Making MKL-DNN default build choice (#16474)

tensorflow · Jan 26, 2018 · e4a628a · e4a628a
1 parent 6a75a52
commit e4a628a
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Showing 23 changed files with 96 additions and 84 deletions.
diff --git a/tensorflow/core/graph/mkl_layout_pass.cc b/tensorflow/core/graph/mkl_layout_pass.cc
@@ -42,7 +42,7 @@ limitations under the License.
 
 namespace tensorflow {
 
-#ifndef INTEL_MKL_DNN
+#ifdef INTEL_MKL_ML
 
 // This pass implements rewriting of graph to support following scenarios:
 // (A) Merging nodes in the graph
@@ -2215,7 +2215,7 @@ Status MklLayoutRewritePass::Run(
   return Status::OK();
 }
 
-#else  // INTEL_MKL_DNN
+#else  // INTEL_MKL_ML
 
 // This pass implements rewriting of graph to support following scenarios:
 // (A) Merging nodes in the graph
@@ -4325,7 +4325,7 @@ Status MklLayoutRewritePass::Run(
 
   return Status::OK();
 }
-#endif  // INTEL_MKL_DNN
+#endif  // INTEL_MKL_ML
 }  // namespace tensorflow
 
 #endif
diff --git a/tensorflow/core/graph/mkl_layout_pass_test.cc b/tensorflow/core/graph/mkl_layout_pass_test.cc
@@ -38,7 +38,7 @@ limitations under the License.
 
 namespace tensorflow {
 
-#ifndef INTEL_MKL_DNN
+#ifdef INTEL_MKL_ML
 
 namespace {
 
@@ -1885,7 +1885,7 @@ BENCHMARK(BM_MklLayoutRewritePass)->Arg(1000)->Arg(10000);
 
 }  // namespace
 
-#else  // INTEL_MKL_DNN
+#else  // INTEL_MKL_ML
 
 namespace {
 
@@ -3503,7 +3503,7 @@ BENCHMARK(BM_MklLayoutRewritePass)->Arg(1000)->Arg(10000);
 
 }  // namespace
 
-#endif  // INTEL_MKL_DNN
+#endif  // INTEL_MKL_ML
 
 }  // namespace tensorflow
 

diff --git a/tensorflow/core/kernels/mkl_aggregate_ops.cc b/tensorflow/core/kernels/mkl_aggregate_ops.cc
@@ -28,7 +28,7 @@ limitations under the License.
 #include "mkl_dnn_types.h"
 #include "tensorflow/core/util/mkl_util.h"
 
-#ifdef INTEL_MKL_DNN
+#ifndef INTEL_MKL_ML
 #include "mkldnn.hpp"
 using mkldnn::stream;
 using mkldnn::sum;
@@ -37,7 +37,7 @@ using mkldnn::sum;
 namespace tensorflow {
 typedef Eigen::ThreadPoolDevice CPUDevice;
 
-#ifndef INTEL_MKL_DNN
+#ifdef INTEL_MKL_ML
 
 template <typename Device, typename T>
 class MklAddNOp : public OpKernel {
@@ -285,7 +285,7 @@ class MklAddNOp : public OpKernel {
   } MklAddNOpContext;
 };
 
-#else  // INTEL_MKL_DNN
+#else  // INTEL_MKL_ML
 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
@@ -24,7 +24,7 @@
 
 #include "tensorflow/core/kernels/mkl_pooling_ops_common.h"
 
-#ifdef INTEL_MKL_DNN
+#ifndef INTEL_MKL_ML
 #include "mkldnn.hpp"
 using mkldnn::algorithm;
 using mkldnn::engine;
@@ -40,8 +40,7 @@ namespace tensorflow {
 
 typedef Eigen::ThreadPoolDevice CPUDevice;
 
-// For now, MKL-ML is default. So making MKL-DNN not a default choice.
-#ifndef INTEL_MKL_DNN
+#ifdef INTEL_MKL_ML
 
 template <typename Device, typename T>
 class MklAvgPoolingOp : public OpKernel {
@@ -429,7 +428,10 @@ class MklAvgPoolingGradOp : public OpKernel {
   TensorFormat data_format_;
 };  // MklAvgPoolingGradOp
 
-#else  // INTEL_MKL_DNN is defined
+
+
+#else
+
 
 template <typename Device, typename T>
 class MklAvgPoolingOp : public MklPoolingForwardOpBase<T> {
@@ -678,7 +680,11 @@ class MklAvgPoolingGradOp : public MklPoolingBackwardOpBase<T> {
   }
 };  // MklAvgPoolingGradOp
 
-#endif  // INTEL_MKL_DNN
+
+
+
+#endif  // INTEL_MKL_ML
+
 
 REGISTER_KERNEL_BUILDER(Name("_MklAvgPool")
                             .Device(DEVICE_CPU)

diff --git a/tensorflow/core/kernels/mkl_concat_op.cc b/tensorflow/core/kernels/mkl_concat_op.cc
@@ -30,7 +30,7 @@ limitations under the License.
 #include "mkl_dnn_types.h"
 #include "tensorflow/core/util/mkl_util.h"
 
