diff --git a/inference-engine/src/transformations/include/transformations/op_conversions/batch_norm_decomposition.hpp b/inference-engine/src/transformations/include/transformations/op_conversions/batch_norm_decomposition.hpp
index 7845d835cd54b9..531bacc8ded626 100644
--- a/inference-engine/src/transformations/include/transformations/op_conversions/batch_norm_decomposition.hpp
+++ b/inference-engine/src/transformations/include/transformations/op_conversions/batch_norm_decomposition.hpp
@@ -19,7 +19,6 @@ namespace ngraph {
 namespace pass {
 
 class TRANSFORMATIONS_API BatchNormDecomposition;
-class TRANSFORMATIONS_API BatchNormV5Decomposition;
 
 }  // namespace pass
 }  // namespace ngraph
@@ -29,9 +28,3 @@ class ngraph::pass::BatchNormDecomposition: public ngraph::pass::MatcherPass {
     NGRAPH_RTTI_DECLARATION;
     BatchNormDecomposition();
 };
-
-class ngraph::pass::BatchNormV5Decomposition: public ngraph::pass::MatcherPass {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    BatchNormV5Decomposition();
-};
diff --git a/inference-engine/src/transformations/src/transformations/common_optimizations/common_optimizations.cpp b/inference-engine/src/transformations/src/transformations/common_optimizations/common_optimizations.cpp
index d1a25a7f00fb27..26c084f8c16002 100644
--- a/inference-engine/src/transformations/src/transformations/common_optimizations/common_optimizations.cpp
+++ b/inference-engine/src/transformations/src/transformations/common_optimizations/common_optimizations.cpp
@@ -83,7 +83,6 @@ bool ngraph::pass::CommonOptimizations::run_on_function(std::shared_ptr<ngraph::
     auto common_fusions = manager.register_pass<ngraph::pass::GraphRewrite>();
     common_fusions->add_matcher<ngraph::pass::ConvertScatterElementsToScatter>();
     common_fusions->add_matcher<ngraph::pass::DepthToSpaceFusion>();
-    //common_fusions->add_matcher<ngraph::pass::MishFusion>();
     common_fusions->add_matcher<ngraph::pass::SoftPlusFusion>();
     common_fusions->add_matcher<ngraph::pass::SoftPlusToMishFusion>();
     common_fusions->add_matcher<ngraph::pass::SwishFusion>();
@@ -115,7 +114,6 @@ bool ngraph::pass::CommonOptimizations::run_on_function(std::shared_ptr<ngraph::
     decomp->add_matcher<ngraph::pass::ConvertDepthToSpace>();
     decomp->add_matcher<ngraph::pass::ConvertSpaceToDepth>();
     decomp->add_matcher<ngraph::pass::BatchNormDecomposition>();
-    decomp->add_matcher<ngraph::pass::BatchNormV5Decomposition>();
     decomp->set_name("ngraph::pass::CommonDecompositions");
 
     // CF is required after all decompositions
diff --git a/inference-engine/src/transformations/src/transformations/common_optimizations/conv_bias_fusion.cpp b/inference-engine/src/transformations/src/transformations/common_optimizations/conv_bias_fusion.cpp
index e4225bdcb15367..f6f05dc08b1bca 100644
--- a/inference-engine/src/transformations/src/transformations/common_optimizations/conv_bias_fusion.cpp
+++ b/inference-engine/src/transformations/src/transformations/common_optimizations/conv_bias_fusion.cpp
@@ -164,7 +164,7 @@ NGRAPH_RTTI_DEFINITION(ngraph::pass::ConvAddFusion, "ConvAddFusion", 0);
 ngraph::pass::ConvAddFusion::ConvAddFusion() {
     MATCHER_SCOPE(ConvAddFusion);
     auto conv = ngraph::pattern::wrap_type<op::ConvolutionIE>(pattern::consumers_count(1));
-    auto add = ngraph::pattern::wrap_type<opset1::Add>({conv, std::make_shared<pattern::op::Label>()});
+    auto add = ngraph::pattern::wrap_type<opset1::Add>({conv, pattern::any_input()});
 
