add url of cuda9.0_cudnn7_avx_mkl library

doc/fluid/howto/inference/build_and_install_lib_cn.rst

@@ -13,6 +13,7 @@ cpu_noavx_openblas       `fluid.tgz <https://guest:@paddleci.ngrok.io/repository
 cuda7.5_cudnn5_avx_mkl   `fluid.tgz <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda75cudnn5cp27cp27mu/.lastSuccessful/fluid.tgz>`_
 cuda8.0_cudnn5_avx_mkl   `fluid.tgz <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda80cudnn5cp27cp27mu/.lastSuccessful/fluid.tgz>`_
 cuda8.0_cudnn7_avx_mkl   `fluid.tgz <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda8cudnn7cp27cp27mu/.lastSuccessful/fluid.tgz>`_
+cuda9.0_cudnn7_avx_mkl   `fluid.tgz <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda90cudnn7avxMkl/.lastSuccessful/fluid.tgz>`_
 ======================   ========================================
 
 从源码编译

paddle/fluid/operators/batch_norm_mkldnn_op.cc

@@ -21,8 +21,6 @@ namespace operators {
 
 using batch_norm_bwd = mkldnn::batch_normalization_backward;
 using batch_norm_fwd = mkldnn::batch_normalization_forward;
-using framework::DataLayout;
-using framework::Tensor;
 using mkldnn::memory;
 using mkldnn::primitive;
 using mkldnn::reorder;
@@ -31,18 +29,6 @@ using paddle::platform::MKLDNNDeviceContext;
 using paddle::platform::MKLDNNMemDesc;
 using platform::to_void_cast;
 
-template <typename T>
-using EigenArrayMap =
-    Eigen::Map<Eigen::Array<T, Eigen::Dynamic, Eigen::Dynamic>>;
-template <typename T>
-using ConstEigenArrayMap =
-    Eigen::Map<const Eigen::Array<T, Eigen::Dynamic, Eigen::Dynamic>>;
-template <typename T>
-using EigenVectorArrayMap = Eigen::Map<Eigen::Array<T, Eigen::Dynamic, 1>>;
-template <typename T>
-using ConstEigenVectorArrayMap =
-    Eigen::Map<const Eigen::Array<T, Eigen::Dynamic, 1>>;
-
 namespace {
 template <typename T>
 struct bn_type_traits {

paddle/fluid/operators/batch_norm_op.cc

@@ -22,22 +22,6 @@ limitations under the License. */
 namespace paddle {
 namespace operators {
 
-using Tensor = framework::Tensor;
-using LoDTensor = framework::LoDTensor;
-using DataLayout = framework::DataLayout;
-
-template <typename T>
-using EigenArrayMap =
-    Eigen::Map<Eigen::Array<T, Eigen::Dynamic, Eigen::Dynamic>>;
-template <typename T>
-using ConstEigenArrayMap =
-    Eigen::Map<const Eigen::Array<T, Eigen::Dynamic, Eigen::Dynamic>>;
-template <typename T>
-using EigenVectorArrayMap = Eigen::Map<Eigen::Array<T, Eigen::Dynamic, 1>>;
-template <typename T>
-using ConstEigenVectorArrayMap =
-    Eigen::Map<const Eigen::Array<T, Eigen::Dynamic, 1>>;
-
 class BatchNormOp : public framework::OperatorWithKernel {
  public:
   using framework::OperatorWithKernel::OperatorWithKernel;

paddle/fluid/operators/batch_norm_op.h

@@ -19,6 +19,22 @@ limitations under the License. */
 namespace paddle {
 namespace operators {
 
+using Tensor = framework::Tensor;
+using LoDTensor = framework::LoDTensor;
+using DataLayout = framework::DataLayout;
+
+template <typename T>
+using EigenArrayMap =
+    Eigen::Map<Eigen::Array<T, Eigen::Dynamic, Eigen::Dynamic>>;
+template <typename T>
+using ConstEigenArrayMap =
+    Eigen::Map<const Eigen::Array<T, Eigen::Dynamic, Eigen::Dynamic>>;
+template <typename T>
+using EigenVectorArrayMap = Eigen::Map<Eigen::Array<T, Eigen::Dynamic, 1>>;
+template <typename T>
+using ConstEigenVectorArrayMap =
+    Eigen::Map<const Eigen::Array<T, Eigen::Dynamic, 1>>;
+
 template <typename DeviceContext, typename T>
 class BatchNormKernel : public framework::OpKernel<T> {
  public: