Black 20 release

examples/benchmarking/plot_csv_file.py

@@ -20,7 +20,9 @@ class PlotArguments:
     Arguments pertaining to which model/config/tokenizer we are going to fine-tune, or train from scratch.
     """
 
-    csv_file: str = field(metadata={"help": "The csv file to plot."},)
+    csv_file: str = field(
+        metadata={"help": "The csv file to plot."},
+    )
     plot_along_batch: bool = field(
         default=False,
         metadata={"help": "Whether to plot along batch size or sequence lengh. Defaults to sequence length."},
@@ -30,7 +32,8 @@ class PlotArguments:
         metadata={"help": "Whether the csv file has time results or memory results. Defaults to memory results."},
     )
     no_log_scale: bool = field(
-        default=False, metadata={"help": "Disable logarithmic scale when plotting"},
+        default=False,
+        metadata={"help": "Disable logarithmic scale when plotting"},
     )
     is_train: bool = field(
         default=False,
@@ -39,7 +42,8 @@ class PlotArguments:
         },
     )
     figure_png_file: Optional[str] = field(
-        default=None, metadata={"help": "Filename under which the plot will be saved. If unused no plot is saved."},
+        default=None,
+        metadata={"help": "Filename under which the plot will be saved. If unused no plot is saved."},
     )
     short_model_names: Optional[List[str]] = list_field(
         default=None, metadata={"help": "List of model names that are used instead of the ones in the csv file."}