formatting

src/tf/tf.cpp

@@ -164,7 +164,7 @@ struct tf_parser
             {
                 op.padding_mode = op::convolution::same;
             }
-            else if (pad_mode.find("EXPLICIT") != std::string::npos)
+            else if(pad_mode.find("EXPLICIT") != std::string::npos)
             {
                 std::vector<std::size_t> padding(4);
                 copy(attributes.at("explicit_paddings").list().i(), padding.begin());
@@ -308,19 +308,17 @@ struct tf_parser
     static attribute_map get_attributes(const tensorflow::NodeDef& node)
     {
         attribute_map result;
-        for (auto&& attr : node.attr())
+        for(auto&& attr : node.attr())
         {
             result[attr.first] = attr.second;
         }
         return result;
     }
 
-    static std::string get_name(const tensorflow::NodeDef& node)
-    {
-        return node.name();
-    }
+    static std::string get_name(const tensorflow::NodeDef& node) { return node.name(); }
 
-    static node_map get_nodes(const tensorflow::GraphDef& graph, std::vector<tensorflow::NodeDef>& input_nodes)
+    static node_map get_nodes(const tensorflow::GraphDef& graph,
+                              std::vector<tensorflow::NodeDef>& input_nodes)
     {
         node_map result;
         for(auto&& node : graph.node())
@@ -381,8 +379,7 @@ struct tf_parser
             break; // throw std::runtime_error("Unsupported type VARIANT");
         case tensorflow::DataType::DT_UINT32: shape_type = shape::uint32_type; break;
         case tensorflow::DataType::DT_UINT64: shape_type = shape::uint64_type; break;
-        default:
-            break;
+        default: break;
         }
         return shape_type;
     }
@@ -397,27 +394,32 @@ struct tf_parser
 
         if(!t.tensor_content().empty()) // has raw data
         {
-            const std::string&s = t.tensor_content();
+            const std::string& s = t.tensor_content();
             switch(t.dtype())
             {
             case tensorflow::DataType::DT_INVALID: throw std::runtime_error("");
-            case tensorflow::DataType::DT_FLOAT: return literal{{shape::float_type, dims}, s.data()};
+            case tensorflow::DataType::DT_FLOAT:
+                return literal{{shape::float_type, dims}, s.data()};
             case tensorflow::DataType::DT_UINT8: throw std::runtime_error("");
             case tensorflow::DataType::DT_INT8: return literal{{shape::int32_type, dims}, s.data()};
-            case tensorflow::DataType::DT_UINT16: return literal{{shape::int32_type, dims}, s.data()};
-            case tensorflow::DataType::DT_INT16: return literal{{shape::int32_type, dims}, s.data()};
-            case tensorflow::DataType::DT_INT32: return literal{{shape::int32_type, dims}, s.data()};
-            case tensorflow::DataType::DT_INT64: return literal{{shape::int64_type, dims}, s.data()};
+            case tensorflow::DataType::DT_UINT16:
+                return literal{{shape::int32_type, dims}, s.data()};
+            case tensorflow::DataType::DT_INT16:
+                return literal{{shape::int32_type, dims}, s.data()};
+            case tensorflow::DataType::DT_INT32:
+                return literal{{shape::int32_type, dims}, s.data()};
+            case tensorflow::DataType::DT_INT64:
+                return literal{{shape::int64_type, dims}, s.data()};
             case tensorflow::DataType::DT_STRING: throw std::runtime_error("");
             case tensorflow::DataType::DT_BOOL: return literal{{shape::int32_type, dims}, s.data()};
             case tensorflow::DataType::DT_HALF: return literal{{shape::half_type, dims}, s.data()};
-            case tensorflow::DataType::DT_DOUBLE: return literal{{shape::double_type, dims}, s.data()};
+            case tensorflow::DataType::DT_DOUBLE:
+                return literal{{shape::double_type, dims}, s.data()};
             case tensorflow::DataType::DT_UINT32: throw std::runtime_error("");
             case tensorflow::DataType::DT_UINT64: throw std::runtime_error("");
             case tensorflow::DataType::DT_COMPLEX64: throw std::runtime_error("");
             case tensorflow::DataType::DT_COMPLEX128: throw std::runtime_error("");
-            default:
-                break;
+            default: break;
             }
             MIGRAPHX_THROW("Invalid tensor type");
         }
@@ -449,11 +451,9 @@ struct tf_parser
         case tensorflow::DataType::DT_UINT64: throw std::runtime_error("");
         case tensorflow::DataType::DT_COMPLEX64: throw std::runtime_error("");
         case tensorflow::DataType::DT_COMPLEX128: throw std::runtime_error("");
-        default:
-            break;
+        default: break;
         }
         MIGRAPHX_THROW("Invalid tensor type");
-
     }
 
     static std::vector<size_t> parse_dims(const tensorflow::TensorShapeProto& s)
@@ -466,9 +466,6 @@ struct tf_parser
         }
         return dims;
     }
-
-
-
 };
 
 program parse_tf(const std::string& name, bool is_nhwc)