[misc] upgrade format to py39 (#7256)

src/llamafactory/extras/ploting.py

@@ -15,7 +15,7 @@
 import json
 import math
 import os
-from typing import Any, Dict, List
+from typing import Any
 
 from transformers.trainer import TRAINER_STATE_NAME
 
@@ -31,10 +31,8 @@ if is_matplotlib_available():
 logger = logging.get_logger(__name__)
 
 
-def smooth(scalars: List[float]) -> List[float]:
-    r"""
-    EMA implementation according to TensorBoard.
-    """
+def smooth(scalars: list[float]) -> list[float]:
+    r"""EMA implementation according to TensorBoard."""
     if len(scalars) == 0:
         return []
 
@@ -48,10 +46,8 @@ def smooth(scalars: List[float]) -> List[float]:
     return smoothed
 
 
-def gen_loss_plot(trainer_log: List[Dict[str, Any]]) -> "matplotlib.figure.Figure":
-    r"""
-    Plots loss curves in LlamaBoard.
-    """
+def gen_loss_plot(trainer_log: list[dict[str, Any]]) -> "matplotlib.figure.Figure":
+    r"""Plot loss curves in LlamaBoard."""
     plt.close("all")
     plt.switch_backend("agg")
     fig = plt.figure()
@@ -70,10 +66,8 @@ def gen_loss_plot(trainer_log: List[Dict[str, Any]]) -> "matplotlib.figure.Figur
     return fig
 
 
-def plot_loss(save_dictionary: str, keys: List[str] = ["loss"]) -> None:
-    r"""
-    Plots loss curves and saves the image.
-    """
+def plot_loss(save_dictionary: str, keys: list[str] = ["loss"]) -> None:
+    r"""Plot loss curves and saves the image."""
     plt.switch_backend("agg")
     with open(os.path.join(save_dictionary, TRAINER_STATE_NAME), encoding="utf-8") as f:
         data = json.load(f)