clang-format comments: /src/ngraph/frontend (#3503)

* New clang-format rules for src/ngraph/frontend

* Remove now-redundant .clang-format

src/ngraph/frontend/.clang-format

-#
-# OVERRIDE TO STYLE: Comments do *not* wrap.
-#
-BasedOnStyle: LLVM
-IndentWidth: 4
-UseTab: Never
-Language: Cpp
-Standard: Cpp11
-
-AccessModifierOffset: -4
-
-AlignConsecutiveDeclarations: false
-AlignConsecutiveAssignments: false
-AlignTrailingComments: true
-
-AllowShortBlocksOnASingleLine: true
-AllowShortCaseLabelsOnASingleLine: true
-AllowShortFunctionsOnASingleLine: Inline
-
-AlwaysBreakBeforeMultilineStrings: true
-AlwaysBreakTemplateDeclarations: true
-
-BinPackArguments: false
-BinPackParameters: false
-
-BreakBeforeBraces: Allman
-BreakConstructorInitializersBeforeComma: true
-
-ColumnLimit: 100
-CommentPragmas: '.*'
-
-IndentCaseLabels: false
-IndentWrappedFunctionNames: true
-
-KeepEmptyLinesAtTheStartOfBlocks: false
-NamespaceIndentation: All
-
-PointerAlignment: Left
-SpaceAfterCStyleCast: false
-SpaceBeforeAssignmentOperators: true
-SpaceBeforeParens: ControlStatements
-SpaceInEmptyParentheses: false
-SpacesInAngles: false
-SpacesInCStyleCastParentheses: false
-SpacesInParentheses: false
-SpacesInSquareBrackets: false
-
-SortIncludes: false
-ReflowComments: true
-
-IncludeCategories:
-  - Regex:           '^".*'
-    Priority:        3
-  - Regex:           '^<.*'
-    Priority:        2
-SortIncludes: true

src/ngraph/frontend/onnx_import/core/graph.cpp

@@ -104,7 +104,8 @@ namespace ngraph
                 {
                     unknown_operators.emplace(detail::get_op_domain_and_name(node_proto),
                                               node_proto);
-                    // If a node from an unregistered domain is detected, try registering that domain
+                    // If a node from an unregistered domain is detected, try registering that
+                    // domain
                     m_model->enable_opset_domain(detail::get_node_domain(node_proto));
                 }
             }

src/ngraph/frontend/onnx_import/core/model.hpp

@@ -53,8 +53,10 @@ namespace ngraph
             /// \param name       type name of the operator object,
             /// \param domain     domain name of the operator object.
             /// \return Reference to the operator object.
-            /// \throw error::UnknownDomain    there is no operator set defined for the given domain,
-            /// \throw error::UnknownOperator  the given operator type name does not exist in operator set.
+            /// \throw error::UnknownDomain    there is no operator set defined for the given
+            ///                                domain,
+            /// \throw error::UnknownOperator  the given operator type name does not exist in
+            ///                                operator set.
             const Operator& get_operator(const std::string& name, const std::string& domain) const;
 
             /// \brief Check availability of operator base on NodeProto.

src/ngraph/frontend/onnx_import/op/abs.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/acos.hpp

@@ -36,7 +36,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/acosh.cpp

@@ -53,7 +53,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/acosh.hpp

@@ -32,7 +32,7 @@ namespace ngraph
                 NodeVector acosh(const Node& node);
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/add.hpp

@@ -53,7 +53,7 @@ namespace ngraph
 
             } // namespace set_7
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/and.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/argmax.cpp

@@ -34,7 +34,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/argmax.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/argmin.cpp

@@ -34,7 +34,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/argmin.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/asin.hpp

@@ -36,7 +36,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/asinh.cpp

@@ -52,7 +52,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/asinh.hpp

@@ -32,7 +32,7 @@ namespace ngraph
                 NodeVector asinh(const Node& node);
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/atan.hpp

@@ -36,7 +36,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/atanh.cpp

@@ -56,7 +56,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/atanh.hpp

@@ -32,7 +32,7 @@ namespace ngraph
                 NodeVector atanh(const Node& node);
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/average_pool.cpp

@@ -33,7 +33,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/average_pool.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/batch_norm.cpp

@@ -75,7 +75,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/batch_norm.hpp

@@ -30,7 +30,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/cast.cpp

@@ -39,7 +39,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/cast.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/ceil.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/clip.cpp

@@ -43,7 +43,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/clip.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/concat.cpp

@@ -45,7 +45,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/concat.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/constant.cpp

@@ -151,7 +151,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/constant.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/conv.cpp

@@ -53,7 +53,8 @@ namespace ngraph
                         {
                             // Split one convolution op to N ops where N is the number of groups
                             // and concat results after computation.
-                            // reference: https://github.com/NervanaSystems/ngraph-mxnet/blob/fdd692/src/ngraph/ngraph_emitter.cc#L822-L856
+                            // reference:
+                            // https://github.com/NervanaSystems/ngraph-mxnet/blob/fdd692/src/ngraph/ngraph_emitter.cc#L822-L856
                             std::size_t n_data_channels{data->get_shape().at(1)};
                             std::size_t n_filters_channels{filters->get_shape().at(0)};
                             std::size_t data_group_size{n_data_channels / groups};
@@ -166,7 +167,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/conv.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/conv_integer.cpp

@@ -113,7 +113,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/conv_integer.hpp

@@ -31,13 +31,13 @@ namespace ngraph
                 ///
                 /// \param node   The ONNX node object representing this operation.
                 ///
-                /// \return The vector containing Ngraph nodes producing output of quantized ONNX convolution
-                ///         operation.
+                /// \return The vector containing Ngraph nodes producing output of quantized ONNX
+                ///         convolution operation.
                 NodeVector conv_integer(const Node& node);
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/conv_transpose.cpp

@@ -120,7 +120,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/conv_transpose.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/cos.hpp

@@ -36,7 +36,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/cosh.hpp

@@ -36,7 +36,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/depth_to_space.cpp

@@ -33,7 +33,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/depth_to_space.hpp

@@ -39,7 +39,7 @@ namespace ngraph
                 NodeVector depth_to_space(const Node& node);
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/dequantize_linear.cpp

@@ -83,7 +83,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/dequantize_linear.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/div.hpp

@@ -53,7 +53,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/dropout.hpp

@@ -38,7 +38,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/elu.cpp

@@ -40,7 +40,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/elu.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/equal.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/erf.hpp

@@ -36,7 +36,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/exp.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/eye_like.hpp

@@ -30,7 +30,7 @@ namespace ngraph
                 NodeVector eye_like(const Node& node);
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/flatten.cpp

@@ -42,7 +42,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace  onnx_import
 

src/ngraph/frontend/onnx_import/op/flatten.hpp

@@ -33,7 +33,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace  onnx_import
 

src/ngraph/frontend/onnx_import/op/floor.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/gather.hpp

@@ -44,7 +44,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/gemm.cpp

@@ -46,7 +46,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace  onnx_import
 

src/ngraph/frontend/onnx_import/op/gemm.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace  onnx_import
 

src/ngraph/frontend/onnx_import/op/global_average_pool.hpp

@@ -31,8 +31,8 @@ namespace ngraph
                 ///
                 /// \param node   The ONNX node object representing this operation.
                 ///
-                /// \return The vector containing Ngraph nodes producing output of ONNX GlobalAveragePool
-                ///         operation.
+                /// \return The vector containing Ngraph nodes producing output of ONNX
+                ///         GlobalAveragePool operation.
                 NodeVector global_average_pool(const Node& node);
 
             } // namespace set_1

src/ngraph/frontend/onnx_import/op/global_max_pool.hpp

@@ -31,8 +31,8 @@ namespace ngraph
                 ///
                 /// \param node   The ONNX node object representing this operation.
                 ///
-                /// \return The vector containing Ngraph nodes producing output of ONNX GlobalMaxPool
-                ///         operation.
+                /// \return The vector containing Ngraph nodes producing output of ONNX
+                ///         GlobalMaxPool operation.
                 NodeVector global_max_pool(const Node& node);
 
             } // namespace set_1

src/ngraph/frontend/onnx_import/op/greater.hpp

@@ -38,7 +38,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/hard_sigmoid.cpp

@@ -41,7 +41,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/hard_sigmoid.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/hardmax.hpp

@@ -30,7 +30,7 @@ namespace ngraph
                 NodeVector hardmax(const Node& node);
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/identity.hpp

@@ -33,7 +33,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/instance_norm.cpp

@@ -86,7 +86,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/instance_norm.hpp

@@ -27,7 +27,8 @@ namespace ngraph
         {
             namespace set_1
             {
-                /// \brief      Creates nGraph node representing ONNX InstanceNormalization operator.
+                /// \brief      Creates nGraph node representing ONNX InstanceNormalization
+                ///             operator.
                 ///
                 /// \note       The resulting node represents following equation:
                 ///             y = scale * (x - mean) / sqrt(variance + epsilon) + B
@@ -40,7 +41,7 @@ namespace ngraph
                 NodeVector instance_norm(const Node& node);
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/leaky_relu.cpp

@@ -54,7 +54,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/leaky_relu.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/less.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/log.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/log_softmax.hpp

@@ -38,7 +38,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/lp_norm.cpp

@@ -58,7 +58,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/lp_norm.hpp

@@ -32,7 +32,8 @@ namespace ngraph
                 ///             Suppose A contains spatial dimensions of input tensor, then
                 ///             for matrix A we have p-norm defined as following double sum over
                 ///             all elements:
-                ///             ||A||_p = ||vec(A)||_p = [sum_{i=1}^m sum_{j=1}^n abs(a_{i,j})^p]^{1/p}
+                ///             ||A||_p = ||vec(A)||_p =
+                ///                  [sum_{i=1}^m sum_{j=1}^n abs(a_{i,j})^p]^{1/p}
                 ///
                 /// \param[in]  node  The input ONNX node representing this operation.
                 ///
@@ -41,7 +42,7 @@ namespace ngraph
                 NodeVector lp_norm(const Node& node);
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/lp_pool.cpp

@@ -72,7 +72,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/lp_pool.hpp

@@ -37,7 +37,8 @@ namespace ngraph
                 ///             Suppose A contains spatial dimensions of input tensor, then
                 ///             for matrix A we have p-norm defined as following double sum over
                 ///             all elements:
-                ///             ||A||_p = ||vec(A)||_p = [sum_{i=1}^m sum_{j=1}^n abs(a_{i,j})^p]^{1/p}
+                ///             ||A||_p = ||vec(A)||_p =
+                ///                 [sum_{i=1}^m sum_{j=1}^n abs(a_{i,j})^p]^{1/p}
                 ///
                 /// \param[in]  node  The input ONNX node representing this operation.
                 ///
@@ -46,7 +47,7 @@ namespace ngraph
                 NodeVector global_lp_pool(const Node& node);
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/lrn.cpp

@@ -40,7 +40,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/lrn.hpp

@@ -30,7 +30,7 @@ namespace ngraph
                 NodeVector lrn(const Node& node);
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/lstm.cpp

@@ -77,9 +77,11 @@ namespace ngraph
                         // ----- Mandatory inputs ------
                         // Packed input sequences. Shape: [seq_length, batch_size, input_size]
                         m_map[LSTMInput::LSTM_INPUT_X] = ng_inputs.at(0);
-                        // Weight tensor for the gates. Shape: [num_directions, 4*hidden_size, input_size]
+                        // Weight tensor for the gates.
+                        // Shape: [num_directions, 4*hidden_size, input_size]
                         m_map[LSTMInput::LSTM_INPUT_W] = ng_inputs.at(1);
-                        // The recurrence weight tensor. Shape: [num_directions, 4*hidden_size, hidden_size]
+                        // The recurrence weight tensor.
+                        // Shape: [num_directions, 4*hidden_size, hidden_size]
                         m_map[LSTMInput::LSTM_INPUT_R] = ng_inputs.at(2);
 
                         const std::size_t hidden_size =
@@ -116,7 +118,8 @@ namespace ngraph
                                 std::vector<std::int32_t>(
                                     batch_size, m_map[LSTMInput::LSTM_INPUT_X]->get_shape().at(0)));
                         }
-                        // The initial value of the hidden. Shape [num_directions, batch_size, hidden_size]
+                        // The initial value of the hidden.
+                        // Shape [num_directions, batch_size, hidden_size]
                         if (ng_inputs.size() > 5 && !ng_inputs.at(5)->is_null())
                         {
                             m_map[LSTMInput::LSTM_INPUT_INIT_H] = ng_inputs.at(5);
@@ -128,7 +131,8 @@ namespace ngraph
                                 Shape{num_directions, batch_size, hidden_size},
                                 std::vector<float>(num_directions * batch_size * hidden_size, 0.f));
                         }
-                        // The initial value of the cell. Shape [num_directions, batch_size, hidden_size]
+                        // The initial value of the cell.
+                        // Shape [num_directions, batch_size, hidden_size]
                         if (ng_inputs.size() > 6 && !ng_inputs.at(6)->is_null())
                         {
                             m_map[LSTMInput::LSTM_INPUT_INIT_C] = ng_inputs.at(6);
@@ -237,8 +241,8 @@ namespace ngraph
                                          const std::shared_ptr<ngraph::Node>& initial_c,
                                          const std::shared_ptr<ngraph::Node>& seq_lengths,
                                          const LSTMAttributes& attributes)
-                        : m_X{X}
-                        // Since we have forward LSTM we can squeeze `num_directions` axis from inputs.
+                        : m_X{X} // Since we have forward LSTM we can squeeze `num_directions` axis
+                                 // from inputs.
                         , m_W(reshape::squeeze(W))
                         , m_R(reshape::squeeze(R))
                         , m_B(reshape::squeeze(B))
@@ -258,7 +262,8 @@ namespace ngraph
                         // ------ INPUTS ------
                         // X - The input tensor. [seq_length, batch_size, input_size]
                         // W - The weight tensor. [num_directions, 4*hidden_size, input_size]
-                        // R - The recurrence weight tensor. [num_directions, 4*hidden_size, hidden_size]
+                        // R - The recurrence weight tensor. [num_directions, 4*hidden_size,
+                        //                                    hidden_size]
                         // B - The bias tensor for input gate. [num_directions, 8*hidden_size]
                         // P - The weight tensor for peepholes. [num_directions, 3*hidde_size]
                         // ------ ACRONYMS ------
@@ -452,7 +457,8 @@ namespace ngraph
                     }
                     if (attributes.m_direction == LSTMDirection::LSTM_DIRECTION_BIDIRECTIONAL)
                     {
-                        // In bidirectional mode weights are stacked together, so we must split them.
+                        // In bidirectional mode weights are stacked together, so we must split
+                        // them.
                         NodeVector W{
                             ngraph::builder::split(input_map.at(LSTMInput::LSTM_INPUT_W), 2)};
                         NodeVector R{
@@ -502,7 +508,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/lstm.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/matmul.cpp

@@ -32,7 +32,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/matmul.hpp

@@ -30,7 +30,7 @@ namespace ngraph
                 NodeVector matmul(const Node& node);
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/matmul_integer.cpp

@@ -32,7 +32,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/matmul_integer.hpp

@@ -31,13 +31,13 @@ namespace ngraph
                 ///
                 /// \param node The ONNX node object representing this operation.
                 ///
-                /// \return The vector containing Ngraph nodes producing output of quantized ONNX matrix
-                ///         multiplication operation.
+                /// \return The vector containing Ngraph nodes producing output of quantized ONNX
+                ///         matrix multiplication operation.
                 NodeVector matmul_integer(const Node& node);
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/max.hpp

@@ -45,7 +45,7 @@ namespace ngraph
 
             } // namespace set_8
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/max_pool.cpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/max_pool.hpp

@@ -39,7 +39,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/mean.cpp

@@ -33,7 +33,8 @@ namespace ngraph
                     auto sum = variadic::make_ng_variadic_op<ngraph::op::Add>(node).front();
                     auto shape = sum->get_shape();
 
-                    // Create a Constant representing the number of inputs with the same shape as sum
+                    // Create a Constant representing the number of inputs with the same shape as
+                    // sum
                     auto count = ngraph::op::Constant::create(
                         sum->get_element_type(),
                         shape,
@@ -52,7 +53,8 @@ namespace ngraph
                         variadic::make_ng_variadic_op_with_broadcast<ngraph::op::Add>(node).front();
                     auto shape = sum->get_shape();
 
-                    // Create a Constant representing the number of inputs with the same shape as sum
+                    // Create a Constant representing the number of inputs with the same shape as
+                    // sum
                     auto count = ngraph::op::Constant::create(
                         sum->get_element_type(),
                         shape,
@@ -63,7 +65,7 @@ namespace ngraph
 
             } // namespace set_8
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/mean.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/mean_variance_normalization.cpp

@@ -54,7 +54,7 @@ namespace ngraph
 
             } // namespace set_9
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/mean_variance_normalization.hpp

@@ -37,7 +37,7 @@ namespace ngraph
                 NodeVector mean_variance_normalization(const Node& node);
             } // namespace set_9
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/min.hpp

@@ -45,7 +45,7 @@ namespace ngraph
 
             } // namespace set_8
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/mul.hpp

@@ -56,7 +56,7 @@ namespace ngraph
 
             } // namespace set_7
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/neg.hpp

@@ -31,7 +31,7 @@ namespace ngraph
                 inline NodeVector neg(const Node& node) { return {-node.get_ng_inputs().at(0)}; }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/not.hpp

@@ -35,7 +35,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/onehot.cpp

@@ -89,7 +89,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace  onnx_import
 

src/ngraph/frontend/onnx_import/op/onehot.hpp

@@ -33,7 +33,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace  onnx_import
 

src/ngraph/frontend/onnx_import/op/or.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/pad.cpp

@@ -71,7 +71,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/pad.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/pow.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/prelu.cpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/prelu.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/qlinear_matmul.cpp

@@ -32,7 +32,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/qlinear_matmul.hpp

@@ -30,7 +30,7 @@ namespace ngraph
                 NodeVector qlinear_matmul(const Node& node);
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/quant_conv.cpp

@@ -82,7 +82,8 @@ namespace ngraph
                         {
                             // Split one convolution op to N ops where N is the number of groups
                             // and concat results after computation.
-                            // reference: https://github.com/NervanaSystems/ngraph-mxnet/blob/fdd692/src/ngraph/ngraph_emitter.cc#L822-L856
+                            // reference:
+                            // https://github.com/NervanaSystems/ngraph-mxnet/blob/fdd692/src/ngraph/ngraph_emitter.cc#L822-L856
                             std::size_t n_data_channels{data->get_shape().at(1)};
                             std::size_t n_filters_channels{filters->get_shape().at(0)};
 
@@ -270,7 +271,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/quant_conv.hpp

@@ -31,13 +31,13 @@ namespace ngraph
                 ///
                 /// \param node   The ONNX node object representing this operation.
                 ///
-                /// \return The vector containing Ngraph nodes producing output of ONNX quantizied convolution
-                ///         operation.
+                /// \return The vector containing Ngraph nodes producing output of ONNX quantizied
+                ///         convolution operation.
                 NodeVector quant_conv(const Node& node);
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/quantize_linear.cpp

@@ -72,7 +72,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/quantize_linear.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/reciprocal.cpp

@@ -45,7 +45,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/reciprocal.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/reduce.cpp

@@ -61,7 +61,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/reduce.hpp

@@ -41,7 +41,8 @@ namespace ngraph
         {
             namespace set_1
             {
-                /// \brief      Compute the log sum of the input tensor's elements along the provided axes.
+                /// \brief      Compute the log sum of the input tensor's elements along the
+                ///             provided axes.
                 ///
                 /// \par Overview
                 ///     The output tensor has the same rank as the input if Node attribute keepdims
@@ -63,7 +64,8 @@ namespace ngraph
                     return {std::make_shared<ngraph::op::Log>(sum_node)};
                 }
 
-                /// \brief      Compute the log sum exponent of the input tensor's elements along the provided axes.
+                /// \brief      Compute the log sum exponent of the input tensor's elements along
+                ///             the provided axes.
                 ///
                 /// \par Overview
                 ///     The output tensor has the same rank as the input if Node attribute keepdims
@@ -86,7 +88,8 @@ namespace ngraph
                     return {std::make_shared<ngraph::op::Log>(sum_node)};
                 }
 
