mypy

ignite/handlers/lr_finder.py

@@ -542,7 +542,7 @@ def __init__(
         # override base_lrs
         self.base_lrs = start_lrs
 
-    def get_lr(self) -> List[float]:  # type: ignore[override]
+    def get_lr(self) -> List[float]:
         curr_iter = self.last_epoch + 1
         r = curr_iter / self.num_iter
         return [base_lr * (end_lr / base_lr) ** r for end_lr, base_lr in zip(self.end_lrs, self.base_lrs)]

ignite/handlers/param_scheduler.py

@@ -7,7 +7,7 @@
 from collections import OrderedDict
 from copy import copy
 from pathlib import Path
-from typing import Any, cast, Dict, List, Mapping, Optional, Sequence, Tuple, Type, Union
+from typing import Any, Dict, List, Mapping, Optional, Sequence, Tuple, Type, Union
 
 import torch
 from torch.optim.lr_scheduler import CosineAnnealingWarmRestarts, ReduceLROnPlateau
@@ -992,7 +992,7 @@ def get_param(self) -> Union[float, List[float]]:
         """Method to get current optimizer's parameter value"""
         # Emulate context manager for pytorch>=1.4
         self.lr_scheduler._get_lr_called_within_step = True  # type: ignore[union-attr]
-        lr_list = cast(List[float], self.lr_scheduler.get_lr())
+        lr_list = self.lr_scheduler.get_lr()
         self.lr_scheduler._get_lr_called_within_step = False  # type: ignore[union-attr]
         if len(lr_list) == 1:
             return lr_list[0]
@@ -1670,7 +1670,7 @@ def __init__(
             _scheduler_kwargs["verbose"] = False
 
         self.scheduler = ReduceLROnPlateau(optimizer, **_scheduler_kwargs)
-        self.scheduler._reduce_lr = self._reduce_lr  # type: ignore[attr-defined]
+        self.scheduler._reduce_lr = self._reduce_lr  # type: ignore[method-assign]
 
         self._state_attrs += ["metric_name", "scheduler"]