Transformers don't need to export symbols.

src/ngraph/runtime/cpu/op/batch_mat_mul_transpose.hpp

@@ -17,7 +17,6 @@
 #pragma once
 
 #include "ngraph/op/op.hpp"
-#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
 
 namespace ngraph
 {
@@ -35,7 +34,6 @@ namespace ngraph
         class BatchMatMulTranspose : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             /// \brief Constructs a batch of matmul product operation.

src/ngraph/runtime/cpu/op/batch_norm_relu.hpp

@@ -30,7 +30,6 @@ namespace ngraph
         class BatchNormTrainingRelu : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             CPU_BACKEND_API BatchNormTrainingRelu(double eps,
@@ -60,7 +59,6 @@ namespace ngraph
         class BatchNormInferenceRelu : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             BatchNormInferenceRelu(double eps,

src/ngraph/runtime/cpu/op/bounded_relu.hpp

@@ -19,7 +19,6 @@
 #include "ngraph/node.hpp"
 #include "ngraph/op/op.hpp"
 #include "ngraph/op/util/unary_elementwise_arithmetic.hpp"
-#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
 
 namespace ngraph
 {
@@ -30,7 +29,6 @@ namespace ngraph
         class BoundedRelu : public ngraph::op::util::UnaryElementwiseArithmetic
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             /// \brief Constructs a BoundedRelu operation.

src/ngraph/runtime/cpu/op/conv_add.hpp

@@ -18,7 +18,6 @@
 
 #include "ngraph/op/convolution.hpp"
 #include "ngraph/op/op.hpp"
-#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
 
 namespace ngraph
 {
@@ -27,7 +26,6 @@ namespace ngraph
         class ConvolutionAdd : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             ConvolutionAdd(const std::shared_ptr<op::Convolution>& conv,

src/ngraph/runtime/cpu/op/conv_relu.hpp

@@ -28,7 +28,6 @@ namespace ngraph
         class ConvolutionRelu : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             CPU_BACKEND_API ConvolutionRelu(const std::shared_ptr<op::Convolution>& conv);

src/ngraph/runtime/cpu/op/convert_layout.hpp

@@ -35,7 +35,6 @@ namespace ngraph
                 class ConvertLayout : public ngraph::op::Op
                 {
                 public:
-                    CPU_BACKEND_API
                     static const std::string type_name;
                     const std::string& description() const override { return type_name; }
                     CPU_BACKEND_API ConvertLayout(

src/ngraph/runtime/cpu/op/deconv.hpp

@@ -18,7 +18,6 @@
 
 #include "ngraph/op/convolution.hpp"
 #include "ngraph/op/op.hpp"
-#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
 
 namespace ngraph
 {
@@ -28,7 +27,6 @@ namespace ngraph
         class DeconvolutionBias : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             /// \brief Constructs a batched-convolution data batch-backprop operation.

src/ngraph/runtime/cpu/op/dropout.hpp

@@ -17,7 +17,6 @@
 #pragma once
 
 #include "ngraph/op/op.hpp"
-#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
 #include "ngraph/util.hpp"
 
 namespace ngraph
@@ -27,7 +26,6 @@ namespace ngraph
         class Dropout : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             Dropout(const Output<Node>& input,

src/ngraph/runtime/cpu/op/group_conv_bias.hpp

@@ -17,7 +17,6 @@
 #pragma once
 #include "ngraph/op/fused/group_conv.hpp"
 #include "ngraph/op/op.hpp"
-#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
 
 namespace ngraph
 {
@@ -28,7 +27,6 @@ namespace ngraph
         class GroupConvolutionBias : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             GroupConvolutionBias(const std::shared_ptr<op::GroupConvolution>& conv,

src/ngraph/runtime/cpu/op/halide_op.hpp

@@ -20,7 +20,6 @@
 #include <vector>
 
 #include "ngraph/op/op.hpp"
-#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
 
 namespace ngraph
 {
@@ -33,7 +32,6 @@ namespace ngraph
                 class HalideOp : public ngraph::op::Op
                 {
                 public:
-                    CPU_BACKEND_API
                     static const std::string type_name;
                     const std::string& description() const override { return type_name; }
                     HalideOp(const OutputVector& args,

src/ngraph/runtime/cpu/op/leaky_relu.hpp

@@ -19,7 +19,6 @@
 #include "ngraph/node.hpp"
 #include "ngraph/op/op.hpp"
 #include "ngraph/op/util/unary_elementwise_arithmetic.hpp"
-#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
 
 namespace ngraph
 {
@@ -31,7 +30,6 @@ namespace ngraph
         class CPULeakyRelu : public ngraph::op::util::UnaryElementwiseArithmetic
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             /// \brief Constructs a CPULeakyRelu operation.

src/ngraph/runtime/cpu/op/lstm.hpp

@@ -17,7 +17,6 @@
 #pragma once
 
 #include "ngraph/op/op.hpp"
-#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
 #include "ngraph/runtime/cpu/op/rnn_utils.hpp"
 #include "ngraph/util.hpp"
 
