/tensor_format.h"
 
-
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 using mkldnn::batch_normalization_backward;
 using mkldnn::batch_normalization_forward;
@@ -41,7 +40,7 @@ using mkldnn::use_scale_shift;
 namespace tensorflow {
 using CPUDevice = Eigen::ThreadPoolDevice;
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
 template <typename Device, typename T>
 class MklFusedBatchNormOp : public OpKernel {
@@ -684,7 +683,7 @@ class MklFusedBatchNormGradOp : public OpKernel {
 };
 #endif
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 
 struct MklBatchNormFwdParams {
   memory::dims src_dims;
diff --git a/tensorflow/core/kernels/mkl_identity_op.cc b/tensorflow/core/kernels/mkl_identity_op.cc
index b02cc5384c..b57e816028 100644
--- a/tensorflow/core/kernels/mkl_identity_op.cc
+++ b/tensorflow/core/kernels/mkl_identity_op.cc
@@ -24,20 +24,20 @@ limitations under the License.
 #include "tensorflow/core/lib/core/status.h"
 #include "tensorflow/core/platform/logging.h"
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 #include "mkl_dnn.h"
 #include "mkl_dnn_types.h"
 #endif
 #include "tensorflow/core/util/mkl_util.h"
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 #endif
 
 namespace tensorflow {
 typedef Eigen::ThreadPoolDevice CPUDevice;
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
 template <typename Device, typename T>
 class MklIdentityOp : public OpKernel {
diff --git a/tensorflow/core/kernels/mkl_input_conversion_op.cc b/tensorflow/core/kernels/mkl_input_conversion_op.cc
index dc4da33a06..06ce820ae9 100644
--- a/tensorflow/core/kernels/mkl_input_conversion_op.cc
+++ b/tensorflow/core/kernels/mkl_input_conversion_op.cc
@@ -32,7 +32,7 @@ limitations under the License.
 #include "tensorflow/core/kernels/mkl_tfconv_op.h"
 #include "tensorflow/core/util/mkl_util.h"
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 
 using mkldnn::stream;
@@ -60,7 +60,7 @@ typedef Eigen::ThreadPoolDevice CPUDevice;
 //     convert the TF format input to MKL format
 ///////////////////////////////////////////////////////////
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 template <typename Device, typename T>
 class MklInputConversionOp : public OpKernel {
  public:
diff --git a/tensorflow/core/kernels/mkl_lrn_op.cc b/tensorflow/core/kernels/mkl_lrn_op.cc
index 7966c271d5..22ff4cd80f 100644
--- a/tensorflow/core/kernels/mkl_lrn_op.cc
+++ b/tensorflow/core/kernels/mkl_lrn_op.cc
@@ -35,7 +35,7 @@ limitations under the License.
 #include "tensorflow/core/util/work_sharder.h"
 #endif
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 using mkldnn::lrn_across_channels;
 using mkldnn::lrn_backward;
@@ -69,7 +69,7 @@ void GetBandMatrix(int depth, int depth_radius,
 
 }  // namespace
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
 template <typename T>
 class MklLRNOp : public OpKernel {
@@ -1345,7 +1345,7 @@ class MklLRNGradOp : public OpKernel {
   float beta_;
 };
 
-#endif  // INTEL_MKL_ML
+#endif  // INTEL_MKL_ML_ONLY
 
 #define REGISTER_MKL_LRN_CPU(T)                                     \
   REGISTER_KERNEL_BUILDER(Name("_MklLRN")                           \
diff --git a/tensorflow/core/kernels/mkl_matmul_op.cc b/tensorflow/core/kernels/mkl_matmul_op.cc
index fd261433a0..077d62ce32 100644
--- a/tensorflow/core/kernels/mkl_matmul_op.cc
+++ b/tensorflow/core/kernels/mkl_matmul_op.cc
@@ -31,7 +31,7 @@ limitations under the License.
 #include "tensorflow/core/kernels/fill_functor.h"
 
