Merge branch 'master' into cloudhan_fix-mkldnn_v1

src/ngraph/attribute_adapter.cpp

@@ -242,4 +242,40 @@ namespace ngraph
         m_value = copy_from<vector<uint64_t>>(value);
         m_buffer_valid = false;
     }
+
+    constexpr DiscreteTypeInfo AttributeAdapter<vector<float>>::type_info;
+
+    const vector<float>& AttributeAdapter<vector<float>>::get()
+    {
+        if (!m_buffer_valid)
+        {
+            m_buffer = copy_from<vector<float>>(m_value);
+            m_buffer_valid = true;
+        }
+        return m_buffer;
+    }
+
+    void AttributeAdapter<vector<float>>::set(const vector<float>& value)
+    {
+        m_value = copy_from<vector<float>>(value);
+        m_buffer_valid = false;
+    }
+
+    constexpr DiscreteTypeInfo AttributeAdapter<vector<string>>::type_info;
+
+    const vector<string>& AttributeAdapter<vector<string>>::get()
+    {
+        if (!m_buffer_valid)
+        {
+            m_buffer = copy_from<vector<string>>(m_value);
+            m_buffer_valid = true;
+        }
+        return m_buffer;
+    }
+
+    void AttributeAdapter<vector<string>>::set(const vector<string>& value)
+    {
+        m_value = copy_from<vector<string>>(value);
+        m_buffer_valid = false;
+    }
 }

src/ngraph/attribute_adapter.hpp

@@ -16,6 +16,7 @@
 
 #pragma once
 
+#include <string>
 #include <type_traits>
 #include <vector>
 
@@ -299,6 +300,39 @@ namespace ngraph
         void set(const std::vector<int64_t>& value) override;
     };
 
+    template <>
+    class NGRAPH_API AttributeAdapter<std::vector<float>>
+        : public ValueReference<std::vector<float>>, public ValueAccessor<std::vector<float>>
+    {
+    public:
+        AttributeAdapter(std::vector<float>& value)
+            : ValueReference<std::vector<float>>(value)
+        {
+        }
+
+        static constexpr DiscreteTypeInfo type_info{"AttributeAdapter<vector<float>>", 0};
+        const DiscreteTypeInfo& get_type_info() const override { return type_info; }
+        const std::vector<float>& get() override;
+        void set(const std::vector<float>& value) override;
+    };
+
+    template <>
+    class NGRAPH_API AttributeAdapter<std::vector<std::string>>
+        : public ValueReference<std::vector<std::string>>,
+          public ValueAccessor<std::vector<std::string>>
+    {
+    public:
+        AttributeAdapter(std::vector<std::string>& value)
+            : ValueReference<std::vector<std::string>>(value)
+        {
+        }
+
+        static constexpr DiscreteTypeInfo type_info{"AttributeAdapter<vector<string>>", 0};
+        const DiscreteTypeInfo& get_type_info() const override { return type_info; }
+        const std::vector<std::string>& get() override;
+        void set(const std::vector<std::string>& value) override;
+    };
+
     template <typename A, typename B>
     A copy_from(B& b)
     {

src/ngraph/attribute_visitor.hpp

@@ -46,16 +46,25 @@ namespace ngraph
         {
             on_adapter(name, static_cast<ValueAccessor<void>&>(adapter));
         };
+        virtual void on_adapter(const std::string& name, ValueAccessor<int64_t>& adapter)
+        {
+            on_adapter(name, static_cast<ValueAccessor<void>&>(adapter));
+        }
+        virtual void on_adapter(const std::string& name, ValueAccessor<double>& adapter)
+        {
+            on_adapter(name, static_cast<ValueAccessor<void>&>(adapter));
+        }
         virtual void on_adapter(const std::string& name,
                                 ValueAccessor<std::vector<int64_t>>& adapter)
         {
             on_adapter(name, static_cast<ValueAccessor<void>&>(adapter));
         }
-        virtual void on_adapter(const std::string& name, ValueAccessor<int64_t>& adapter)
+        virtual void on_adapter(const std::string& name, ValueAccessor<std::vector<float>>& adapter)
         {
             on_adapter(name, static_cast<ValueAccessor<void>&>(adapter));
         }
-        virtual void on_adapter(const std::string& name, ValueAccessor<double>& adapter)
+        virtual void on_adapter(const std::string& name,
+                                ValueAccessor<std::vector<std::string>>& adapter)
         {
             on_adapter(name, static_cast<ValueAccessor<void>&>(adapter));
         }
@@ -68,5 +77,11 @@ namespace ngraph
             AttributeAdapter<T> adapter(value);
             on_adapter(name, adapter);
         }
+
+        void on_attribute(const std::string& name, op::AutoBroadcastSpec& value)
+        {
+            AttributeAdapter<op::AutoBroadcastType> adapter(value.m_type);
+            on_adapter(name, adapter);
+        }
     };
 }

src/ngraph/coordinate_diff.cpp

@@ -80,7 +80,7 @@ const vector<int64_t>& AttributeAdapter<CoordinateDiff>::get()
 
 void AttributeAdapter<CoordinateDiff>::set(const vector<int64_t>& value)
 {
-    m_value = copy_from<CoordinateDiff>(m_value);
+    m_value = copy_from<CoordinateDiff>(value);
     m_buffer_valid = false;
 }
 

src/ngraph/op/erf.cpp

@@ -23,6 +23,11 @@ using namespace ngraph;
 
 constexpr NodeTypeInfo op::Erf::type_info;
 
+bool ngraph::op::v0::Erf::visit_attributes(AttributeVisitor& visitor)
+{
+    return true;
+}
+
 shared_ptr<Node> op::Erf::copy_with_new_args(const NodeVector& new_args) const
 {
     check_new_args_count(this, new_args);

src/ngraph/op/erf.hpp

@@ -32,6 +32,7 @@ namespace ngraph
                 Erf() = default;
                 Erf(const Output<Node>& arg);
 
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 virtual std::shared_ptr<Node>
                     copy_with_new_args(const NodeVector& new_args) const override;
             };

src/ngraph/op/exp.cpp

@@ -28,6 +28,11 @@ op::Exp::Exp(const Output<Node>& arg)
     constructor_validate_and_infer_types();
 }
 
+bool ngraph::op::v0::Exp::visit_attributes(AttributeVisitor& visitor)
+{
+    return true;
+}
+
 shared_ptr<Node> op::Exp::copy_with_new_args(const NodeVector& new_args) const
 {
     check_new_args_count(this, new_args);

src/ngraph/op/exp.hpp

@@ -37,6 +37,7 @@ namespace ngraph
                 /// \param arg Node that produces the input tensor.
                 Exp(const Output<Node>& arg);
 
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 virtual std::shared_ptr<Node>
                     copy_with_new_args(const NodeVector& new_args) const override;
 

src/ngraph/op/floor.cpp

@@ -27,6 +27,11 @@ op::Floor::Floor(const Output<Node>& arg)
     constructor_validate_and_infer_types();
 }
 
+bool ngraph::op::v0::Floor::visit_attributes(AttributeVisitor& visitor)
+{
+    return true;
+}
+
 shared_ptr<Node> op::Floor::copy_with_new_args(const NodeVector& new_args) const
 {
     check_new_args_count(this, new_args);

src/ngraph/op/floor.hpp

@@ -37,6 +37,7 @@ namespace ngraph
                 /// \param arg Node that produces the input tensor.
                 Floor(const Output<Node>& arg);
 
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 virtual std::shared_ptr<Node>
                     copy_with_new_args(const NodeVector& new_args) const override;
             };

src/ngraph/op/fused/elu.cpp

@@ -15,6 +15,7 @@
 //*****************************************************************************
 #include "ngraph/op/fused/elu.hpp"
 
+#include "ngraph/attribute_visitor.hpp"
 #include "ngraph/builder/autobroadcast.hpp"
 #include "ngraph/builder/make_constant.hpp"
 #include "ngraph/op/add.hpp"
@@ -37,6 +38,12 @@ op::Elu::Elu(const Output<Node>& data, const double alpha)
     constructor_validate_and_infer_types();
 }
 
+bool ngraph::op::v0::Elu::visit_attributes(AttributeVisitor& visitor)
+{
+    visitor.on_attribute("alpha", m_alpha);
+    return true;
+}
+
 NodeVector op::Elu::decompose_op() const
 {
     auto data = input_value(0);

src/ngraph/op/fused/elu.hpp

@@ -42,6 +42,7 @@ namespace ngraph
                 /// \param alpha Multiplier for negative values
                 Elu(const Output<Node>& data, const double alpha);
 
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 virtual NodeVector decompose_op() const override;
 
                 virtual std::shared_ptr<Node>

src/ngraph/op/fused/fake_quantize.cpp

@@ -17,6 +17,7 @@
 #include <memory>
 
 #include "fake_quantize.hpp"
+#include "ngraph/attribute_visitor.hpp"
 #include "ngraph/builder/autobroadcast.hpp"
 #include "ngraph/op/add.hpp"
 #include "ngraph/op/constant.hpp"
@@ -80,6 +81,13 @@ void op::FakeQuantize::validate_and_infer_types()
     set_output_type(0, get_input_element_type(0), get_input_partial_shape(0));
 }
 
+bool ngraph::op::v0::FakeQuantize::visit_attributes(AttributeVisitor& visitor)
+{
+    visitor.on_attribute("levels", m_levels);
+    visitor.on_attribute("auto_broadcast", m_auto_broadcast);
+    return true;
+}
+
 NodeVector op::FakeQuantize::decompose_op() const
 {
     Output<Node> data{input_value(0)};

src/ngraph/op/fused/fake_quantize.hpp

@@ -67,6 +67,7 @@ namespace ngraph
                              const AutoBroadcastSpec& auto_broadcast =
                                  AutoBroadcastSpec(AutoBroadcastType::NUMPY));
 
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 virtual NodeVector decompose_op() const override;
                 virtual void validate_and_infer_types() override;
 

src/ngraph/op/fused/grn.cpp

@@ -17,6 +17,7 @@
 #include <iterator>
 
 #include "grn.hpp"
+#include "ngraph/attribute_visitor.hpp"
 #include "ngraph/axis_set.hpp"
 #include "ngraph/builder/norm.hpp"
 #include "ngraph/builder/reshape.hpp"
@@ -36,6 +37,12 @@ op::GRN::GRN(const Output<Node>& data, float bias)
     constructor_validate_and_infer_types();
 }
 
+bool ngraph::op::v0::GRN::visit_attributes(AttributeVisitor& visitor)
+{
+    visitor.on_attribute("bias", m_bias);
+    return true;
+}
+
 void op::GRN::pre_validate_and_infer_types()
 {
     const auto& data_pshape = get_input_partial_shape(0);

src/ngraph/op/fused/grn.hpp

@@ -42,6 +42,7 @@ namespace ngraph
                 ///
                 GRN(const Output<Node>& data, float bias);
 
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 float get_bias() const { return m_bias; }
                 virtual void pre_validate_and_infer_types() override;
                 virtual NodeVector decompose_op() const override;

src/ngraph/op/fused/group_conv.cpp

@@ -18,6 +18,7 @@
 
 #include "group_conv.hpp"
 
+#include "ngraph/attribute_visitor.hpp"
 #include "ngraph/builder/reshape.hpp"
 #include "ngraph/builder/split.hpp"
 #include "ngraph/op/concat.hpp"
@@ -57,6 +58,16 @@ op::v1::GroupConvolution::GroupConvolution(const Output<Node>& data_batch,
     constructor_validate_and_infer_types();
 }
 
+bool ngraph::op::v1::GroupConvolution::visit_attributes(AttributeVisitor& visitor)
+{
+    visitor.on_attribute("strides", m_strides);
+    visitor.on_attribute("pads_begin", m_pads_begin);
+    visitor.on_attribute("pads_end", m_pads_end);
+    visitor.on_attribute("dilations", m_dilations);
+    visitor.on_attribute("auto_pad", m_auto_pad);
+    return true;
+}
+
 void op::v1::GroupConvolution::validate_and_infer_types()
 {
     const PartialShape& data_batch_pshape = get_input_partial_shape(0);
@@ -219,6 +230,17 @@ op::v1::GroupConvolutionBackpropData::GroupConvolutionBackpropData(
     constructor_validate_and_infer_types();
 }
 
+bool ngraph::op::v1::GroupConvolutionBackpropData::visit_attributes(AttributeVisitor& visitor)
+{
+    visitor.on_attribute("strides", m_strides);
+    visitor.on_attribute("pads_begin", m_pads_begin);
+    visitor.on_attribute("pads_end", m_pads_end);
+    visitor.on_attribute("dilations", m_dilations);
+    visitor.on_attribute("auto_pad", m_auto_pad);
+    visitor.on_attribute("output_padding", m_output_padding);
+    return true;
+}
+
 bool op::v1::GroupConvolutionBackpropData::is_dynamic() const
 {
     bool is_dynamic = Node::is_dynamic();

src/ngraph/op/fused/group_conv.hpp

@@ -61,6 +61,8 @@ namespace ngraph
                                  const CoordinateDiff& pads_end,
                                  const Strides& dilations,
                                  const PadType& auto_pad = PadType::EXPLICIT);
+
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 // TODO - Remove supports_decompose and validate_and_infer_type once op supports
                 // decomposition
                 bool supports_decompose() const override { return false; }
@@ -187,6 +189,7 @@ namespace ngraph
                                              const PadType& auto_pad = PadType::EXPLICIT,
                                              const CoordinateDiff& output_padding = {});
 
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 virtual bool is_dynamic() const override;
                 virtual NodeVector decompose_op() const override;
                 virtual void pre_validate_and_infer_types() override;

src/ngraph/op/fused/hard_sigmoid.cpp

@@ -37,6 +37,11 @@ op::HardSigmoid::HardSigmoid(const Output<Node>& data,
     constructor_validate_and_infer_types();
 }
 
+bool ngraph::op::v0::HardSigmoid::visit_attributes(AttributeVisitor& visitor)
+{
+    return true;
+}
+
 void op::HardSigmoid::pre_validate_and_infer_types()
 {
     const auto& alpha_pshape = get_input_partial_shape(1);

src/ngraph/op/fused/hard_sigmoid.hpp

@@ -46,6 +46,7 @@ namespace ngraph
                             const Output<Node>& alpha,
                             const Output<Node>& beta);
 
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 virtual void pre_validate_and_infer_types() override;
                 virtual NodeVector decompose_op() const override;
                 virtual std::shared_ptr<Node>

src/ngraph/op/fused/lstm_cell.cpp

@@ -17,6 +17,7 @@
 #include <cmath>
 #include <functional>
 
+#include "ngraph/attribute_visitor.hpp"
 #include "ngraph/builder/reshape.hpp"
 #include "ngraph/builder/split.hpp"
 #include "ngraph/op/add.hpp"
@@ -107,6 +108,19 @@ op::LSTMCell::LSTMCell(const Output<Node>& X,
     constructor_validate_and_infer_types();
 }
 
+bool ngraph::op::v0::LSTMCell::visit_attributes(AttributeVisitor& visitor)
+{
+    visitor.on_attribute("hidden_size", m_hidden_size);
+    visitor.on_attribute("activations", m_activations);
+    visitor.on_attribute("activations_alpha", m_activations_alpha);
+    visitor.on_attribute("activations_beta", m_activations_beta);
+    visitor.on_attribute("clip", m_clip);
+
+    visitor.on_attribute("input_forget", m_input_forget);
+    visitor.on_attribute("weights_format", m_weights_format);
+    return true;
+}
+
 void op::LSTMCell::pre_validate_and_infer_types()
 {
     set_output_size(2);
@@ -386,3 +400,26 @@ shared_ptr<Node> op::LSTMCell::copy_with_new_args(const NodeVector& new_args) co
         throw ngraph_error("Incorrect number of new arguments");
     }
 }
+
+namespace ngraph
+{
+    template <>
+    EnumNames<op::LSTMWeightsFormat>& EnumNames<op::LSTMWeightsFormat>::get()
+    {
+        static auto enum_names =
+            EnumNames<op::LSTMWeightsFormat>("op::LSTMWeightsFormat",
+                                             {{"fico", op::LSTMWeightsFormat::FICO},
+                                              {"icof", op::LSTMWeightsFormat::ICOF},
+                                              {"ifco", op::LSTMWeightsFormat::IFCO},
+                                              {"ifoc", op::LSTMWeightsFormat::IFOC},
+                                              {"iofc", op::LSTMWeightsFormat::IOFC}});
+        return enum_names;
+    }
+
+    constexpr DiscreteTypeInfo AttributeAdapter<op::LSTMWeightsFormat>::type_info;
+
+    std::ostream& operator<<(std::ostream& s, const op::LSTMWeightsFormat& type)
+    {
+        return s << as_string(type);
+    }
+} // namespace ngraph

src/ngraph/op/fused/lstm_cell.hpp

@@ -224,6 +224,7 @@ namespace ngraph
                          float clip = 0.f,
                          bool input_forget = false);
 
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 virtual void pre_validate_and_infer_types() override;
                 virtual NodeVector decompose_op() const override;
                 virtual std::shared_ptr<Node>
@@ -284,4 +285,20 @@ namespace ngraph
         }
         using v0::LSTMCell;
     } // namespace op
+
+    std::ostream& operator<<(std::ostream& s, const op::LSTMWeightsFormat& type);
+
+    template <>
+    class NGRAPH_API AttributeAdapter<op::LSTMWeightsFormat>
+        : public EnumAttributeAdapterBase<op::LSTMWeightsFormat>
+    {
+    public:
+        AttributeAdapter(op::LSTMWeightsFormat& value)
+            : EnumAttributeAdapterBase<op::LSTMWeightsFormat>(value)
+        {
+        }
+
+        static constexpr DiscreteTypeInfo type_info{"AttributeAdapter<op::LSTMWeightsFormat>", 1};
+        const DiscreteTypeInfo& get_type_info() const override { return type_info; }
+    };
 } // namespace ngraph

src/ngraph/op/fused/lstm_sequence.cpp

@@ -16,6 +16,7 @@
 
 #include "ngraph/op/fused/lstm_sequence.hpp"
 
+#include "ngraph/attribute_visitor.hpp"
 #include "ngraph/builder/autobroadcast.hpp"
 #include "ngraph/builder/reshape.hpp"
 #include "ngraph/builder/split.hpp"
@@ -32,6 +33,19 @@ using namespace ngraph;
 using namespace std;
 
 constexpr NodeTypeInfo op::LSTMSequence::type_info;
+bool ngraph::op::v0::LSTMSequence::visit_attributes(AttributeVisitor& visitor)
+{
+    visitor.on_attribute("hidden_size", m_hidden_size);
+    visitor.on_attribute("activations", m_activations);
+    visitor.on_attribute("activations_alpha", m_activations_alpha);
+    visitor.on_attribute("activations_beta", m_activations_beta);
+    visitor.on_attribute("clip", m_clip_threshold);
+    visitor.on_attribute("direction", m_direction);
+
+    visitor.on_attribute("input_forget", m_input_forget);
+    visitor.on_attribute("weights_format", m_weights_format);
+    return true;
+}
 NodeVector op::LSTMSequence::decompose_op() const
 {
     NodeVector results;
@@ -247,3 +261,24 @@ shared_ptr<Node> op::LSTMSequence::prepare_input(Output<Node> node, bool is_reve
     // Since we have forward LSTM we can squeeze `num_directions` axis from inputs.
     return builder::squeeze(tmp);
 }
+
+namespace ngraph
+{
+    template <>
+    EnumNames<op::v0::LSTMSequence::direction>& EnumNames<op::v0::LSTMSequence::direction>::get()
+    {
+        static auto enum_names = EnumNames<op::v0::LSTMSequence::direction>(
+            "op::v0::LSTMSequence::direction",
+            {{"forward", op::v0::LSTMSequence::direction::FORWARD},
+             {"reverse", op::v0::LSTMSequence::direction::REVERSE},
+             {"bidirectional", op::v0::LSTMSequence::direction::BIDIRECTIONAL}});
+        return enum_names;
+    }
+
+    constexpr DiscreteTypeInfo AttributeAdapter<op::v0::LSTMSequence::direction>::type_info;
+
+    std::ostream& operator<<(std::ostream& s, const op::v0::LSTMSequence::direction& type)
+    {
+        return s << as_string(type);
+    }
+} // namespace ngraph

src/ngraph/op/fused/lstm_sequence.hpp

@@ -135,6 +135,7 @@ namespace ngraph
                 {
                 }
 
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 virtual NodeVector decompose_op() const override;
 
                 virtual std::shared_ptr<Node>
@@ -185,4 +186,21 @@ namespace ngraph
         }
         using v0::LSTMSequence;
     } // namespace op
+
+    std::ostream& operator<<(std::ostream& s, const op::v0::LSTMSequence::direction& type);
+
+    template <>
+    class NGRAPH_API AttributeAdapter<op::v0::LSTMSequence::direction>
+        : public EnumAttributeAdapterBase<op::v0::LSTMSequence::direction>
+    {
+    public:
+        AttributeAdapter(op::v0::LSTMSequence::direction& value)
+            : EnumAttributeAdapterBase<op::v0::LSTMSequence::direction>(value)
+        {
+        }
+
+        static constexpr DiscreteTypeInfo type_info{
+            "AttributeAdapter<op::v0::LSTMSequence::direction>", 1};
+        const DiscreteTypeInfo& get_type_info() const override { return type_info; }
+    };
 } // namespace ngraph

src/ngraph/op/gather.cpp

@@ -112,6 +112,11 @@ op::v1::Gather::Gather(const Output<Node>& params,
     constructor_validate_and_infer_types();
 }
 
+bool ngraph::op::v1::Gather::visit_attributes(AttributeVisitor& visitor)
+{
+    return true;
+}
+
 void op::v1::Gather::validate_and_infer_types()
 {
     const auto& input_rank = get_input_partial_shape(PARAMS).rank();

src/ngraph/op/gather.hpp

@@ -67,6 +67,7 @@ namespace ngraph
                        const Output<Node>& indices,
                        const Output<Node>& axis);
 
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 int64_t get_axis() const;
 
                 void validate_and_infer_types() override;

src/ngraph/op/gather_tree.cpp

@@ -38,6 +38,11 @@ shared_ptr<Node> op::v1::GatherTree::copy_with_new_args(const NodeVector& new_ar
         new_args.at(0), new_args.at(1), new_args.at(2), new_args.at(3));
 }
 
+bool ngraph::op::v1::GatherTree::visit_attributes(AttributeVisitor& visitor)
+{
+    return true;
+}
+
 void op::v1::GatherTree::validate_and_infer_types()
 {
     const auto& step_ids_rank = get_input_partial_shape(0);

src/ngraph/op/gather_tree.hpp

@@ -44,6 +44,7 @@ namespace ngraph
                            const Output<Node>& max_seq_len,
                            const Output<Node>& end_token);
 
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 void validate_and_infer_types() override;
 
                 virtual std::shared_ptr<Node>

src/ngraph/op/log.cpp

@@ -28,6 +28,11 @@ op::Log::Log(const Output<Node>& arg)
     constructor_validate_and_infer_types();
 }
 
+bool ngraph::op::v0::Log::visit_attributes(AttributeVisitor& visitor)
+{
+    return true;
+}
+
 shared_ptr<Node> op::Log::copy_with_new_args(const NodeVector& new_args) const
 {
     check_new_args_count(this, new_args);

src/ngraph/op/log.hpp

@@ -37,6 +37,7 @@ namespace ngraph
                 /// \param arg Node that produces the input tensor.
                 Log(const Output<Node>& arg);
 
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 virtual std::shared_ptr<Node>
                     copy_with_new_args(const NodeVector& new_args) const override;
 

src/ngraph/op/lrn.cpp

@@ -15,6 +15,7 @@
 //*****************************************************************************
 
 #include "ngraph/op/lrn.hpp"
+#include "ngraph/attribute_visitor.hpp"
 #include "ngraph/op/constant.hpp"
 #include "ngraph/op/multiply.hpp"
 
@@ -111,6 +112,15 @@ void op::LRN::validate_and_infer_types()
                           ").");
 }
 
+bool ngraph::op::v0::LRN::visit_attributes(AttributeVisitor& visitor)
+{
+    visitor.on_attribute("alpha", m_alpha);
+    visitor.on_attribute("beta", m_beta);
+    visitor.on_attribute("bias", m_bias);
+    visitor.on_attribute("size", m_size);
+    return true;
+}
+
 shared_ptr<Node> op::LRN::copy_with_new_args(const NodeVector& new_args) const
 {
     check_new_args_count(this, new_args);

src/ngraph/op/lrn.hpp

@@ -58,6 +58,7 @@ namespace ngraph
                     double bias,
                     size_t size);
 
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 virtual std::shared_ptr<Node>
                     copy_with_new_args(const NodeVector& new_args) const override;
                 void validate_and_infer_types() override;

src/ngraph/op/not.cpp

@@ -28,6 +28,11 @@ op::v1::LogicalNot::LogicalNot(const Output<Node>& arg)
     constructor_validate_and_infer_types();
 }
 
+bool ngraph::op::v1::LogicalNot::visit_attributes(AttributeVisitor& visitor)
+{
+    return true;
+}
+
 // TODO(amprocte): Update this to allow only boolean, for consistency with logical binops.
 void op::v1::LogicalNot::validate_and_infer_types()
 {

src/ngraph/op/not.hpp

@@ -37,6 +37,7 @@ namespace ngraph
                 /// \param arg Node that produces the input tensor.
                 LogicalNot(const Output<Node>& arg);
 
+                bool visit_attributes(AttributeVisitor& visitor) override;
                 void validate_and_infer_types() override;
 
                 virtual std::shared_ptr<Node>

test/attributes.cpp

@@ -17,6 +17,7 @@
 #include "gtest/gtest.h"
 
 #include "ngraph/ngraph.hpp"
+#include "ngraph/opsets/opset1.hpp"
 
 using namespace std;
 using namespace ngraph;
@@ -140,16 +141,26 @@ public:
     double get_double(const string& name) { return m_doubles.at(name); }
     int64_t get_signed(const string& name) { return m_signeds.at(name); }
     uint64_t get_unsigned(const string& name) { return m_unsigneds.at(name); }
+    vector<float>& get_float_vector(const string& name) { return m_float_vectors.at(name); }
     vector<int64_t>& get_signed_vector(const string& name) { return m_signed_vectors.at(name); }
+    vector<string>& get_string_vector(const string& name) { return m_string_vectors.at(name); }
     void set_string(const string& name, const string& value) { m_strings[name] = value; }
     void set_bool(const string& name, bool value) { m_bools[name] = value; }
     void set_double(const string& name, double value) { m_doubles[name] = value; }
     void set_signed(const string& name, int64_t value) { m_signeds[name] = value; }
     void set_unsigned(const string& name, uint64_t value) { m_unsigneds[name] = value; }
+    void set_float_vector(const string& name, const vector<float>& value)
+    {
+        m_float_vectors[name] = value;
+    }
     void set_signed_vector(const string& name, const vector<int64_t>& value)
     {
         m_signed_vectors[name] = value;
     }
+    void set_string_vector(const string& name, const vector<string>& value)
+    {
+        m_string_vectors[name] = value;
+    }
 
     void on_attribute(const string& name, string& value) override { set_string(name, value); };
     void on_attribute(const string& name, bool& value) override { set_bool(name, value); }
@@ -162,10 +173,6 @@ public:
     {
         set_string(name, adapter.get());
     };
-    void on_adapter(const string& name, ValueAccessor<vector<int64_t>>& adapter) override
-    {
-        set_signed_vector(name, adapter.get());
-    }
     void on_adapter(const string& name, ValueAccessor<int64_t>& adapter) override
     {
         set_signed(name, adapter.get());
@@ -174,6 +181,18 @@ public:
     {
         set_double(name, adapter.get());
     }
+    void on_adapter(const string& name, ValueAccessor<vector<float>>& adapter) override
+    {
+        set_float_vector(name, adapter.get());
+    }
+    void on_adapter(const string& name, ValueAccessor<vector<int64_t>>& adapter) override
+    {
+        set_signed_vector(name, adapter.get());
+    }
+    void on_adapter(const string& name, ValueAccessor<vector<string>>& adapter) override
+    {
+        set_string_vector(name, adapter.get());
+    }
 
 protected:
     NodeTypeInfo m_node_type_info;
@@ -183,6 +202,8 @@ protected:
     map<string, int64_t> m_signeds;
     map<string, uint64_t> m_unsigneds;
     map<string, vector<int64_t>> m_signed_vectors;
+    map<string, vector<float>> m_float_vectors;
+    map<string, vector<std::string>> m_string_vectors;
 };
 
 class NodeBuilder : public AttributeVisitor
@@ -197,7 +218,6 @@ public:
     {
         shared_ptr<Node> node(FactoryRegistry<Node>::get().create(m_values.get_node_type_info()));
         node->visit_attributes(*this);
-        node->validate_and_infer_types();
         return node;
     }
 
@@ -215,10 +235,6 @@ public:
     {
         adapter.set(m_values.get_string(name));
     };
-    void on_adapter(const string& name, ValueAccessor<vector<int64_t>>& adapter) override
-    {
-        adapter.set(m_values.get_signed_vector(name));
-    }
     void on_adapter(const string& name, ValueAccessor<int64_t>& adapter) override
     {
         adapter.set(m_values.get_signed(name));
@@ -227,6 +243,18 @@ public:
     {
         adapter.set(m_values.get_double(name));
     }
+    void on_adapter(const string& name, ValueAccessor<vector<int64_t>>& adapter) override
+    {
+        adapter.set(m_values.get_signed_vector(name));
+    }
+    void on_adapter(const string& name, ValueAccessor<vector<string>>& adapter) override
+    {
+        adapter.set(m_values.get_string_vector(name));
+    }
+    void on_adapter(const string& name, ValueAccessor<vector<float>>& adapter) override
+    {
+        adapter.set(m_values.get_float_vector(name));
+    }
 
 protected:
     NodeSaver m_values;
@@ -256,3 +284,217 @@ TEST(attributes, user_op)
     EXPECT_EQ(g_oracle->get_hyper_parameters(), oracle->get_hyper_parameters());
     EXPECT_EQ(g_oracle->get_ultra_parameters(), oracle->get_ultra_parameters());
 }
+
+TEST(attributes, elu_op)
+{
+    FactoryRegistry<Node>::get().register_factory<opset1::Elu>();
+    auto data = make_shared<op::Parameter>(element::f32, Shape{2, 4});
+
+    double alpha = 0.1;
+
+    const auto elu = make_shared<opset1::Elu>(data, alpha);
+    NodeBuilder builder(elu);
+    auto g_elu = as_type_ptr<opset1::Elu>(builder.create());
+
+    EXPECT_EQ(g_elu->get_alpha(), elu->get_alpha());
+}
+
+TEST(attributes, fake_quantize_op)
+{
+    FactoryRegistry<Node>::get().register_factory<opset1::FakeQuantize>();
+    const auto data = make_shared<op::Parameter>(element::f32, Shape{1, 2, 3, 4});
+    const auto input_low = make_shared<op::Parameter>(element::f32, Shape{});
+    const auto input_high = make_shared<op::Parameter>(element::f32, Shape{});
+    const auto output_low = make_shared<op::Parameter>(element::f32, Shape{});
+    const auto output_high = make_shared<op::Parameter>(element::f32, Shape{});
+
+    auto levels = 5;
+    auto auto_broadcast = op::AutoBroadcastType::NUMPY;
+
+    const auto fake_quantize = make_shared<op::FakeQuantize>(
+        data, input_low, input_high, output_low, output_high, levels, auto_broadcast);
+    NodeBuilder builder(fake_quantize);
+    auto g_fake_quantize = as_type_ptr<opset1::FakeQuantize>(builder.create());
+
+    EXPECT_EQ(g_fake_quantize->get_levels(), fake_quantize->get_levels());
+    EXPECT_EQ(g_fake_quantize->get_auto_broadcast(), fake_quantize->get_auto_broadcast());
+}
+
+TEST(attributes, grn_op)
+{
+    FactoryRegistry<Node>::get().register_factory<opset1::GRN>();
+    auto data = make_shared<op::Parameter>(element::f32, Shape{2, 3, 4, 5});
+
+    float bias = 1.25f;
+
+    auto grn = make_shared<opset1::GRN>(data, bias);
+    NodeBuilder builder(grn);
+    auto g_grn = as_type_ptr<opset1::GRN>(builder.create());
+
+    EXPECT_EQ(g_grn->get_bias(), grn->get_bias());
+}
+
+TEST(attributes, group_conv_op)
+{
+    FactoryRegistry<Node>::get().register_factory<opset1::GroupConvolution>();
+    auto data = make_shared<op::Parameter>(element::f32, Shape{1, 12, 224, 224});
+    auto filters = make_shared<op::Parameter>(element::f32, Shape{4, 1, 3, 5, 5});
+    auto strides = Strides{1, 1};
+    auto pads_begin = CoordinateDiff{1, 2};
+    auto pads_end = CoordinateDiff{1, 2};
+    auto dilations = Strides{1, 1};
+    auto group_conv = make_shared<opset1::GroupConvolution>(
+        data, filters, strides, pads_begin, pads_end, dilations, op::PadType::VALID);
+    NodeBuilder builder(group_conv);
+    auto g_group_conv = as_type_ptr<opset1::GroupConvolution>(builder.create());
+    EXPECT_EQ(g_group_conv->get_strides(), group_conv->get_strides());
+    EXPECT_EQ(g_group_conv->get_pads_begin(), group_conv->get_pads_begin());
+    EXPECT_EQ(g_group_conv->get_pads_end(), group_conv->get_pads_end());
+    EXPECT_EQ(g_group_conv->get_dilations(), group_conv->get_dilations());
+    EXPECT_EQ(g_group_conv->get_auto_pad(), group_conv->get_auto_pad());
+}
+
+TEST(attributes, group_conv_backprop_data_op)
+{
+    FactoryRegistry<Node>::get().register_factory<opset1::GroupConvolutionBackpropData>();
+    const auto data = make_shared<op::Parameter>(element::f32, Shape{1, 20, 224, 224});
+    const auto filter = make_shared<op::Parameter>(element::f32, Shape{4, 5, 2, 3, 3});
+    const auto output_shape = make_shared<op::Parameter>(element::f32, Shape{1, 8, 447, 447});
+
+    const auto strides = Strides{2, 1};
+    const auto pads_begin = CoordinateDiff{3, 4};
+    const auto pads_end = CoordinateDiff{4, 6};
+    const auto dilations = Strides{3, 1};
+    const auto auto_pad = op::PadType::EXPLICIT;
+    const auto output_padding = CoordinateDiff{3, 4};
+
+    const auto gcbd = make_shared<opset1::GroupConvolutionBackpropData>(data,
+                                                                        filter,
+                                                                        output_shape,
+                                                                        strides,
+                                                                        pads_begin,
+                                                                        pads_end,
+                                                                        dilations,
+                                                                        auto_pad,
+                                                                        output_padding);
+    NodeBuilder builder(gcbd);
+    const auto g_gcbd = as_type_ptr<opset1::GroupConvolutionBackpropData>(builder.create());
+
+    EXPECT_EQ(g_gcbd->get_strides(), gcbd->get_strides());
+    EXPECT_EQ(g_gcbd->get_pads_begin(), gcbd->get_pads_begin());
+    EXPECT_EQ(g_gcbd->get_pads_end(), gcbd->get_pads_end());
+    EXPECT_EQ(g_gcbd->get_dilations(), gcbd->get_dilations());
+    EXPECT_EQ(g_gcbd->get_auto_pad(), gcbd->get_auto_pad());
+    EXPECT_EQ(g_gcbd->get_output_padding(), gcbd->get_output_padding());
+}
+
+TEST(attributes, lrn_op)
+{
+    FactoryRegistry<Node>::get().register_factory<opset1::LRN>();
+    const auto arg = make_shared<op::Parameter>(element::f32, Shape{1, 2, 3, 4});
+    const auto axes = make_shared<op::Parameter>(element::i32, Shape{2});
+
+    const double alpha = 1.1;
+    const double beta = 2.2;
+    const double bias = 3.3;
+    const size_t size = 4;
+
+    const auto lrn = make_shared<opset1::LRN>(arg, axes, alpha, beta, bias, size);
+    NodeBuilder builder(lrn);
+    auto g_lrn = as_type_ptr<opset1::LRN>(builder.create());
+
+    EXPECT_EQ(g_lrn->get_alpha(), lrn->get_alpha());
+    EXPECT_EQ(g_lrn->get_beta(), lrn->get_beta());
+    EXPECT_EQ(g_lrn->get_bias(), lrn->get_bias());
+    EXPECT_EQ(g_lrn->get_nsize(), lrn->get_nsize());
+}
+
+TEST(attributes, lstm_cell_op)
+{
+    FactoryRegistry<Node>::get().register_factory<opset1::LSTMCell>();
+    auto X = make_shared<op::Parameter>(element::f32, Shape{2, 3});
+    auto H = make_shared<op::Parameter>(element::f32, Shape{2, 3});
+    auto W = make_shared<op::Parameter>(element::f32, Shape{12, 3});
+    auto R = make_shared<op::Parameter>(element::f32, Shape{12, 3});
+    const auto initial_hidden_state = make_shared<op::Parameter>(element::f32, Shape{2, 3});
+    const auto initial_cell_state = make_shared<op::Parameter>(element::f32, Shape{2, 3});
+
+    const auto hidden_size = 3;
+    const auto weights_format = op::LSTMWeightsFormat::ICOF;
+    const std::vector<std::string> activations = {"tanh", "sigmoid", "tanh"};
+    auto activations_alpha = std::vector<float>{1.0, 1.5};
+    auto activations_beta = std::vector<float>{2.0, 1.0};
+    const float clip = 0.5f;
+    bool input_forget = true;
+
+    const auto lstm_cell = make_shared<opset1::LSTMCell>(X,
+                                                         initial_hidden_state,
+                                                         initial_cell_state,
+                                                         W,
+                                                         R,
+                                                         hidden_size,
+                                                         weights_format,
+                                                         activations,
+                                                         activations_alpha,
+                                                         activations_beta,
+                                                         clip,
+                                                         input_forget);
+    NodeBuilder builder(lstm_cell);
+    auto g_lstm_cell = as_type_ptr<opset1::LSTMCell>(builder.create());
+
+    EXPECT_EQ(g_lstm_cell->get_hidden_size(), lstm_cell->get_hidden_size());
+    EXPECT_EQ(g_lstm_cell->get_activations(), lstm_cell->get_activations());
+    EXPECT_EQ(g_lstm_cell->get_activations_alpha(), lstm_cell->get_activations_alpha());
+    EXPECT_EQ(g_lstm_cell->get_activations_beta(), lstm_cell->get_activations_beta());
+    EXPECT_EQ(g_lstm_cell->get_clip(), lstm_cell->get_clip());
+    EXPECT_EQ(g_lstm_cell->get_input_forget(), lstm_cell->get_input_forget());
+    EXPECT_EQ(g_lstm_cell->get_weights_format(), lstm_cell->get_weights_format());
+}
+
+TEST(attributes, lstm_sequence_op)
+{
+    FactoryRegistry<Node>::get().register_factory<opset1::LSTMSequence>();
+    const auto X = make_shared<op::Parameter>(element::f32, Shape{1, 2, 4});
+    const auto initial_hidden_state = make_shared<op::Parameter>(element::f32, Shape{1, 2, 3});
+    const auto initial_cell_state = make_shared<op::Parameter>(element::f32, Shape{1, 2, 3});
+    const auto sequence_lengths = make_shared<op::Parameter>(element::i32, Shape{2});
+    const auto W = make_shared<op::Parameter>(element::f32, Shape{1, 12, 4});
+    const auto R = make_shared<op::Parameter>(element::f32, Shape{1, 12, 3});
+    const auto B = make_shared<op::Parameter>(element::f32, Shape{1, 12});
+
+    const auto hidden_size = 3;
+    const auto lstm_direction = op::LSTMSequence::direction::FORWARD;
+    const auto weights_format = op::LSTMWeightsFormat::ICOF;
+    const std::vector<float> activations_alpha = {1, 2, 3};
+    const std::vector<float> activations_beta = {4, 5, 6};
+    const std::vector<std::string> activations = {"tanh", "sigmoid", "tanh"};
+    const float clip_threshold = 0.5f;
+    const bool input_forget = true;
+
+    const auto lstm_sequence = make_shared<opset1::LSTMSequence>(X,
+                                                                 initial_hidden_state,
+                                                                 initial_cell_state,
+                                                                 sequence_lengths,
+                                                                 W,
+                                                                 R,
+                                                                 B,
+                                                                 hidden_size,
+                                                                 lstm_direction,
+                                                                 weights_format,
+                                                                 activations_alpha,
+                                                                 activations_beta,
+                                                                 activations,
+                                                                 clip_threshold,
+                                                                 input_forget);
+    NodeBuilder builder(lstm_sequence);
+    auto g_lstm_sequence = as_type_ptr<opset1::LSTMSequence>(builder.create());
+
+    EXPECT_EQ(g_lstm_sequence->get_hidden_size(), lstm_sequence->get_hidden_size());
+    EXPECT_EQ(g_lstm_sequence->get_activations(), lstm_sequence->get_activations());
+    EXPECT_EQ(g_lstm_sequence->get_activations_alpha(), lstm_sequence->get_activations_alpha());
+    EXPECT_EQ(g_lstm_sequence->get_activations_beta(), lstm_sequence->get_activations_beta());
+    EXPECT_EQ(g_lstm_sequence->get_clip_threshold(), lstm_sequence->get_clip_threshold());
+    EXPECT_EQ(g_lstm_sequence->get_direction(), lstm_sequence->get_direction());
+    EXPECT_EQ(g_lstm_sequence->get_input_forget(), lstm_sequence->get_input_forget());
+    EXPECT_EQ(g_lstm_sequence->get_weights_format(), lstm_sequence->get_weights_format());
+}