     matcher_pass_callback callback = [](ngraph::pattern::Matcher &m) {
         return conv_callback<op::ConvolutionIE>(m);
@@ -179,7 +179,7 @@ NGRAPH_RTTI_DEFINITION(ngraph::pass::ConvMultiplyFusion, "ConvMultiplyFusion", 0
 ngraph::pass::ConvMultiplyFusion::ConvMultiplyFusion() {
     MATCHER_SCOPE(ConvMultiplyFusion);
     auto conv = ngraph::pattern::wrap_type<op::ConvolutionIE>(pattern::consumers_count(1));
-    auto add = ngraph::pattern::wrap_type<opset1::Multiply>({conv, std::make_shared<pattern::op::Label>()});
+    auto add = ngraph::pattern::wrap_type<opset1::Multiply>({conv, pattern::any_input()});
 
     matcher_pass_callback callback = [](ngraph::pattern::Matcher &m) {
         return conv_callback<op::ConvolutionIE>(m);
@@ -194,7 +194,7 @@ NGRAPH_RTTI_DEFINITION(ngraph::pass::DeconvAddFusion, "DeconvAddFusion", 0);
 ngraph::pass::DeconvAddFusion::DeconvAddFusion() {
     MATCHER_SCOPE(DeconvAddFusion);
     auto conv = ngraph::pattern::wrap_type<op::DeconvolutionIE>(pattern::consumers_count(1));
-    auto add = ngraph::pattern::wrap_type<opset1::Add>({conv, std::make_shared<pattern::op::Label>()});
+    auto add = ngraph::pattern::wrap_type<opset1::Add>({conv, pattern::any_input()});
 
     matcher_pass_callback callback = [](ngraph::pattern::Matcher &m){
         return conv_callback<op::DeconvolutionIE>(m);
diff --git a/inference-engine/src/transformations/src/transformations/op_conversions/batch_norm_decomposition.cpp b/inference-engine/src/transformations/src/transformations/op_conversions/batch_norm_decomposition.cpp
index 8907487b8b66a9..a7efe7960b948b 100644
--- a/inference-engine/src/transformations/src/transformations/op_conversions/batch_norm_decomposition.cpp
+++ b/inference-engine/src/transformations/src/transformations/op_conversions/batch_norm_decomposition.cpp
@@ -19,7 +19,7 @@ NGRAPH_RTTI_DEFINITION(ngraph::pass::BatchNormDecomposition, "BatchNormDecomposi
 
 ngraph::pass::BatchNormDecomposition::BatchNormDecomposition() {
     MATCHER_SCOPE(BatchNormDecomposition);
-    auto bn = pattern::wrap_type<opset1::BatchNormInference>({
+    auto bn = pattern::wrap_type<opset1::BatchNormInference, opset5::BatchNormInference>({
         pattern::any_input(pattern::has_static_rank()),
         pattern::any_input(pattern::has_static_shape()),
         pattern::any_input(pattern::has_static_shape()),
@@ -28,20 +28,30 @@ ngraph::pass::BatchNormDecomposition::BatchNormDecomposition() {
     });
 
     ngraph::matcher_pass_callback callback = [this](ngraph::pattern::Matcher &m) {
-        auto m_bn = dynamic_pointer_cast<opset1::BatchNormInference>(m.get_match_root());
-        if (!m_bn) {
+        auto m_bn = m.get_match_root();
+        Output<Node> m_input, m_gamma, m_beta, m_mean, m_var;
+        double eps;
+        if (auto m_bn_v1 = dynamic_pointer_cast<opset1::BatchNormInference>(m_bn)) {
+            m_gamma = m_bn_v1->input_value(0);
+            m_beta = m_bn_v1->input_value(1);
+            m_input = m_bn_v1->input_value(2);
+            m_mean = m_bn_v1->input_value(3);
+            m_var = m_bn_v1->input_value(4);
+            eps = m_bn_v1->get_eps_value();
+        } else if (auto m_bn_v5 = dynamic_pointer_cast<opset5::BatchNormInference>(m_bn)) {
+            m_input = m_bn_v5->input_value(0);
+            m_gamma = m_bn_v5->input_value(1);
+            m_beta = m_bn_v5->input_value(2);
+            m_mean = m_bn_v5->input_value(3);
+            m_var = m_bn_v5->input_value(4);
+            eps = m_bn_v5->get_eps_value();
+        } else {
             return false;
         }
 
-        auto m_gamma = m_bn->input_value(0);
-        auto m_beta = m_bn->input_value(1);
-        auto m_input = m_bn->input_value(2);
-        auto m_mean = m_bn->input_value(3);
-        auto m_var = m_bn->input_value(4);
-
         const auto& input_type = m_input.get_element_type();
         // scale_add = variance + eps
-        auto scale_add = make_shared<opset5::Add>(m_var, opset5::Constant::create(input_type, Shape{}, {m_bn->get_eps_value()}));
+        auto scale_add = make_shared<opset5::Add>(m_var, opset5::Constant::create(input_type, Shape{}, {eps}));
         // scale = sqrt(variance + eps)
         auto scale = make_shared<opset5::Sqrt>(scale_add);
         // Divide `gamma` by `sqrt(variance + eps)`
@@ -79,67 +89,3 @@ ngraph::pass::BatchNormDecomposition::BatchNormDecomposition() {
     this->register_matcher(m, callback);
 }
 
-NGRAPH_RTTI_DEFINITION(ngraph::pass::BatchNormV5Decomposition, "BatchNormDecomposition", 5);
-
-// TODO: this pass will be unified with BatchNormDecomposition pass
-ngraph::pass::BatchNormV5Decomposition::BatchNormV5Decomposition() {
-    MATCHER_SCOPE(BatchNormV5Decomposition);
-    auto bn = pattern::wrap_type<opset5::BatchNormInference>({
-        pattern::any_input(pattern::has_static_rank()),
-        pattern::any_input(pattern::has_static_shape()),
-        pattern::any_input(pattern::has_static_shape()),
-        pattern::any_input(pattern::has_static_shape()),
-        pattern::any_input(pattern::has_static_shape())
-    });
-
-    ngraph::matcher_pass_callback callback = [this](ngraph::pattern::Matcher &m) {
-        auto m_bn = dynamic_pointer_cast<opset5::BatchNormInference>(m.get_match_root());
-        if (!m_bn) {
-            return false;
-        }
-
-        auto m_input = m_bn->input_value(0);
-        auto m_gamma = m_bn->input_value(1);
-        auto m_beta = m_bn->input_value(2);
-        auto m_mean = m_bn->input_value(3);
-        auto m_var = m_bn->input_value(4);
-
-        const auto& input_type = m_input.get_element_type();
-        // scale_add = variance + eps
-        auto scale_add = make_shared<opset5::Add>(m_var, opset5::Constant::create(input_type, Shape{}, {m_bn->get_eps_value()}));
-        // scale = sqrt(variance + eps)
-        auto scale = make_shared<opset5::Sqrt>(scale_add);
-        // Divide `gamma` by `sqrt(variance + eps)`
-        auto gamma_div_scale = std::make_shared<opset5::Divide>(m_gamma, scale);
-
-        int64_t dims_to_add = m_input.get_partial_shape().rank().get_length() - 2;
-
-        // TODO: instead of getting full shape we can concatenate sequence of ones with ShapeOf
-        Shape input_aligned_shape = m_gamma.get_shape();
-        for (int64_t i = 0; i < dims_to_add; ++i)
-            input_aligned_shape.push_back(1);
-        auto new_shape = opset5::Constant::create(element::i64, Shape{input_aligned_shape.size()}, input_aligned_shape);
-
-        auto gamma_div_scale_aligned = make_shared<opset5::Reshape>(gamma_div_scale, new_shape, true);
-        auto beta_aligned = make_shared<opset5::Reshape>(m_beta, new_shape, true);
-        auto mean_aligned = make_shared<opset5::Reshape>(m_mean, new_shape, true);
-
-        // input_sub_mean = input - mean
-        auto input_sub_mean = register_new_node<opset5::Subtract>(m_input, mean_aligned);
-        // Multiply  `input - mean` and `gamma / sqrt(variance + eps)`
-        auto mul = std::make_shared<opset5::Multiply>(input_sub_mean, gamma_div_scale_aligned);
-        // Add `(input - mean) * gamma / sqrt(variance + eps)` and `beta`
-        auto add = std::make_shared<opset5::Add>(mul, beta_aligned);
-
-        add->set_friendly_name(m_bn->get_friendly_name());
-
-        copy_runtime_info(m_bn, {scale_add, scale, gamma_div_scale, gamma_div_scale_aligned,
-            beta_aligned, input_sub_mean, mul, add});
-
-        replace_node(m_bn, add);
-
-        return true;
-    };
-    auto m = std::make_shared<ngraph::pattern::Matcher>(bn, matcher_name);
-    this->register_matcher(m, callback);
-}
diff --git a/inference-engine/src/transformations/src/transformations/op_conversions/convert_gelu.cpp b/inference-engine/src/transformations/src/transformations/op_conversions/convert_gelu.cpp
index 2ee04f4f654c36..a3c683d1537a9d 100644
--- a/inference-engine/src/transformations/src/transformations/op_conversions/convert_gelu.cpp
+++ b/inference-engine/src/transformations/src/transformations/op_conversions/convert_gelu.cpp
@@ -10,13 +10,13 @@
 
 #include <ngraph/ngraph.hpp>
 #include <ngraph/rt_info.hpp>
+#include <ngraph/pattern/op/wrap_type.hpp>
 
 NGRAPH_RTTI_DEFINITION(ngraph::pass::ConvertGELU, "ConvertGELU", 0);
 
 ngraph::pass::ConvertGELU::ConvertGELU() {
     MATCHER_SCOPE(ConvertGELU);
-    auto input = std::make_shared<pattern::op::Label>(element::f32, Shape{});
-    auto gelu = std::make_shared<ngraph::opset2::Gelu>(input);
+    auto gelu = pattern::wrap_type<ngraph::opset2::Gelu>();
 
     ngraph::matcher_pass_callback callback = [this](pattern::Matcher& m) {
         auto gelu = std::dynamic_pointer_cast<ngraph::opset2::Gelu>(m.get_match_root());
diff --git a/inference-engine/src/transformations/src/transformations/op_conversions/convert_shuffle_channels3.cpp b/inference-engine/src/transformations/src/transformations/op_conversions/convert_shuffle_channels3.cpp
index 4b4d9f901fd661..ec80a640a5dae1 100644
--- a/inference-engine/src/transformations/src/transformations/op_conversions/convert_shuffle_channels3.cpp
+++ b/inference-engine/src/transformations/src/transformations/op_conversions/convert_shuffle_channels3.cpp
@@ -11,6 +11,7 @@
 #include <ngraph/opsets/opset2.hpp>
 #include <ngraph/opsets/opset3.hpp>
 #include <ngraph/rt_info.hpp>
+#include <ngraph/pattern/op/wrap_type.hpp>
 
 using namespace ngraph;
 
@@ -18,8 +19,7 @@ NGRAPH_RTTI_DEFINITION(ngraph::pass::ConvertShuffleChannels3, "ConvertShuffleCha
 
 ngraph::pass::ConvertShuffleChannels3::ConvertShuffleChannels3() {
     MATCHER_SCOPE(ConvertShuffleChannels3);
-    auto input = std::make_shared<pattern::op::Label>(element::f32, Shape{1, 1, 1, 1});
-    auto shuffle_channels = std::make_shared<::opset3::ShuffleChannels>(input);
+    auto shuffle_channels = pattern::wrap_type<opset3::ShuffleChannels>();
 
     ngraph::matcher_pass_callback callback = [this](pattern::Matcher &m) {
         auto shuffle_channels = std::dynamic_pointer_cast<::opset3::ShuffleChannels>(m.get_match_root());
diff --git a/inference-engine/src/transformations/src/transformations/op_conversions/convert_ti_to_sequences.cpp b/inference-engine/src/transformations/src/transformations/op_conversions/convert_ti_to_sequences.cpp
index 4a1d8b8b28e4bb..2a9c72b59cb990 100644
--- a/inference-engine/src/transformations/src/transformations/op_conversions/convert_ti_to_sequences.cpp
+++ b/inference-engine/src/transformations/src/transformations/op_conversions/convert_ti_to_sequences.cpp
@@ -24,8 +24,8 @@ NGRAPH_RTTI_DEFINITION(ngraph::pass::ConvertTensorIteratorToGRUSequence, "Conver
 
 ngraph::pass::ConvertTensorIteratorToLSTMSequence::ConvertTensorIteratorToLSTMSequence() {
     MATCHER_SCOPE(ConvertTensorIteratorToLSTMSequence);
-    auto tensor_iterator = std::make_shared<ngraph::pattern::op::Label>(ngraph::element::f32,
-                                                                        ngraph::Shape{}, ngraph::pattern::has_class<ngraph::opset5::TensorIterator>());
+    auto tensor_iterator = pattern::wrap_type<ngraph::opset5::TensorIterator>();
+
     ngraph::matcher_pass_callback callback = [this](pattern::Matcher &m) {
         auto ti = std::dynamic_pointer_cast<ngraph::opset5::TensorIterator>(m.get_match_root());
         if (!ti || transformation_callback(ti))
@@ -201,8 +201,8 @@ ngraph::pass::ConvertTensorIteratorToLSTMSequence::ConvertTensorIteratorToLSTMSe
 
 ngraph::pass::ConvertTensorIteratorToRNNSequence::ConvertTensorIteratorToRNNSequence() {
     MATCHER_SCOPE(ConvertTensorIteratorToRNNSequence);
-    auto tensor_iterator = std::make_shared<ngraph::pattern::op::Label>(ngraph::element::f32,
-                                                                        ngraph::Shape{}, ngraph::pattern::has_class<ngraph::opset5::TensorIterator>());
+    auto tensor_iterator = pattern::wrap_type<ngraph::opset5::TensorIterator>();
+
     ngraph::matcher_pass_callback callback = [this](pattern::Matcher &m) {
         auto ti = std::dynamic_pointer_cast<ngraph::opset5::TensorIterator>(m.get_match_root());
         if (!ti || transformation_callback(ti))
@@ -357,8 +357,8 @@ ngraph::pass::ConvertTensorIteratorToRNNSequence::ConvertTensorIteratorToRNNSequ
 
 ngraph::pass::ConvertTensorIteratorToGRUSequence::ConvertTensorIteratorToGRUSequence() {
     MATCHER_SCOPE(ConvertTensorIteratorToGRUSequence);
-    auto tensor_iterator = std::make_shared<ngraph::pattern::op::Label>(ngraph::element::f32,
-                                                                        ngraph::Shape{}, ngraph::pattern::has_class<ngraph::opset5::TensorIterator>());
+    auto tensor_iterator = pattern::wrap_type<ngraph::opset5::TensorIterator>();
+
     ngraph::matcher_pass_callback callback = [this](pattern::Matcher &m) {
         auto ti = std::dynamic_pointer_cast<ngraph::opset5::TensorIterator>(m.get_match_root());
         if (!ti || transformation_callback(ti))
diff --git a/inference-engine/src/transformations/src/transformations/op_conversions/lstm_cell_decomposition.cpp b/inference-engine/src/transformations/src/transformations/op_conversions/lstm_cell_decomposition.cpp
index 1f30d6662cf3a9..28e7d2c429d333 100644
--- a/inference-engine/src/transformations/src/transformations/op_conversions/lstm_cell_decomposition.cpp
+++ b/inference-engine/src/transformations/src/transformations/op_conversions/lstm_cell_decomposition.cpp
@@ -18,10 +18,8 @@ NGRAPH_RTTI_DEFINITION(ngraph::pass::LSTMCellDecomposition, "LSTMCellDecompositi
 
 ngraph::pass::LSTMCellDecomposition::LSTMCellDecomposition() {
     MATCHER_SCOPE(LSTMCellDecomposition);
-    auto is_supported_lstm_cell = [](const std::shared_ptr<Node>& n) {
-        return pattern::has_class<ngraph::opset1::LSTMCell>()(n) || pattern::has_class<ngraph::opset4::LSTMCell>()(n);
-    };
-    auto any_lstm = std::make_shared<pattern::op::Label>(element::f32, Shape{}, is_supported_lstm_cell);
+    auto any_lstm = pattern::wrap_type<opset1::LSTMCell, opset4::LSTMCell>();
+
     ngraph::matcher_pass_callback callback = [this](ngraph::pattern::Matcher& m) {
         auto lstm_cell = std::dynamic_pointer_cast<ngraph::op::util::RNNCellBase>(m.get_match_root());
         if (!lstm_cell || transformation_callback(lstm_cell)) {
diff --git a/ngraph/core/include/ngraph/pattern/op/wrap_type.hpp b/ngraph/core/include/ngraph/pattern/op/wrap_type.hpp
index 3c95c7e4300ce3..77307b7ee670c4 100644
--- a/ngraph/core/include/ngraph/pattern/op/wrap_type.hpp
+++ b/ngraph/core/include/ngraph/pattern/op/wrap_type.hpp
@@ -36,7 +36,17 @@ namespace ngraph
                                       [](const Output<Node>& output) { return true; },
                                   const OutputVector& input_values = {})
                     : Pattern(input_values, pred)
-                    , m_wrapped_type(wrapped_type)
+                    , m_wrapped_types({wrapped_type})
+                {
+                    set_output_type(0, element::Type_t::dynamic, PartialShape::dynamic());
+                }
+
+                explicit WrapType(std::vector<NodeTypeInfo> wrapped_types,
+                                  const ValuePredicate& pred =
+                                      [](const Output<Node>& output) { return true; },
+                                  const OutputVector& input_values = {})
+                    : Pattern(input_values, pred)
+                    , m_wrapped_types(std::move(wrapped_types))
                 {
                     set_output_type(0, element::Type_t::dynamic, PartialShape::dynamic());
                 }
@@ -45,30 +55,33 @@ namespace ngraph
                                  const Output<Node>& pattern_value,
                                  const Output<Node>& graph_value) override;
 