-#ifdef INTEL_MKL_DNN
+#ifndef INTEL_MKL_ML
 #include "mkldnn.hpp"
 
 using mkldnn::concat;
@@ -62,7 +62,7 @@ class EigenConcatBaseOp : public OpKernel {
   // we need to have empty Compute because Compute is pure virtual function.
   void Compute(OpKernelContext* c) {}
 
-#ifndef INTEL_MKL_DNN
+#ifdef INTEL_MKL_ML
 
   void Compute(OpKernelContext* c, const std::vector<Tensor>& values) {
     const Tensor* concat_dim_tensor;
@@ -230,7 +230,7 @@ class EigenConcatBaseOp : public OpKernel {
 #endif
 };
 
-#ifndef INTEL_MKL_DNN
+#ifdef INTEL_MKL_ML
 
 // --------------------------------------------------------------------------
 //                      Mkl Concat Op

diff --git a/tensorflow/core/kernels/mkl_conv_grad_filter_ops.cc b/tensorflow/core/kernels/mkl_conv_grad_filter_ops.cc
@@ -42,7 +42,7 @@ limitations under the License.
 #include "mkl_dnn_types.h"
 #include "tensorflow/core/util/mkl_util.h"
 
-#ifdef INTEL_MKL_DNN
+#ifndef INTEL_MKL_ML
 #include "mkldnn.hpp"
 
 using mkldnn::convolution_backward_weights;
@@ -55,7 +55,7 @@ namespace tensorflow {
 
 typedef Eigen::ThreadPoolDevice CPUDevice;
 
-#ifndef INTEL_MKL_DNN
+#ifdef INTEL_MKL_ML
 
 template <typename Device, class T>
 class MklConv2DCustomBackpropFilterOp : public OpKernel {
@@ -655,7 +655,7 @@ class MklConv2DCustomBackpropFilterOp
 TF_CALL_float(REGISTER_MKL_FILTER_KERNELS);
 #undef REGISTER_MKL_FILTER_KERNELS
 
-#endif  // INTEL_MKL_DNN
+#endif  // INTEL_MKL_ML
 
 }  // namespace tensorflow
 

diff --git a/tensorflow/core/kernels/mkl_conv_grad_input_ops.cc b/tensorflow/core/kernels/mkl_conv_grad_input_ops.cc
@@ -44,7 +44,7 @@ limitations under the License.
 #include "tensorflow/core/util/use_cudnn.h"
 #include "tensorflow/core/util/work_sharder.h"
 
-#ifdef INTEL_MKL_DNN
+#ifndef INTEL_MKL_ML
 #include "mkldnn.hpp"
 
 using mkldnn::convolution_backward_data;
@@ -56,7 +56,7 @@ namespace tensorflow {
 
 typedef Eigen::ThreadPoolDevice CPUDevice;
 
-#ifndef INTEL_MKL_DNN
+#ifdef INTEL_MKL_ML
 
 template <typename Device, class T>
 class MklConv2DCustomBackpropInputOp : public OpKernel {
@@ -493,7 +493,7 @@ class MklConv2DCustomBackpropInputOp
   }
 };
 
-#endif  // INTEL_MKL_DNN
+#endif  // INTEL_MKL_ML
 
 #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
@@ -41,7 +41,10 @@ limitations under the License.
 
 #include "tensorflow/core/util/mkl_util.h"
 
-#ifdef INTEL_MKL_DNN
+
+
+#ifndef INTEL_MKL_ML
+
 #include "mkldnn.hpp"
 
 using mkldnn::prop_kind;
@@ -58,8 +61,8 @@ namespace tensorflow {
 
 typedef Eigen::ThreadPoolDevice CPUDevice;
 
-// For now, MKL-ML is default. So making MKL-DNN not a default choice.
-#ifndef INTEL_MKL_DNN
+// MKL-DNN is now default. MKL-ML must be specified explicitly.
+#ifdef INTEL_MKL_ML
 
 template <typename Device, typename T, bool biasEnabled>
 class MklConv2DOp : public OpKernel {

diff --git 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"
 
-#ifdef INTEL_MKL_DNN
+#ifndef INTEL_MKL_ML
 #include "mkldnn.hpp"
 
 using mkldnn::prop_kind;
@@ -52,7 +52,7 @@ using mkldnn::convolution_forward;
 
 namespace tensorflow {
 
-#ifdef INTEL_MKL_DNN
+#ifndef INTEL_MKL_ML
 
 class MklDnnConvUtil {
  protected:
@@ -553,7 +553,7 @@ class MklConv2DBackpropCommonOp : public OpKernel {
   Padding padding_;
   TensorFormat data_format_;
 };
-#endif  // INTEL_MKL_DNN
+#endif  // INTEL_MKL_ML
 