 // This header file is part of MKL ML, need equivalent file in MKL DNN
-#ifndef DO_NOT_USE_ML
+#ifndef INTEL_MKL_DNN_ONLY
 #include "mkl_cblas.h"
 #else
 #include "mkldnn.h"
@@ -155,7 +155,7 @@ class MklMatMulOp : public OpKernel {
     // 1.0 and 0.0 respectively.
     const float alpha = 1.0f;
     const float beta = 0.0f;
-#if defined(DO_NOT_USE_ML)
+#if defined(INTEL_MKL_DNN_ONLY)
     const char* const ftrans[] = {"N", "T", "C"};
     int index_transa = transa ? 1 : 0;
     int index_transb = transb ? 1 : 0;
@@ -173,7 +173,7 @@ class MklMatMulOp : public OpKernel {
   }
 
   // MKLDNN only supports SGEMM
-#ifndef DO_NOT_USE_ML
+#ifndef INTEL_MKL_DNN_ONLY
 
   // Matrix-Matrix Multiplication with FP64 tensors. For detailed info about
   // parameters, look at FP32 function description.
@@ -229,7 +229,7 @@ class MklMatMulOp : public OpKernel {
 // additional types
 TF_CALL_float(REGISTER_CPU);
 
-#ifndef DO_NOT_USE_ML
+#ifndef INTEL_MKL_DNN_ONLY
 TF_CALL_double(REGISTER_CPU);
 TF_CALL_complex64(REGISTER_CPU);
 TF_CALL_complex128(REGISTER_CPU);
diff --git a/tensorflow/core/kernels/mkl_maxpooling_op.cc b/tensorflow/core/kernels/mkl_maxpooling_op.cc
index 0a2151566e..e149f003e5 100644
--- a/tensorflow/core/kernels/mkl_maxpooling_op.cc
+++ b/tensorflow/core/kernels/mkl_maxpooling_op.cc
@@ -22,7 +22,7 @@ limitations under the License.
 #include "tensorflow/core/util/mkl_util.h"
 #include "tensorflow/core/util/padding.h"
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include <algorithm>
 #include "mkldnn.hpp"
 using mkldnn::algorithm;
@@ -40,7 +40,7 @@ namespace tensorflow {
 typedef Eigen::ThreadPoolDevice CPUDevice;
 
 // MKL-DNN is now default. MKL-ML must be specified explicitly.
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
 // An implementation of MaxPooling (forward).
 template <typename Device, typename T>
@@ -817,7 +817,7 @@ class MklMaxPoolingGradOp : public MklPoolingBackwardOpBase<T> {
   }
 };  // MklMaxPoolingGradOp
 
-#endif  // INTEL_MKL_ML
+#endif  // INTEL_MKL_ML_ONLY
 
 REGISTER_KERNEL_BUILDER(Name("_MklMaxPool")
                             .Device(DEVICE_CPU)
diff --git a/tensorflow/core/kernels/mkl_pooling_ops_common.cc b/tensorflow/core/kernels/mkl_pooling_ops_common.cc
index 915878d9ea..d7ad3f9dcd 100644
--- a/tensorflow/core/kernels/mkl_pooling_ops_common.cc
+++ b/tensorflow/core/kernels/mkl_pooling_ops_common.cc
@@ -223,7 +223,7 @@ void MklPoolParameters::Init(OpKernelContext* context,
   Init(context, ksize, stride, padding, data_format);
 }
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 // Initialization for MKL format
 void MklPoolParameters::Init(OpKernelContext* context,
                              const std::vector<int32>& ksize,
@@ -253,7 +253,7 @@ void MklPoolParameters::Init(OpKernelContext* context,
 
   Init(context, ksize, stride, padding, data_format);
 }
-#endif  // INTEL_MKL_ML
+#endif  // INTEL_MKL_ML_ONLY
 // Common Initialization for TensorFlow and MKL formats
 void MklPoolParameters::Init(OpKernelContext* context,
                              const std::vector<int32>& ksize,
@@ -288,7 +288,7 @@ void MklPoolParameters::Init(OpKernelContext* context,
     OP_REQUIRES_OK(context, GetWindowedOutputSizeVerbose(
                                 tensor_in_cols, window_cols, col_stride,
                                 padding, &out_width, &pad_left, &pad_right));
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
     // TF can work with int64, but mkldnn only supports int32
     // Fail if the height or width are greater than MAX_INT
 
diff --git a/tensorflow/core/kernels/mkl_pooling_ops_common.h b/tensorflow/core/kernels/mkl_pooling_ops_common.h
index 3a3de1c58b..ec7af5092d 100644
--- a/tensorflow/core/kernels/mkl_pooling_ops_common.h
+++ b/tensorflow/core/kernels/mkl_pooling_ops_common.h
@@ -22,7 +22,7 @@ limitations under the License.
 #include "tensorflow/core/util/mkl_util.h"
 #include "tensorflow/core/util/padding.h"
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 using mkldnn::memory;
 using mkldnn::pooling_backward;
@@ -405,7 +405,7 @@ struct MklPoolParameters {
   void Init(OpKernelContext* context, const std::vector<int32>& ksize,
             const std::vector<int32>& stride, Padding padding,
             TensorFormat data_format, const TensorShape& tensor_in_shape);
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
   void Init(OpKernelContext* context, const std::vector<int32>& ksize,
             const std::vector<int32>& stride, Padding padding,
             TensorFormat data_format, const MklShape* mkl_in_shape);
@@ -422,7 +422,7 @@ struct MklPoolParameters {
             TensorFormat data_format);
 };
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 
 template <class T>
 class MklPoolingOpBase : public OpKernel {
@@ -674,7 +674,7 @@ class MklPoolingBackwardOpBase : public MklPoolingOpBase<T> {
     return grad_reorder_needed ? target_diff_dst_md : original_input_grad_md;
   }
 };
-#endif  // INTEL_MKL_ML
+#endif  // INTEL_MKL_ML_ONLY
 
 //-------------------------------------------------------------------
 // Utility functions
diff --git a/tensorflow/core/kernels/mkl_relu_op.cc b/tensorflow/core/kernels/mkl_relu_op.cc
index 78abbdb730..05034894e5 100644
--- a/tensorflow/core/kernels/mkl_relu_op.cc
+++ b/tensorflow/core/kernels/mkl_relu_op.cc
@@ -23,8 +23,7 @@ limitations under the License.
 #include "tensorflow/core/framework/tensor.h"
 #include "tensorflow/core/lib/core/errors.h"
 
-
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 
 using mkldnn::algorithm;
@@ -58,7 +57,7 @@ struct MklReluHelpers {
   }
 };
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
 template <typename Device, typename T>
 class MklReluOp : public OpKernel {
@@ -368,10 +367,7 @@ void MklReluGradOp<Device, T>::Compute(OpKernelContext* context) {
   mkl_context.MklCleanup();
 }
 
-
-
-#else  // INTEL_MKL_ML
-
+#else  // INTEL_MKL_ML_ONLY
 
 template <typename Device, typename T, algorithm alg_kind>
 class MklReluOpBase : public OpKernel {
@@ -874,7 +870,7 @@ class MklTanhGradOp : public MklReluGradOpBase<Device, T, eltwise_tanh> {
                           MklReluGradOp<CPUDevice, type>);
 TF_CALL_float(REGISTER_RELU_MKL_SUPPORTED_KERNELS_TYPES);
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 
 // register dnn kernels for supported operations and supported types
 #define REGISTER_ELU_MKL_SUPPORTED_KERNELS_TYPES(type)              \
diff --git a/tensorflow/core/kernels/mkl_reshape_op.cc b/tensorflow/core/kernels/mkl_reshape_op.cc
index 9c536df215..d9a7893a53 100644
--- a/tensorflow/core/kernels/mkl_reshape_op.cc
+++ b/tensorflow/core/kernels/mkl_reshape_op.cc
@@ -24,8 +24,7 @@ limitations under the License.
 #include "tensorflow/core/lib/core/status.h"
 #include "tensorflow/core/platform/logging.h"
 