-                NodeTypeInfo get_wrapped_type() const { return m_wrapped_type; }
+                NodeTypeInfo get_wrapped_type() const;
+
+                const std::vector<NodeTypeInfo>& get_wrapped_types() const;
+
             private:
-                NodeTypeInfo m_wrapped_type;
+                std::vector<NodeTypeInfo> m_wrapped_types;
             };
         }
 
-        template <class T>
+        template <class... Args>
         std::shared_ptr<Node> wrap_type(const OutputVector& inputs,
                                         const pattern::op::ValuePredicate& pred)
         {
-            static_assert(std::is_base_of<Node, T>::value, "Unexpected template type");
-            return std::make_shared<op::WrapType>(T::type_info, pred, inputs);
+            std::vector<DiscreteTypeInfo> info{Args::type_info...};
+            return std::make_shared<op::WrapType>(info, pred, inputs);
         }
 
-        template <class T>
+        template <class... Args>
         std::shared_ptr<Node> wrap_type(const OutputVector& inputs = {})
         {
-            return wrap_type<T>(inputs, [](const Output<Node>& output) { return true; });
+            return wrap_type<Args...>(inputs, [](const Output<Node>& output) { return true; });
         }
 
-        template <class T>
+        template <class... Args>
         std::shared_ptr<Node> wrap_type(const pattern::op::ValuePredicate& pred)
         {
-            return wrap_type<T>({}, pred);
+            return wrap_type<Args...>({}, pred);
         }
     }
 }
diff --git a/ngraph/core/src/pass/graph_rewrite.cpp b/ngraph/core/src/pass/graph_rewrite.cpp
index d1980024e47060..85a9189241b33f 100644
--- a/ngraph/core/src/pass/graph_rewrite.cpp
+++ b/ngraph/core/src/pass/graph_rewrite.cpp
@@ -109,12 +109,14 @@ bool pass::GraphRewrite::run_on_function(shared_ptr<Function> f)
         // it's type
         // and use it in unordered_map as key for fast MatcherPass search. Otherwise type is unknown
         // and default algorithm is used.
-        NodeTypeInfo root_type_info = root->get_type_info();
         if (auto p = dynamic_pointer_cast<pattern::op::Pattern>(root))
         {
             if (auto any_type = dynamic_pointer_cast<pattern::op::WrapType>(p))
             {
-                root_type_info = any_type->get_wrapped_type();
+                for (const auto& root_type_info : any_type->get_wrapped_types())
+                {
+                    type_to_matcher[root_type_info].push_back(matcher_index);
+                }
             }
             else
             {
@@ -122,7 +124,10 @@ bool pass::GraphRewrite::run_on_function(shared_ptr<Function> f)
                 break;
             }
         }
-        type_to_matcher[root_type_info].push_back(matcher_index);
+        else
+        {
+            type_to_matcher[root->get_type_info()].push_back(matcher_index);
+        }
 