-                /// \brief      Compute the L1 norm of the input tensor's element along the provided axes.
+                /// \brief      Compute the L1 norm of the input tensor's element along the provided
+                ///             axes.
                 ///
                 /// \par Overview
                 ///     The output tensor has the same rank as the input if Node attribute keepdims
@@ -107,7 +110,8 @@ namespace ngraph
                         node, node.get_ng_inputs().at(0), l1_norm_reduction)};
                 }
 
-                /// \brief      Compute the L2 norm of the input tensor's element along the provided axes.
+                /// \brief      Compute the L2 norm of the input tensor's element along the provided
+                ///             axes.
                 ///
                 /// \par Overview
                 ///     The output tensor has the same rank as the input if Node attribute keepdims
@@ -129,7 +133,8 @@ namespace ngraph
                         node, node.get_ng_inputs().at(0), l2_norm_reduction)};
                 }
 
-                /// \brief      Compute the maximum value of the input tensor's elements along the provided axes.
+                /// \brief      Compute the maximum value of the input tensor's elements along the
+                ///             provided axes.
                 ///
                 /// \par Overview
                 ///     The output tensor has the same rank as the input if Node attribute keepdims
@@ -150,7 +155,8 @@ namespace ngraph
                                          const ngraph::AxisSet&>)};
                 }
 
-                /// \brief      Compute the mean value of the input tensor's elements along the provided axes.
+                /// \brief      Compute the mean value of the input tensor's elements along the
+                ///             provided axes.
                 ///
                 /// \par Overview
                 ///     The output tensor has the same rank as the input if Node attribute keepdims
@@ -163,7 +169,8 @@ namespace ngraph
                 ///
                 NodeVector reduce_mean(const Node& node);
 
-                /// \brief      Compute the minimum value of the input tensor's elements along the provided axes.
+                /// \brief      Compute the minimum value of the input tensor's elements along the
+                ///             provided axes.
                 ///
                 /// \par Overview
                 ///     The output tensor has the same rank as the input if Node attribute keepdims
@@ -184,7 +191,8 @@ namespace ngraph
                                          const ngraph::AxisSet&>)};
                 }
 
-                /// \brief      Compute the product of the input tensor's elements along the provided axes.
+                /// \brief      Compute the product of the input tensor's elements along the
+                ///             provided axes.
                 ///
                 /// \par Overview
                 ///     The output tensor has the same rank as the input if Node attribute keepdims
@@ -205,7 +213,8 @@ namespace ngraph
                                          const ngraph::AxisSet&>)};
                 }
 
-                /// \brief      Compute the sum of the input tensor's elements along the provided axes.
+                /// \brief      Compute the sum of the input tensor's elements along the provided
+                ///             axes.
                 ///
                 /// \par Overview
                 ///     The output tensor has the same rank as the input if Node attribute keepdims
@@ -226,7 +235,8 @@ namespace ngraph
                                          const ngraph::AxisSet&>)};
                 }
 
-                /// \brief      Compute the sum square of the input tensor's element along the provided axes.
+                /// \brief      Compute the sum square of the input tensor's element along the
+                ///             provided axes.
                 ///
                 /// \par Overview
                 ///     The output tensor has the same rank as the input if Node attribute keepdims
@@ -251,7 +261,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/relu.hpp

@@ -36,7 +36,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/reshape.cpp

@@ -68,7 +68,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/reshape.hpp

@@ -38,7 +38,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/reverse_sequence.cpp

@@ -35,7 +35,7 @@ namespace ngraph
                     const auto data = node.get_ng_inputs().at(0);
 
                     const auto sequence_lengths = node.get_ng_inputs().at(1);
-                    //nGraph supports only int32 type of sequence_lengths
+                    // nGraph supports only int32 type of sequence_lengths
                     const auto sequence_lengths_i32 = std::make_shared<ngraph::op::Convert>(
                         node.get_ng_inputs().at(1), element::i32);
 
@@ -48,7 +48,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/selu.cpp

@@ -70,7 +70,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/selu.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/shape.cpp

@@ -42,7 +42,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/shape.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/shrink.cpp

@@ -92,7 +92,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/shrink.hpp

@@ -30,13 +30,13 @@ namespace ngraph
                 /// \brief ONNX Shrink operator
                 ///
                 /// \note It operates on a single input tensor and two attributes: lambd and bias.
-                ///       Input values greater or equal to '-lambd' and less or equal to 'lambd' are zeroed-out.
-                ///       'Bias' is added to the values that are less than '-lambd'
+                ///       Input values greater or equal to '-lambd' and less or equal to 'lambd' are
+                ///       zeroed-out. 'Bias' is added to the values that are less than '-lambd'
                 ///       and subtracted from values greater than 'lambd'.
                 NodeVector shrink(const Node& node);
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/sigmoid.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/sign.hpp

@@ -36,7 +36,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/sin.hpp

@@ -36,7 +36,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/sinh.hpp

@@ -36,7 +36,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/size.cpp

@@ -46,7 +46,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/size.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/slice.cpp

@@ -59,7 +59,8 @@ namespace ngraph
                             get_valid_array_idx(ends.at(idx), data_shape.at(axis));
                     }
 
-                    // Check for cases when start is greater than end and change them to "empty" slice.
+                    // Check for cases when start is greater than end and change them to "empty"
+                    // slice.
                     for (auto idx = 0; idx < lower_bounds.size(); ++idx)
                     {
                         if (lower_bounds.at(idx) > upper_bounds.at(idx))
@@ -73,7 +74,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/slice.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/softmax.cpp

@@ -53,7 +53,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/softmax.hpp

@@ -32,7 +32,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/softplus.cpp

@@ -68,7 +68,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/softplus.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/softsign.cpp

@@ -47,7 +47,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/softsign.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/space_to_depth.cpp

@@ -33,7 +33,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/space_to_depth.hpp

@@ -36,7 +36,7 @@ namespace ngraph
                 NodeVector space_to_depth(const Node& node);
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/split.cpp

@@ -57,7 +57,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/split.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/sqrt.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/squeeze.cpp

@@ -47,6 +47,6 @@ namespace ngraph
                 }
 
             } // namespace set_1
-        }     //namespace op
+        }     // namespace op
     }         // namespace onnx_import
 } // namespace ngraph

src/ngraph/frontend/onnx_import/op/squeeze.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/sub.hpp

@@ -55,7 +55,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/sum.hpp

@@ -45,7 +45,7 @@ namespace ngraph
 
             } // namespace set_8
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/tan.hpp

@@ -36,7 +36,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/tanh.hpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/thresholded_relu.cpp

@@ -50,7 +50,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/thresholded_relu.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/topk.cpp

@@ -61,7 +61,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/topk.hpp

@@ -36,7 +36,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/transpose.cpp

@@ -43,7 +43,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/transpose.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/unsqueeze.cpp

@@ -37,7 +37,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/unsqueeze.hpp

@@ -31,7 +31,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/where.hpp

@@ -40,7 +40,7 @@ namespace ngraph
                 }
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/op/xor.hpp

@@ -45,7 +45,7 @@ namespace ngraph
 
             } // namespace set_1
 
-        } //namespace op
+        } // namespace op
 
     } // namespace onnx_import
 

src/ngraph/frontend/onnx_import/utils/common.hpp

@@ -92,8 +92,8 @@ namespace ngraph
 
             /// \brief Creates a shifted square identity matrix.
             /// \note Shifting in the context of this operator means that
-            ///       the matrix can be created with elements equal to 1 not only in the main diagonal.
-            ///       Shifting adds an offset and moves the diagonal up or down
+            ///       the matrix can be created with elements equal to 1 not only in the main
+            ///       diagonal. Shifting adds an offset and moves the diagonal up or down
             ///
             /// \param[in] output_shape Shape of the resulting matrix.
             /// \param[in] output_type Element type of the resulting matrix.

src/ngraph/frontend/onnx_import/utils/matmul_factory.hpp

@@ -24,15 +24,17 @@ namespace ngraph
     {
         namespace matmul
         {
-            /// \brief  Factory class which generates an nGraph sub-graph based on an ONNX MatMul operation.
+            /// \brief  Factory class which generates an nGraph sub-graph based on an ONNX MatMul
+            ///         operation.
             ///
             /// \note
             /// The sub-graph is needed to adjust nGraph's Dot operation semantics to semantics
             /// expected by ONNX, which are modeled on NumPy's "stacks of arrays" approach.
             /// Differences are apparent with matrices of rank > 2.
             ///
-            /// This default implementation `MatmulFactory` creates a `MatMul` operation for floating-point data.
-            /// Subclasses: `QLinearMatmulFactory` and `MatmulIntegerFactory` implement quantized versions.
+            /// This default implementation `MatmulFactory` creates a `MatMul` operation for
+            /// floating-point data. Subclasses: `QLinearMatmulFactory` and `MatmulIntegerFactory`
+            /// implement quantized versions.
             class MatmulFactory
             {
             public:
@@ -65,7 +67,8 @@ namespace ngraph
                 const NodeVector m_inputs;
             };
 
-            /// \brief  Factory class which generates an nGraph sub-graph based on an ONNX QLinearMatMul operation.
+            /// \brief  Factory class which generates an nGraph sub-graph based on an ONNX
+            ///         QLinearMatMul operation.
             class QLinearMatmulFactory : public MatmulFactory
             {
             public:
@@ -80,7 +83,8 @@ namespace ngraph
                              const std::shared_ptr<ngraph::Node>& right) override;
             };
 
-            /// \brief  Factory class which generates an nGraph sub-graph based on an ONNX MatMulInteger operation.
+            /// \brief  Factory class which generates an nGraph sub-graph based on an ONNX
+            ///         MatMulInteger operation.
             class MatmulIntegerFactory : public MatmulFactory
             {
             public:

src/ngraph/frontend/onnx_import/utils/pooling_factory.hpp

@@ -33,7 +33,8 @@ namespace ngraph
         namespace pooling
         {
             ///
-            /// \brief      Factory class which generates sub-graphs for ONNX 'regular' pooling operators.
+            /// \brief      Factory class which generates sub-graphs for ONNX 'regular' pooling
+            ///             operators.
             ///
             /// \note       This factory is intended for creating pooling operations like:
             ///             - AveragePool
@@ -52,7 +53,8 @@ namespace ngraph
                 ///
                 /// \brief      Creates a sub-graph representing appropriate ONNX operation.
                 ///
-                /// \tparam     NgraphOperator  nGraph operator class type used to build ONNX operation.
+                /// \tparam     NgraphOperator  nGraph operator class type used to build ONNX
+                ///                             operation.
                 ///
                 /// \return     Vector of output nodes.
                 ///
@@ -83,7 +85,8 @@ namespace ngraph
             NodeVector PoolingFactory::make_pooling_op<ngraph::op::AvgPool>() const;
 
             ///
-            /// \brief      Factory class which generates sub-graphs for ONNX 'global' pooling operators.
+            /// \brief      Factory class which generates sub-graphs for ONNX 'global' pooling
+            ///             operators.
             ///
             class GlobalPoolingFactory : public PoolingFactory
             {

src/ngraph/frontend/onnx_import/utils/reshape.cpp

@@ -52,9 +52,9 @@ namespace ngraph
                     }
                 }
 
-                // Check whether there are dimensions equal to -1 in output_shape. There may be at most
-                // one such case. Its value is then inferred from the size of the tensor and the
-                // remaining dimensions.
+                // Check whether there are dimensions equal to -1 in output_shape. There may be at
+                // most one such case. Its value is then inferred from the size of the tensor and
+                // the remaining dimensions.
                 auto neg_value_it =
                     std::find(std::begin(inferred_dims), std::end(inferred_dims), -1);
                 if (neg_value_it != std::end(inferred_dims))

src/ngraph/frontend/onnx_import/utils/reshape.hpp

@@ -34,10 +34,11 @@ namespace ngraph
             /// \brief      Infer `output_shape` dimension values.
             ///
             /// \par Inferention rules
-            ///     \li         The input_shape may consist at most on -1 value. In this case the value
-            ///                 is inferred from the size of the tensor and the remaining dimensions.
-            ///     \li         If a dimension value is equal to 0, then its output value is going to
-            ///                 be copied from the input_shape argument.
+            ///     \li         The input_shape may consist at most on -1 value. In this case the
+            ///                 value is inferred from the size of the tensor and the remaining
+            ///                 dimensions.
+            ///     \li         If a dimension value is equal to 0, then its output value is going
+            ///                 to be copied from the input_shape argument.
             ///
             /// \param[in]  node_name     The node name.
             /// \param[in]  input_shape   The input node shape.