Type hint for python version lower than 3.9

3 files changed, 12 insertions, 12 deletions

diff --git a/utils/configuration.py b/utils/configuration.py
index aa04b32..455abe8 100644
--- a/utils/configuration.py
+++ b/utils/configuration.py
@@ -1,4 +1,4 @@
-from typing import TypedDict, Optional, Union, Tuple
+from typing import TypedDict, Optional, Union, Tuple, Dict
 
 from utils.dataset import ClipClasses, ClipConditions, ClipViews
 
@@ -15,7 +15,7 @@ class DatasetConfiguration(TypedDict):
     train_size: int
     num_sampled_frames: int
     discard_threshold: int
-    selector: Optional[dict[str, Union[ClipClasses, ClipConditions, ClipViews]]]
+    selector: Optional[Dict[str, Union[ClipClasses, ClipConditions, ClipViews]]]
     num_input_channels: int
     frame_size: Tuple[int, int]
     cache_on: bool
diff --git a/utils/dataset.py b/utils/dataset.py
index 0a33693..e691157 100644
--- a/utils/dataset.py
+++ b/utils/dataset.py
@@ -1,7 +1,7 @@
 import os
 import random
 import re
-from typing import Optional, NewType, Union, List, Tuple
+from typing import Optional, NewType, Union, List, Tuple, Set, Dict
 
 import numpy as np
 import torch
@@ -11,9 +11,9 @@ from sklearn.preprocessing import LabelEncoder
 from torch.utils import data
 from tqdm import tqdm
 
-ClipClasses = NewType('ClipClasses', set[str])
-ClipConditions = NewType('ClipConditions', set[str])
-ClipViews = NewType('ClipViews', set[str])
+ClipClasses = NewType('ClipClasses', Set[str])
+ClipConditions = NewType('ClipConditions', Set[str])
+ClipViews = NewType('ClipViews', Set[str])
 
 
 class CASIAB(data.Dataset):
@@ -26,7 +26,7 @@ class CASIAB(data.Dataset):
             train_size: int = 74,
             num_sampled_frames: int = 30,
             discard_threshold: int = 15,
-            selector: Optional[dict[
+            selector: Optional[Dict[
                 str, Union[ClipClasses, ClipConditions, ClipViews]
             ]] = None,
             num_input_channels: int = 3,
@@ -75,12 +75,12 @@ class CASIAB(data.Dataset):
         self.views: np.ndarray[np.str_]
         # Labels, classes, conditions and views in dataset,
         #   set of three attributes above
-        self.metadata = dict[str, List[np.int64, str]]
+        self.metadata = Dict[str, List[np.int64, str]]
 
         # Dictionaries for indexing frames and frame names by clip name
         # and chip path when cache is on
-        self._cached_clips_frame_names: Optional[dict[str, List[str]]] = None
-        self._cached_clips: Optional[dict[str, torch.Tensor]] = None
+        self._cached_clips_frame_names: Optional[Dict[str, List[str]]] = None
+        self._cached_clips: Optional[Dict[str, torch.Tensor]] = None
 
         # Video clip directory names
         self._clip_names: List[str] = []
@@ -170,7 +170,7 @@ class CASIAB(data.Dataset):
     def __getitem__(
             self,
             index: int
-    ) -> dict[str, Union[np.int64, str, torch.Tensor]]:
+    ) -> Dict[str, Union[np.int64, str, torch.Tensor]]:
         label = self.labels[index]
         condition = self.conditions[index]
         view = self.views[index]
diff --git a/utils/sampler.py b/utils/sampler.py
index 734acf9..c1bf3dd 100644
--- a/utils/sampler.py
+++ b/utils/sampler.py
@@ -1,5 +1,5 @@
 import random
-from collections.abc import Iterator
+from collections import Iterator
 from typing import Union, Tuple
 
 import numpy as np