         // TODO: traverse parents for root_type_info in order to register complete list of matchers
         // including ones triggered by parent type info.
diff --git a/ngraph/core/src/pattern/op/wrap_type.cpp b/ngraph/core/src/pattern/op/wrap_type.cpp
index 74ca1b61bdc5e1..b76403c032950f 100644
--- a/ngraph/core/src/pattern/op/wrap_type.cpp
+++ b/ngraph/core/src/pattern/op/wrap_type.cpp
@@ -31,7 +31,12 @@ bool pattern::op::WrapType::match_value(Matcher* matcher,
                                         const Output<Node>& pattern_value,
                                         const Output<Node>& graph_value)
 {
-    if (graph_value.get_node_shared_ptr()->get_type_info().is_castable(get_wrapped_type()) &&
+    if (std::any_of(m_wrapped_types.begin(),
+                    m_wrapped_types.end(),
+                    [&](const NodeTypeInfo& type_info) {
+                        return graph_value.get_node_shared_ptr()->get_type_info().is_castable(
+                            type_info);
+                    }) &&
         m_predicate(graph_value))
     {
         auto& pattern_map = matcher->get_pattern_value_map();
@@ -44,3 +49,17 @@ bool pattern::op::WrapType::match_value(Matcher* matcher,
     }
     return false;
 }
+
+NodeTypeInfo pattern::op::WrapType::get_wrapped_type() const
+{
+    if (m_wrapped_types.size() > 1)
+    {
+        throw ngraph::ngraph_error("get_wrapped_type() called on WrapType with more than one type");
+    }
+    return m_wrapped_types.at(0);
+}
+
+const std::vector<NodeTypeInfo>& pattern::op::WrapType::get_wrapped_types() const
+{
+    return m_wrapped_types;
+}
\ No newline at end of file
diff --git a/ngraph/test/pattern.cpp b/ngraph/test/pattern.cpp
index 5d3772069a7ea3..733078815274a8 100644
--- a/ngraph/test/pattern.cpp
+++ b/ngraph/test/pattern.cpp
@@ -810,7 +810,7 @@ TEST(pattern, is_contained_match)
     ASSERT_FALSE(n.is_contained_match());
 }
 
-TEST(pattern, wrap_type)
+TEST(pattern, wrap_type_single_op)
 {
     auto a = make_shared<op::Parameter>(element::f32, Shape{1, 3, 64, 64});
     auto b = make_shared<op::Abs>(a);
@@ -852,3 +852,47 @@ TEST(pattern, wrap_type)
         ASSERT_TRUE(matcher->match(static_pointer_cast<Node>(mul2)));
     }
 }
+
+TEST(pattern, wrap_type_multi_op)
+{
+    auto a = make_shared<op::Parameter>(element::f32, Shape{1, 3, 64, 64});
+    auto b = make_shared<op::Abs>(a);
+    auto c = make_shared<op::Relu>(a);
+    auto mul = make_shared<op::v1::Multiply>(a, op::Constant::create(element::f32, Shape{}, {1}));
+    auto add = make_shared<op::v1::Add>(op::Constant::create(element::f32, Shape{}, {1}), a);
+
+    {
+        auto m = pattern::wrap_type<op::v1::Multiply, op::v1::Add>();
+        auto matcher = std::make_shared<pattern::Matcher>(m, "MulAddMatcher");
+        ASSERT_TRUE(matcher->match(mul->output(0)));
+        ASSERT_EQ(matcher->get_matched_nodes().size(), 1);
+        ASSERT_EQ(matcher->get_matched_nodes()[0], mul);
+        ASSERT_EQ(matcher->get_pattern_map().count(m), 1);
+
+        ASSERT_TRUE(matcher->match(add->output(0)));
+        ASSERT_EQ(matcher->get_matched_nodes().size(), 1);
+        ASSERT_EQ(matcher->get_matched_nodes()[0], add);
+        ASSERT_EQ(matcher->get_pattern_map().count(m), 1);
+
+        ASSERT_FALSE(matcher->match(static_pointer_cast<Node>(a)));
+        ASSERT_FALSE(matcher->match(static_pointer_cast<Node>(b)));
+        ASSERT_FALSE(matcher->match(static_pointer_cast<Node>(c)));
+    }
+    {
+        auto m = pattern::wrap_type<op::util::BinaryElementwiseArithmetic>();
+        auto matcher = std::make_shared<pattern::Matcher>(m, "ElementwiseMatcher");
+        ASSERT_TRUE(matcher->match(mul->output(0)));
+        ASSERT_EQ(matcher->get_matched_nodes().size(), 1);
+        ASSERT_EQ(matcher->get_matched_nodes()[0], mul);
+        ASSERT_EQ(matcher->get_pattern_map().count(m), 1);
+
+        ASSERT_TRUE(matcher->match(add->output(0)));
+        ASSERT_EQ(matcher->get_matched_nodes().size(), 1);
+        ASSERT_EQ(matcher->get_matched_nodes()[0], add);
+        ASSERT_EQ(matcher->get_pattern_map().count(m), 1);
+
+        ASSERT_FALSE(matcher->match(static_pointer_cast<Node>(a)));
+        ASSERT_FALSE(matcher->match(static_pointer_cast<Node>(b)));
+        ASSERT_FALSE(matcher->match(static_pointer_cast<Node>(c)));
+    }
+}