Merge pull request #2124 from fzyzcjy/patch-1

Fix super tiny type error

timm/scheduler/cosine_lr.py

@@ -8,6 +8,7 @@
 import math
 import numpy as np
 import torch
+from typing import List
 
 from .scheduler import Scheduler
 
@@ -77,7 +78,7 @@ def __init__(
         else:
             self.warmup_steps = [1 for _ in self.base_values]
 
-    def _get_lr(self, t):
+    def _get_lr(self, t: int) -> List[float]:
         if t < self.warmup_t:
             lrs = [self.warmup_lr_init + t * s for s in self.warmup_steps]
         else:

timm/scheduler/multistep_lr.py

@@ -53,7 +53,7 @@ def get_curr_decay_steps(self, t):
         # assumes self.decay_t is sorted
         return bisect.bisect_right(self.decay_t, t + 1)
 
-    def _get_lr(self, t):
+    def _get_lr(self, t: int) -> List[float]:
         if t < self.warmup_t:
             lrs = [self.warmup_lr_init + t * s for s in self.warmup_steps]
         else:

timm/scheduler/plateau_lr.py

@@ -5,6 +5,7 @@
 Hacked together by / Copyright 2020 Ross Wightman
 """
 import torch
+from typing import List
 
 from .scheduler import Scheduler
 
@@ -106,5 +107,5 @@ def _apply_noise(self, epoch):
             param_group['lr'] = new_lr
         self.restore_lr = restore_lr
 
-    def _get_lr(self, t: int) -> float:
+    def _get_lr(self, t: int) -> List[float]:
         assert False, 'should not be called as step is overridden'

timm/scheduler/poly_lr.py

@@ -6,6 +6,7 @@
 """
 import math
 import logging
+from typing import List
 
 import torch
 
@@ -73,7 +74,7 @@ def __init__(
         else:
             self.warmup_steps = [1 for _ in self.base_values]
 
-    def _get_lr(self, t):
+    def _get_lr(self, t: int) -> List[float]:
         if t < self.warmup_t:
             lrs = [self.warmup_lr_init + t * s for s in self.warmup_steps]
         else:

timm/scheduler/scheduler.py

@@ -1,6 +1,6 @@
 import abc
 from abc import ABC
-from typing import Any, Dict, Optional
+from typing import Any, Dict, List, Optional
 
 import torch
 
@@ -65,10 +65,10 @@ def load_state_dict(self, state_dict: Dict[str, Any]) -> None:
         self.__dict__.update(state_dict)
 
     @abc.abstractmethod
-    def _get_lr(self, t: int) -> float:
+    def _get_lr(self, t: int) -> List[float]:
         pass
 
-    def _get_values(self, t: int, on_epoch: bool = True) -> Optional[float]:
+    def _get_values(self, t: int, on_epoch: bool = True) -> Optional[List[float]]:
         proceed = (on_epoch and self.t_in_epochs) or (not on_epoch and not self.t_in_epochs)
         if not proceed:
             return None

timm/scheduler/step_lr.py

@@ -6,6 +6,8 @@
 """
 import math
 import torch
+from typing import List
+
 
 from .scheduler import Scheduler
 
@@ -51,7 +53,7 @@ def __init__(
         else:
             self.warmup_steps = [1 for _ in self.base_values]
 
-    def _get_lr(self, t):
+    def _get_lr(self, t: int) -> List[float]:
         if t < self.warmup_t:
             lrs = [self.warmup_lr_init + t * s for s in self.warmup_steps]
         else:

timm/scheduler/tanh_lr.py

@@ -8,6 +8,7 @@
 import math
 import numpy as np
 import torch
+from typing import List
 
 from .scheduler import Scheduler
 
@@ -75,7 +76,7 @@ def __init__(
         else:
             self.warmup_steps = [1 for _ in self.base_values]
 
-    def _get_lr(self, t):
+    def _get_lr(self, t: int) -> List[float]:
         if t < self.warmup_t:
             lrs = [self.warmup_lr_init + t * s for s in self.warmup_steps]
         else: