reformat inspector doc for better demo

Summary: as title

Differential Revision: D85183062

Author: Gasoonjia

devtools/inspector/_inspector.py

@@ -1036,10 +1036,8 @@ def __init__(
             source_time_scale: The time scale of the performance data retrieved from the runtime. The default time hook implentation in the runtime returns NS.
             target_time_scale: The target time scale to which the users want their performance data converted to. Defaults to MS.
             debug_buffer_path: Debug buffer file path that contains the debug data referenced by ETDump for intermediate and program outputs.
-            delegate_metadata_parser: Optional function to parse delegate metadata from an Profiling Event. Expected signature of the function is:
-                    (delegate_metadata_list: List[bytes]) -> Union[List[str], Dict[str, Any]]
-            delegate_time_scale_converter: Optional function to convert the time scale of delegate profiling data. If not given, use the conversion ratio of
-                    target_time_scale/source_time_scale.
+            delegate_metadata_parser: Optional function to parse delegate metadata from an Profiling Event. Expected signature of the function is (delegate_metadata_list: List[bytes]) -> Union[List[str], Dict[str, Any]].
+            delegate_time_scale_converter: Optional function to convert the time scale of delegate profiling data. If not given, use the conversion ratio of target_time_scale/source_time_scale.
             enable_module_hierarchy: Enable submodules in the operator graph. Defaults to False.
 
         Returns:
@@ -1306,10 +1304,9 @@ def print_data_tabular(
         Displays the underlying EventBlocks in a structured tabular format, with each row representing an Event.
 
         Args:
-            file: Which IO stream to print to. Defaults to stdout.
-                Not used if this is in an IPython environment such as a Jupyter notebook.
-            include_units: Whether headers should include units (default true)
-            include_delegate_debug_data: Whether to include delegate debug metadata (default false)
+            file: Which IO stream to print to. Defaults to stdout. Not used if this is in an IPython environment such as a Jupyter notebook.
+            include_units: Whether headers should include units (default true).
+            include_delegate_debug_data: Whether to include delegate debug metadata (default false).
 
         Returns:
             None
@@ -1419,12 +1416,12 @@ def calculate_numeric_gap(
         compare the intermediate outputs from the AOT and the runtime.
 
         Args:
-            distance: the metrics the inspector will use for gap calculation. Should be one of "MSE", "L1" and "SNR".
-            disable_debug_handle_validation: Often when aten graph has symbolic shape nodes, and inbuilt ops like gt/lt etc.,
-            during re-export of such a graph 'from_node' information is lost from node.meta. As a result we loose connection
-            between edge IR nodes and aten nodes for such ops. By default we validate that every edge IR node has corresponding
-            node in aten IR, and when such validation fails numeric debugger falls back to edge IR as reference graph. This
-            flag allows one to override such behavior and make best effort comparison.
+            distance: The metrics the inspector will use for gap calculation. Should be one of "MSE", "L1" and "SNR".
+            disable_debug_handle_validation: Often when aten graph has symbolic shape nodes and inbuilt ops like gt/lt etc.,
+                during re-export of such a graph 'from_node' information is lost from node.meta. As a result we loose
+                connection between edge IR nodes and aten nodes for such ops. By default we validate that every edge IR
+                node has corresponding node in aten IR, and when such validation fails numeric debugger falls back to edge
+                IR as reference graph. This flag allows one to override such behavior and make best effort comparison.
 
         Returns:
             pd.DataFrame: A DataFrame listing corresponding operator intermediate outputs from both stages and their computed numerical gaps.