Update docstring to comply with coding style and max column length

src/converter/pytorch_node.py

@@ -13,16 +13,14 @@ class PyTorchNodeType(Enum):
 
 class PyTorchNode:
     """
-    Represents a node in a PyTorch execution trace, initialized based on a
-    schema version.
+    Represents a node in a PyTorch execution trace, initialized based on a schema version.
 
     Attributes:
         schema (str): Schema version used for initialization.
         data_deps (List[PyTorchNode]): List of data-dependent parent nodes.
         children (List[PyTorchNode]): List of child nodes.
         gpu_children (List[PyTorchNode]): List of GPU-specific child nodes.
-        record_param_comms_node (Optional[PyTorchNode]): Corresponding
-            record_param_comms node.
+        record_param_comms_node (Optional[PyTorchNode]): Corresponding record_param_comms node.
         nccl_node (Optional[PyTorchNode]): Corresponding NCCL node.
         id (str): Identifier of the node.
         name (str): Name of the node.
@@ -45,10 +43,8 @@ def __init__(self, schema: str, node_data: Dict[str, Any]) -> None:
         provided.
 
         Args:
-            schema (str): The schema version based on which the node will be
-                initialized.
-            node_data (Dict[str, Any]): Dictionary containing the data of the
-                PyTorch node.
+            schema (str): The schema version based on which the node will be initialized.
+            node_data (Dict[str, Any]): Dictionary containing the data of the PyTorch node.
         """
         self.schema = schema
         self.data_deps: List["PyTorchNode"] = []
@@ -67,12 +63,8 @@ def __repr__(self) -> str:
             str: String representation of the node.
         """
         return (
-            f"PyTorchNode("
-            f"id={self.id}, name={self.name}, "
-            f"op_type={self.get_op_type()}, "
-            f"timestamp={self.ts}, "
-            f"inclusive_duration={self.inclusive_dur}, "
-            f"exclusive_duration={self.exclusive_dur})"
+            f"PyTorchNode(id={self.id}, name={self.name}, op_type={self.get_op_type()}, timestamp={self.ts}, "
+            f"inclusive_duration={self.inclusive_dur}, exclusive_duration={self.exclusive_dur})"
         )
 
     def parse_data(self, node_data: Dict[str, Any]) -> None:
@@ -87,9 +79,8 @@ def parse_data(self, node_data: Dict[str, Any]) -> None:
                 self._parse_data_1_0_3_chakra_0_0_4(node_data)
         else:
             raise ValueError(
-                f"Unsupported schema version '{self.schema}'. Please check "
-                f"if the schema version is in the list of supported versions: "
-                f"{self.SUPPORTED_VERSIONS}"
+                f"Unsupported schema version '{self.schema}'. Please check if the schema version is in the list of "
+                f"supported versions: {self.SUPPORTED_VERSIONS}"
             )
 
     def _parse_data_1_0_3_chakra_0_0_4(self, node_data: Dict[str, Any]) -> None:
@@ -163,8 +154,7 @@ def add_gpu_child(self, gpu_child_node: "PyTorchNode") -> None:
         Adds a child GPU node for this node.
 
         Args:
-            gpu_child_node (Optional[PyTorchNode]): The child GPU node to be
-                added.
+            gpu_child_node (Optional[PyTorchNode]): The child GPU node to be added.
         """
         self.gpu_children.append(gpu_child_node)
 
@@ -173,8 +163,7 @@ def is_record_param_comms_op(self) -> bool:
         Checks if the node is a record_param_comms operator.
 
         Returns:
-            bool: True if the node is a record_param_comms operator, False
-                otherwise.
+            bool: True if the node is a record_param_comms operator, False otherwise.
         """
         return "record_param_comms" in self.name
 
@@ -246,10 +235,8 @@ def get_data_type_size(data_type: str) -> int:
         except KeyError as e:
             traceback_str = traceback.format_exc()
             raise ValueError(
-                f"Unsupported data type: {data_type}. The data_type_size_map "
-                f"dictionary is used for mapping the number of bytes for a "
-                f"given tensor data type. This dictionary may be incomplete. "
-                f"Please update the data_type_size_map or report this issue "
-                f"to the maintainer by creating an issue. Traceback:\n"
+                f"Unsupported data type: {data_type}. The data_type_size_map dictionary is used for mapping the "
+                f"number of bytes for a given tensor data type. This dictionary may be incomplete. Please update the "
+                f"data_type_size_map or report this issue to the maintainer by creating an issue. Traceback:\n"
                 f"{traceback_str}"
             ) from e