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authorGravatar A. Unique TensorFlower <gardener@tensorflow.org>2018-08-10 22:34:17 -0700
committerGravatar TensorFlower Gardener <gardener@tensorflow.org>2018-08-10 22:38:34 -0700
commita8e78e2e617b6ca10f4878fe99fdf43ddedfa7c6 (patch)
treed6d7d12dc263afbd4faadc034753c498f574fc93 /tensorflow/core/kernels/mkl_tfconv_op.h
parentf97e945914e83bed8cc2d51a27f1394719f0e7b0 (diff)
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
Diffstat (limited to 'tensorflow/core/kernels/mkl_tfconv_op.h')
-rw-r--r--tensorflow/core/kernels/mkl_tfconv_op.h6
1 files changed, 3 insertions, 3 deletions
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) {