@@ -28,7 +27,6 @@ namespace ngraph
         class Lstm : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             // INPUTS:

src/ngraph/runtime/cpu/op/matmul_bias.hpp

@@ -27,7 +27,6 @@ namespace ngraph
         class MatmulBias : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             CPU_BACKEND_API MatmulBias(const Output<Node>& W,

src/ngraph/runtime/cpu/op/max_pool_with_indices.hpp

@@ -32,7 +32,6 @@ namespace ngraph
         class MaxPoolWithIndices : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             CPU_BACKEND_API MaxPoolWithIndices(const Output<Node>& arg,
@@ -68,7 +67,6 @@ namespace ngraph
         class MaxPoolWithIndicesBackprop : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             CPU_BACKEND_API MaxPoolWithIndicesBackprop(const Output<Node>& arg_forward,

src/ngraph/runtime/cpu/op/quantized_matmul.hpp

@@ -19,7 +19,6 @@
 #include <utility>
 
 #include "ngraph/op/op.hpp"
-#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
 
 namespace ngraph
 {
@@ -28,7 +27,6 @@ namespace ngraph
         class QuantizedMatmul : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             QuantizedMatmul(const Output<Node>& data,

src/ngraph/runtime/cpu/op/rnn.hpp

@@ -48,7 +48,6 @@ namespace ngraph
         class Rnn : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             CPU_BACKEND_API Rnn(const Output<Node>& src_layer,

src/ngraph/runtime/cpu/op/sigmoid_mul.hpp

@@ -30,7 +30,6 @@ namespace ngraph
         class SigmoidMultiply : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             /// Defines valid function types
@@ -69,7 +68,6 @@ namespace ngraph
         class SigmoidMultiplyBackprop : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             typedef SigmoidMultiply::FunctionType FunctionType;

src/ngraph/runtime/cpu/op/update_slice.hpp

@@ -18,7 +18,6 @@
 
 #include "ngraph/coordinate.hpp"
 #include "ngraph/op/op.hpp"
-#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
 #include "ngraph/strides.hpp"
 
 namespace ngraph
@@ -51,7 +50,6 @@ namespace ngraph
         class UpdateSlice : public Op
         {
         public:
-            CPU_BACKEND_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             /// \brief Constructs a tensor slice update operation.

src/ngraph/runtime/plaidml/plaidml_ops_convolution.hpp

@@ -39,7 +39,6 @@ namespace ngraph
 class ngraph::runtime::plaidml::op::Convolution final : public ngraph::op::Op
 {
 public:
-    NGRAPH_API
     static const std::string type_name;
     const std::string& description() const override { return type_name; }
     Convolution(std::shared_ptr<ngraph::op::Convolution> src,
@@ -66,7 +65,6 @@ private:
 class ngraph::runtime::plaidml::op::ConvolutionBackpropData final : public ngraph::op::Op
 {
 public:
-    NGRAPH_API
     static const std::string type_name;
     const std::string& description() const override { return type_name; }
     ConvolutionBackpropData(std::shared_ptr<ngraph::op::ConvolutionBackpropData> src,
@@ -93,7 +91,6 @@ private:
 class ngraph::runtime::plaidml::op::ConvolutionBackpropFilters final : public ngraph::op::Op
 {
 public:
-    NGRAPH_API
     static const std::string type_name;
     const std::string& description() const override { return type_name; }
     ConvolutionBackpropFilters(std::shared_ptr<ngraph::op::ConvolutionBackpropFilters> src,

src/ngraph/runtime/plaidml/plaidml_ops_implicit_broadcast.hpp

@@ -40,7 +40,6 @@ namespace ngraph
 class ngraph::runtime::plaidml::op::ImplicitBroadcast final : public ngraph::op::Op
 {
 public:
-    NGRAPH_API
     static const std::string type_name;
     const std::string& description() const override { return type_name; }
     ImplicitBroadcast(const Output<Node>& input, const Shape& shape);

src/ngraph/runtime/plaidml/plaidml_ops_replicate.hpp

@@ -39,7 +39,6 @@ namespace ngraph
 class ngraph::runtime::plaidml::op::Replicate final : public ngraph::op::Op
 {
 public:
-    NGRAPH_API
     static const std::string type_name;
     const std::string& description() const override { return type_name; }
     Replicate(const Output<Node>& arg, std::size_t replication_axis, std::size_t replication_count);

src/ngraph/runtime/plaidml/plaidml_ops_winograd.hpp

@@ -38,7 +38,6 @@ namespace ngraph
 class ngraph::runtime::plaidml::op::Winograd final : public ngraph::op::Op
 {
 public:
-    NGRAPH_API
     static const std::string type_name;
     const std::string& description() const override { return type_name; }
     Winograd(std::shared_ptr<Convolution> conv, const OutputVector& args);