-
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 using mkldnn::stream;
 #else
@@ -42,7 +41,7 @@ class MklReshapeOp : public OpKernel {
  public:
   explicit MklReshapeOp(OpKernelConstruction* context) : OpKernel(context) {}
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
   void Compute(OpKernelContext* context) override {
     const Tensor& input = MklGetInput(context, 0);
     const Tensor& sizes = MklGetInput(context, 1);
@@ -317,7 +316,7 @@ class MklReshapeOp : public OpKernel {
     }
   }
 
-#endif  // INTEL_MKL_ML
+#endif  // INTEL_MKL_ML_ONLY
 
  private:
   const int kInputSlotIdx = 0;
diff --git a/tensorflow/core/kernels/mkl_softmax_op.cc b/tensorflow/core/kernels/mkl_softmax_op.cc
index 638392954e..8bde966be9 100644
--- a/tensorflow/core/kernels/mkl_softmax_op.cc
+++ b/tensorflow/core/kernels/mkl_softmax_op.cc
@@ -15,7 +15,7 @@ limitations under the License.
 
 // See docs in ../ops/nn_ops.cc.
 #ifdef INTEL_MKL
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 
 #include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
 #include "tensorflow/core/framework/numeric_op.h"
@@ -153,5 +153,5 @@ TF_CALL_float(REGISTER_SOFTMAX_MKL_SUPPORTED_KERNELS_TYPES);
 
 }  // namespace tensorflow
 
-#endif  // INTEL_MKL_ML
+#endif  // INTEL_MKL_ML_ONLY
 #endif  // INTEL_MKL
diff --git a/tensorflow/core/kernels/mkl_tfconv_op.h b/tensorflow/core/kernels/mkl_tfconv_op.h
index a9e92f6638..894c2e34e8 100644
--- a/tensorflow/core/kernels/mkl_tfconv_op.h
+++ b/tensorflow/core/kernels/mkl_tfconv_op.h
@@ -32,13 +32,13 @@ limitations under the License.
 #include "tensorflow/core/platform/macros.h"
 #include "tensorflow/core/util/tensor_format.h"
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 #include "mkl_dnn.h"
 #include "mkl_dnn_types.h"
 #endif
 #include "tensorflow/core/util/mkl_util.h"
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 using mkldnn::stream;
 #endif
 
@@ -64,7 +64,7 @@ class MklToTfOp : public OpKernel {
     VLOG(1) << "MKLToTFConversion complete successfully.";
   }
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
   static void ConvertMklToTf(OpKernel* op_kernel, OpKernelContext* context,
                              string data_format_str, DataType op_data_type,
                              bool has_avx512f, uint input_number) {
diff --git a/tensorflow/core/kernels/mkl_transpose_op.cc b/tensorflow/core/kernels/mkl_transpose_op.cc
index 109e634feb..6bbe271c54 100644
--- a/tensorflow/core/kernels/mkl_transpose_op.cc
+++ b/tensorflow/core/kernels/mkl_transpose_op.cc
@@ -18,14 +18,14 @@ limitations under the License.
 #if defined(INTEL_MKL)
 #define EIGEN_USE_THREADS
 
-#if !defined(DO_NOT_USE_ML)
+#if !defined(INTEL_MKL_DNN_ONLY)
 #include "mkl_trans.h"
 #endif
 
 #include "tensorflow/core/kernels/transpose_functor.h"
 #include "tensorflow/core/kernels/transpose_op.h"
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 #include "tensorflow/core/util/mkl_util.h"
 
@@ -50,7 +50,7 @@ namespace tensorflow {
 // REQUIRES: perm is a permutation.
 
 namespace {
-#if !defined(DO_NOT_USE_ML)
+#if !defined(INTEL_MKL_DNN_ONLY)
 template <typename T>
 Status MKLTranspose2D(const char trans, const Tensor& in, Tensor* out);
 
@@ -104,9 +104,9 @@ Status MKLTranspose2D<complex128>(const char trans, const Tensor& in,
 static const char kMKLTranspose = 'T';
 static const char kMKLConjugateTranspose = 'C';
 
-#endif  // if !defined(DO_NOT_USE_ML)
+#endif  // if !defined(INTEL_MKL_DNN_ONLY)
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 // MKL-DNN based Transpose implementation
 template <typename T>
 Status MKLTransposeND(OpKernelContext* ctx, const Tensor& in, Tensor* out,
@@ -154,14 +154,14 @@ Status MKLTransposeND(OpKernelContext* context, const Tensor& in_tensor,
     return errors::Aborted("Operation received an exception:", error_msg);
   }
 }
-#endif  // #ifndef INTEL_MKL_ML
+#endif  // #ifndef INTEL_MKL_ML_ONLY
 
 }  // namespace
 
 Status MklTransposeCpuOp::DoTranspose(OpKernelContext* ctx, const Tensor& in,
                                       gtl::ArraySlice<int32> perm,
                                       Tensor* out) {
-#if !defined(DO_NOT_USE_ML)
+#if !defined(INTEL_MKL_DNN_ONLY)
   if (in.dims() == 2) {
     if (perm[0] == 0 && perm[1] == 1) {
       return Status::OK();
@@ -181,7 +181,7 @@ Status MklTransposeCpuOp::DoTranspose(OpKernelContext* ctx, const Tensor& in,
   }
 #endif
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
   // MKL-DNN has limit on the maximum number of dimensions in a tensor.
   // Fallback to Eigen for not supported cases.
   if (in.dims() <= TENSOR_MAX_DIMS) {
@@ -206,7 +206,7 @@ Status MklConjugateTransposeCpuOp::DoTranspose(OpKernelContext* ctx,
                                                const Tensor& in,
                                                gtl::ArraySlice<int32> perm,
                                                Tensor* out) {
-#if !defined(DO_NOT_USE_ML)
+#if !defined(INTEL_MKL_DNN_ONLY)
   if (in.dims() == 2 && perm[0] == 1 && perm[1] == 0) {
     // TODO(rmlarsen): By setting lda and ldb, we could use the MKL kernels
     // for any transpose that can be reduced to swapping the last two
@@ -227,7 +227,7 @@ Status MklConjugateTransposeCpuOp::DoTranspose(OpKernelContext* ctx,
   }
 #endif
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
   // MKL-DNN has limit on the maximum number of dimensions in a tensor.
   // Fallback to Eigen for not supported cases.
   if (in.dims() <= TENSOR_MAX_DIMS) {
diff --git a/tensorflow/core/ops/nn_ops.cc b/tensorflow/core/ops/nn_ops.cc
index f947d4c30d..e0f25fb4ef 100644
--- a/tensorflow/core/ops/nn_ops.cc
+++ b/tensorflow/core/ops/nn_ops.cc
@@ -1687,7 +1687,7 @@ NOTE Do not invoke this operator directly in Python. Graph rewrite pass is
 expected to invoke these operators.
 )doc");
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 REGISTER_OP("_MklConv2DWithBiasBackpropBias")
     .Input("out_backprop: T")
     .Input("mkl_out_backprop: uint8")
@@ -1849,7 +1849,7 @@ REGISTER_OP("_MklMaxPool")
     .Input("input: T")
     .Input("mkl_input: uint8")
     .Output("output: T")
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
     .Output("workspace: T")
 #else
     .Output("workspace: uint8")
@@ -1875,7 +1875,7 @@ REGISTER_OP("_MklMaxPoolGrad")
     .Input("orig_input: T")
     .Input("orig_output: T")
     .Input("grad: T")
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
     .Input("workspace: T")
 #else
     .Input("workspace: uint8")
@@ -1947,7 +1947,7 @@ REGISTER_OP("_MklLRN")
     .Input("input: T")
     .Input("mkl_input: uint8")
     .Output("output: T")
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
     .Output("workspace: T")
 #else
     .Output("workspace: uint8")
@@ -1975,7 +1975,7 @@ REGISTER_OP("_MklLRNGrad")
     .Input("input_grads: T")
     .Input("input_image: T")
     .Input("output_image: T")
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
     .Input("workspace: T")
 #else
     .Input("workspace: uint8")
diff --git a/tensorflow/core/util/mkl_util.h b/tensorflow/core/util/mkl_util.h
index a66b1215bd..159a787d05 100644
--- a/tensorflow/core/util/mkl_util.h
+++ b/tensorflow/core/util/mkl_util.h
@@ -22,7 +22,17 @@ limitations under the License.
 #include <utility>
 #include <vector>
 
-#ifdef INTEL_MKL_ML
+#if defined(INTEL_MKL_ML_ONLY) || defined(INTEL_MKL_DNN_ONLY)
+#ifndef INTEL_MKL
+#error "INTEL_MKL_{ML,DNN}_ONLY require INTEL_MKL"
+#endif
+#endif
+
+#if defined(INTEL_MKL_ML_ONLY) && defined(INTEL_MKL_DNN_ONLY)
+#error "at most one of INTEL_MKL_ML_ONLY and INTEL_MKL_DNN_ONLY may be defined"
+#endif
+
+#ifdef INTEL_MKL_ML_ONLY
 #include "mkl_dnn.h"
 #include "mkl_dnn_types.h"
 #include "mkl_service.h"
@@ -40,7 +50,8 @@ limitations under the License.
 #include "tensorflow/core/platform/macros.h"
 #include "tensorflow/core/util/padding.h"
 #include "tensorflow/core/util/tensor_format.h"
-#ifndef INTEL_MKL_ML
+
+#ifndef INTEL_MKL_ML_ONLY
 #include "mkldnn.hpp"
 #include "tensorflow/core/lib/core/stringpiece.h"
 
@@ -76,7 +87,7 @@ typedef enum {
   Dim_I = 1
 } MklDnnDims;
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 class MklShape {
  public:
   MklShape() {}
@@ -670,14 +681,13 @@ class MklDnnShape {
 
 // List of MklShape objects. Used in Concat/Split layers.
 
-
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 typedef std::vector<MklDnnShape> MklDnnShapeList;
 #else
 typedef std::vector<MklShape> MklShapeList;
 #endif
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 // Check if all tensors specified by MklShapes are MKL tensors.
 inline bool AreAllMklTensors(const MklShapeList& shapes) {
   for (auto& s : shapes) {
@@ -760,7 +770,7 @@ inline Tensor ConvertMklToTF(OpKernelContext* context, const Tensor& mkl_tensor,
 #endif
 
 // Get the MKL shape from the second string tensor
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 inline void GetMklShape(OpKernelContext* ctext, int n, MklShape* mklshape) {
   mklshape->DeSerializeMklShape(
       ctext->input(GetTensorMetaDataIndex(n, ctext->num_inputs()))
@@ -795,7 +805,7 @@ inline void GetMklInputList(OpKernelContext* ctext, StringPiece name,
   ctext->input_list(name, input_tensors);
 }
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
 inline void GetMklShapeList(OpKernelContext* ctext, StringPiece name,
                             MklShapeList* mkl_shapes) {
@@ -825,7 +835,7 @@ inline void GetMklShapeList(OpKernelContext* ctext, StringPiece name,
 
 #endif
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 /// Get shape of input tensor pointed by 'input_idx' in TensorShape format.
 /// If the input tensor is in MKL layout, then obtains TensorShape from
 /// MklShape.
@@ -845,7 +855,7 @@ inline TensorShape GetTfShape(OpKernelContext* context, size_t input_idx) {
 }
 #endif
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 // Allocate the second output tensor that will contain
 // the MKL shape serialized
 inline void AllocateOutputSetMklShape(OpKernelContext* ctext, int n,
@@ -878,7 +888,7 @@ inline void AllocateOutputSetMklShape(OpKernelContext* ctext, int n,
 }
 #endif
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 // Allocate the output tensor, create a second output tensor that will contain
 // the MKL shape serialized
 inline void AllocateOutputSetMklShape(OpKernelContext* ctext, int n,
@@ -923,7 +933,7 @@ inline void AllocateOutputSetMklShape(OpKernelContext* ctext, int n,
 
