remove apply same flag from test and remove redundant test, fix type annotations

Signed-off-by: Fabian Klopfer <[email protected]>

Author: SomeUserName1

monai/transforms/utility/dictionary.py

@@ -1478,7 +1478,7 @@ def __init__(self, keys: KeysCollection, name: str, allow_missing_keys: bool = F
 
         self.trans = TorchIO(name, *args, **kwargs)
 
-    def __call__(self, data: Mapping[NdarrayOrTensor]) -> dict[NdarrayOrTensor]:
+    def __call__(self, data: Mapping[Hashable, NdarrayOrTensor]) -> dict[Hashable, NdarrayOrTensor]:
         return self.trans(dict(data))
 
 
@@ -1508,7 +1508,7 @@ def __init__(self, keys: KeysCollection, name: str, allow_missing_keys: bool = F
 
         self.trans = TorchIO(name, *args, **kwargs)
 
-    def __call__(self, data: Mapping[NdarrayOrTensor]) -> dict[NdarrayOrTensor]:
+    def __call__(self, data: Mapping[Hashable, NdarrayOrTensor]) -> dict[Hashable, NdarrayOrTensor]:
         return self.trans(dict(data))
 
 

tests/test_torchiod.py

@@ -14,7 +14,6 @@
 import unittest
 from unittest import skipUnless
 
-import numpy as np
 import torch
 from parameterized import parameterized
 
@@ -33,13 +32,7 @@
         ((TEST_TENSOR - TEST_TENSOR.min()) / (TEST_TENSOR.max() - TEST_TENSOR.min())) * 42,
     ]
 ]
-TEST2 = [
-    [
-        {"keys": ["img1", "img2"], "name": "RandomAffine", "apply_same_transform": True},
-        {"img1": TEST_TENSOR, "img2": TEST_TENSOR},
-    ]
-]
-TEST3 = [[{"keys": ["img1", "img2"], "name": "RandomAffine"}, {"img1": TEST_TENSOR, "img2": TEST_TENSOR}]]
+TEST2 = [[{"keys": ["img1", "img2"], "name": "RandomAffine"}, {"img1": TEST_TENSOR, "img2": TEST_TENSOR}]]
 
 
 @skipUnless(has_torchio, "Requires torchio")
@@ -52,18 +45,11 @@ def test_value(self, input_param, input_data, expected_value):
         assert_allclose(result["img"], expected_value, atol=1e-4, rtol=1e-4, type_test=False)
 
     @parameterized.expand(TEST2)
-    def test_common_random_transform(self, input_param, input_data):
+    def test_random_transform(self, input_param, input_data):
         set_determinism(seed=0)
         result = TorchIOd(**input_param)(input_data)
         assert_allclose(result["img1"], result["img2"], atol=1e-4, rtol=1e-4, type_test=False)
 
-    @parameterized.expand(TEST3)
-    def test_different_random_transform(self, input_param, input_data):
-        set_determinism(seed=0)
-        result = TorchIOd(**input_param)(input_data)
-        equal = np.allclose(result["img1"], result["img2"], atol=1e-4, rtol=1e-4)
-        self.assertFalse(equal)
-
 
 if __name__ == "__main__":
     unittest.main()