 /////////////////////////////////////////////////////////////////////
 ///  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
@@ -25,7 +25,7 @@ limitations under the License.
 #include "mkl_dnn_types.h"
 #include "tensorflow/core/util/mkl_util.h"
 
-#ifdef INTEL_MKL_DNN
+#ifndef INTEL_MKL_ML
 #include "mkldnn.hpp"
 
 using mkldnn::batch_normalization_backward;
@@ -41,7 +41,7 @@ using mkldnn::use_scale_shift;
 namespace tensorflow {
 using CPUDevice = Eigen::ThreadPoolDevice;
 
-#ifndef INTEL_MKL_DNN
+#ifdef INTEL_MKL_ML
 
 template <typename Device, typename T>
 class MklFusedBatchNormOp : public OpKernel {
@@ -683,7 +683,7 @@ class MklFusedBatchNormGradOp : public OpKernel {
 };
 #endif
 
-#ifdef INTEL_MKL_DNN
+#ifndef INTEL_MKL_ML
 
 template <typename Device, typename T>
 class MklFusedBatchNormOp : public OpKernel {

diff --git a/tensorflow/core/kernels/mkl_identity_op.cc b/tensorflow/core/kernels/mkl_identity_op.cc
@@ -28,14 +28,14 @@ limitations under the License.
 #include "mkl_dnn_types.h"
 #include "tensorflow/core/util/mkl_util.h"
 
-#ifdef INTEL_MKL_DNN
+#ifndef INTEL_MKL_ML
 #include "mkldnn.hpp"
 #endif
 
 namespace tensorflow {
 typedef Eigen::ThreadPoolDevice CPUDevice;
 
-#ifndef INTEL_MKL_DNN
+#ifdef INTEL_MKL_ML
 
 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
@@ -31,7 +31,7 @@ limitations under the License.
 #include "tensorflow/core/kernels/mkl_tfconv_op.h"
 #include "tensorflow/core/util/mkl_util.h"
 
-#ifdef INTEL_MKL_DNN
+#ifndef INTEL_MKL_ML
 #include "mkldnn.hpp"
 
 using mkldnn::stream;
@@ -59,7 +59,7 @@ typedef Eigen::ThreadPoolDevice CPUDevice;
 //     convert the TF format input to MKL format
 ///////////////////////////////////////////////////////////
 
-#ifndef INTEL_MKL_DNN
+#ifdef INTEL_MKL_ML
 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
@@ -38,7 +38,7 @@ limitations under the License.
 #include "tensorflow/core/util/work_sharder.h"
 #endif
 
-#ifdef INTEL_MKL_DNN
+#ifndef INTEL_MKL_ML
 #include "mkldnn.hpp"
 using mkldnn::lrn_across_channels;
 using mkldnn::lrn_backward;
@@ -67,7 +67,7 @@ void GetBandMatrix(int depth, int depth_radius,
 
 }  // namespace
 
-#ifndef INTEL_MKL_DNN
+#ifdef INTEL_MKL_ML
 
 template <typename T>
 class MklLRNOp : public OpKernel {
@@ -1343,7 +1343,7 @@ class MklLRNGradOp : public OpKernel {
   float beta_;
 };
 
-#endif  // INTEL_MKL_DNN
+#endif  // INTEL_MKL_ML
 
 #define REGISTER_MKL_LRN_CPU(T)                                     \
   REGISTER_KERNEL_BUILDER(Name("_MklLRN")                           \

diff --git 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"
 
-#ifdef INTEL_MKL_DNN
+#ifndef INTEL_MKL_ML
 #include <algorithm>
 #include "mkldnn.hpp"
 using mkldnn::algorithm;
@@ -39,8 +39,8 @@ namespace tensorflow {
 
 typedef Eigen::ThreadPoolDevice CPUDevice;
 
-// For now, MKL-ML is default. So making MKL-DNN not a default choice.
-#ifndef INTEL_MKL_DNN
+// MKL-DNN is now default. MKL-ML must be specified explicitly.
+#ifdef INTEL_MKL_ML
 
 // An implementation of MaxPooling (forward).
 template <typename Device, typename T>
@@ -494,7 +494,7 @@ class MklMaxPoolingGradOp : public OpKernel {
   bool workspace_enabled_;
 };  // MklMaxPoolingGradOp
 
-#else  // INTEL_MKL_DNN is defined
+#else
 
 // An implementation of MaxPooling (forward).
 template <typename Device, typename T>
@@ -793,7 +793,7 @@ class MklMaxPoolingGradOp : public MklPoolingBackwardOpBase<T> {
   }
 };  // MklMaxPoolingGradOp
 
-#endif  // INTEL_MKL_DNN
+#endif  // INTEL_MKL_ML
 
 REGISTER_KERNEL_BUILDER(Name("_MklMaxPool")
                             .Device(DEVICE_CPU)