Fixing AVX performance issue

4 files changed, 45 insertions, 1 deletions

diff --git a/tensorflow/tensorflow.bzl b/tensorflow/tensorflow.bzl
index e4632c4811..3e3fbeb8f8 100644
--- a/tensorflow/tensorflow.bzl
+++ b/tensorflow/tensorflow.bzl
@@ -24,6 +24,10 @@ load(
     "if_mkl",
     "if_mkl_lnx_x64"
 )
+load(
+    "//third_party/mkl_dnn:build_defs.bzl",
+    "if_mkl_open_source_only",
+)
 
 def register_extension_info(**kwargs):
     pass
@@ -214,6 +218,7 @@ 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_lnx_x64(["-fopenmp"])
       + if_android_arm(["-mfpu=neon"])
       + if_linux_x86_64(["-msse3"])
diff --git a/third_party/mkl_dnn/BUILD b/third_party/mkl_dnn/BUILD
index 5b01f6e3e4..17a0074abe 100644
--- a/third_party/mkl_dnn/BUILD
+++ b/third_party/mkl_dnn/BUILD
@@ -1 +1,9 @@
 licenses(["notice"])
+
+config_setting(
+    name = "using_mkl_dnn_only",
+    values = {
+        "define": "using_mkl_dnn_only=true",
+    },
+    visibility = ["//visibility:public"],
+)
diff --git a/third_party/mkl_dnn/mkldnn.BUILD b/third_party/mkl_dnn/mkldnn.BUILD
index 68f24aabae..57d2e1292b 100644
--- a/third_party/mkl_dnn/mkldnn.BUILD
+++ b/third_party/mkl_dnn/mkldnn.BUILD
@@ -1,5 +1,10 @@
 exports_files(["LICENSE"])
 
+load(
+    "@org_tensorflow//third_party/mkl_dnn:build_defs.bzl",
+    "if_mkl_open_source_only",
+)
+
 config_setting(
     name = "clang_linux_x86_64",
     values = {
@@ -15,7 +20,14 @@ cc_library(
         "src/cpu/*.cpp",
     ]),
     hdrs = glob(["include/*"]),
-    copts = ["-fexceptions"] + select({
+    copts = [
+        "-fexceptions",
+        "-DUSE_MKL",
+        "-DUSE_CBLAS",
+    ] + if_mkl_open_source_only([
+        "-UUSE_MKL",
+        "-UUSE_CBLAS",
+    ]) + select({
         "@org_tensorflow//tensorflow:linux_x86_64": [
             "-fopenmp",  # only works with gcc
         ],
@@ -33,4 +45,19 @@ cc_library(
     ],
     nocopts = "-fno-exceptions",
     visibility = ["//visibility:public"],
+    deps = select({
+        "@org_tensorflow//tensorflow:linux_x86_64": [
+            "@mkl_linux//:mkl_headers",
+            "@mkl_linux//:mkl_libs_linux",
+        ],
+        "@org_tensorflow//tensorflow:darwin": [
+            "@mkl_darwin//:mkl_headers",
+            "@mkl_darwin//:mkl_libs_darwin",
+        ],
+        "@org_tensorflow//tensorflow:windows": [
+            "@mkl_windows//:mkl_headers",
+            "@mkl_windows//:mkl_libs_windows",
+        ],
+        "//conditions:default": [],
+    }),
 )
diff --git a/tools/bazel.rc b/tools/bazel.rc
index 1c1e6afb65..b3a9e6f0ef 100644
--- a/tools/bazel.rc
+++ b/tools/bazel.rc
@@ -27,6 +27,10 @@ build --define framework_shared_object=true
 build:mkl --define=using_mkl=true
 build:mkl -c opt
 
+# This config option is used to enable MKL-DNN open source library only,
+# without depending on MKL binary version.
+build:mkl_open_source_only --define=using_mkl_dnn_only=true
+
 build:download_clang --crosstool_top=@local_config_download_clang//:toolchain
 build:download_clang --define=using_clang=true