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

2 files changed, 31 insertions, 21 deletions

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