 // Allocates a temp tensor and returns the data buffer for temporary storage.
 // Currently
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 template <typename T>
 inline void AllocTmpBuffer(OpKernelContext* context, Tensor* tensor_out,
                            const memory::primitive_desc& pd, void** buf_out) {
@@ -972,7 +982,7 @@ inline void GetStridesFromSizes(TensorFormat data_format, size_t* strides,
   }
 }
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 inline void MklSizesToTFSizes(OpKernelContext* context,
                               TensorFormat data_format_,
                               const MklShape& mkl_shape,
@@ -1016,7 +1026,7 @@ inline int32 GetMklTensorDimIndex(char dimension) {
   }
 }
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 inline int64 GetMklTensorDim(const MklShape& mkl_shape, char dimension) {
   int index = GetMklTensorDimIndex(dimension);
   CHECK(index >= 0 && index < mkl_shape.GetDimension())
@@ -1046,7 +1056,7 @@ inline void CopyMklTensorInToOut(OpKernelContext* context, int idx_in,
   context->set_output(idx_meta_out, meta_output);
 }
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 inline void CopyTfTensorInToOutWithShape(OpKernelContext* context, int idx_in,
                                          int idx_out,
                                          const TensorShape& shape) {
@@ -1084,7 +1094,7 @@ inline void CopyTfTensorInToOutWithShape(OpKernelContext* context, int idx_in,
 }
 #endif
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 
 inline void ForwardTfTensorInToOut(OpKernelContext* context, int idx_in,
                                    int idx_out) {
@@ -1142,7 +1152,7 @@ inline void ForwardMklTensorInToOut(OpKernelContext* context, int idx_in,
   }
 }
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 // Set a dummy MKLDNN shape (called when the output is in TF format)
 inline void SetDummyMklDnnShapeOutput(OpKernelContext* context,
                                       uint32 idx_data_out) {
@@ -1186,7 +1196,7 @@ inline void ForwardMklMetaDataInToOut(OpKernelContext* context,
   }
 }
 
-#ifdef INTEL_MKL_ML
+#ifdef INTEL_MKL_ML_ONLY
 // Set a dummy MKL shape (called when the output is in TF format)
 inline void SetDummyMklShapeOutput(OpKernelContext* context,
                                    uint32 idx_data_out) {
@@ -1303,7 +1313,7 @@ inline void MklNCHWToNHWC(const Tensor& input, Tensor** output) {
 #endif
 // -------------------------------------------------------------------
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 
 /// Return MKL-DNN data type (memory::data_type) for input type T
 ///
diff --git a/tensorflow/core/util/mkl_util_test.cc b/tensorflow/core/util/mkl_util_test.cc
index cd1d0713ad..4f837f105d 100644
--- a/tensorflow/core/util/mkl_util_test.cc
+++ b/tensorflow/core/util/mkl_util_test.cc
@@ -22,7 +22,7 @@ limitations under the License.
 namespace tensorflow {
 namespace {
 
-#ifndef INTEL_MKL_ML
+#ifndef INTEL_MKL_ML_ONLY
 
 TEST(MklUtilTest, MklDnnTfShape) {
   auto cpu_engine = engine(engine::cpu, 0);
@@ -84,7 +84,7 @@ TEST(MklUtilTest, MklDnnBlockedFormatTest) {
   EXPECT_EQ(b_md2.data.format, mkldnn_blocked);
 }
 
-#endif  // INTEL_MKL_ML
+#endif  // INTEL_MKL_ML_ONLY
 }  // namespace
 }  // namespace tensorflow
 
diff --git a/tensorflow/tensorflow.bzl b/tensorflow/tensorflow.bzl
index ca9c0d0aae..30dc4313d0 100644
--- a/tensorflow/tensorflow.bzl
+++ b/tensorflow/tensorflow.bzl
@@ -230,7 +230,7 @@ def tf_copts(android_optimization_level_override="-O2", is_external=False):
       + if_cuda(["-DGOOGLE_CUDA=1"])
       + if_tensorrt(["-DGOOGLE_TENSORRT=1"])
       + if_mkl(["-DINTEL_MKL=1", "-DEIGEN_USE_VML"])
-      + if_mkl_open_source_only(["-DDO_NOT_USE_ML"])
+      + if_mkl_open_source_only(["-DINTEL_MKL_DNN_ONLY"])
       + if_mkl_lnx_x64(["-fopenmp"])
       + if_android_arm(["-mfpu=neon"])
       + if_linux_x86_64(["-msse3"])