auto updates (#5438)

Signed-off-by: monai-bot <monai.miccai2019@gmail.com>

fixes #5444

Signed-off-by: monai-bot <monai.miccai2019@gmail.com>
Signed-off-by: Wenqi Li <wenqil@nvidia.com>
Co-authored-by: Wenqi Li <wenqil@nvidia.com>
Co-authored-by: Wenqi Li <831580+wyli@users.noreply.github.com>

Author: monai-bot

monai/data/meta_tensor.py

@@ -321,7 +321,7 @@ def as_tensor(self) -> torch.Tensor:
         Return the `MetaTensor` as a `torch.Tensor`.
         It is OS dependent as to whether this will be a deep copy or not.
         """
-        return self.as_subclass(torch.Tensor)  # type: ignore
+        return self.as_subclass(torch.Tensor)
 
     def get_array(self, output_type=np.ndarray, dtype=None, device=None, *_args, **_kwargs):
         """

monai/metrics/cumulative_average.py

@@ -10,11 +10,12 @@
 # limitations under the License.
 
 import warnings
-from typing import Any, Optional, Union
+from typing import Any, Optional
 
 import torch
 import torch.distributed as dist
-from numpy.typing import NDArray
+
+from monai.config import NdarrayOrTensor
 
 
 class CumulativeAverage:
@@ -52,7 +53,7 @@ def reset(self) -> None:
         self.count = torch.tensor(0, dtype=torch.float)
         self.is_distributed = dist.is_available() and dist.is_initialized()
 
-    def get_current(self, to_numpy: bool = True) -> Union[NDArray, torch.Tensor]:
+    def get_current(self, to_numpy: bool = True) -> NdarrayOrTensor:
         """
         returns the most recent value (averaged across processes)
 
@@ -74,7 +75,7 @@ def get_current(self, to_numpy: bool = True) -> Union[NDArray, torch.Tensor]:
 
         return val
 
-    def aggregate(self, to_numpy: bool = True) -> Union[NDArray, torch.Tensor]:
+    def aggregate(self, to_numpy: bool = True) -> NdarrayOrTensor:
         """
         returns the total average value (averaged across processes)
 

tests/test_nifti_rw.py

@@ -181,8 +181,8 @@ def test_write_3d(self):
                 writer_obj.set_metadata({"affine": np.diag([1, 1, 1, 1]), "original_affine": np.diag([1.4, 1, 1, 1])})
                 writer_obj.write(image_name, verbose=True)
                 out = nib.load(image_name)
-                np.testing.assert_allclose(out.get_fdata(), [[[0, 1, 2], [3, 4, 5]]])
-                np.testing.assert_allclose(out.affine, np.diag([1.4, 1, 1, 1]))
+                np.testing.assert_allclose(out.get_fdata(), [[[0, 1, 2], [3, 4, 5]]], atol=1e-4, rtol=1e-4)
+                np.testing.assert_allclose(out.affine, np.diag([1.4, 1, 1, 1]), atol=1e-4, rtol=1e-4)
 
                 image_name = os.path.join(out_dir, "test1.nii.gz")
                 img = p(np.arange(5).reshape((1, 1, 5)))
@@ -205,8 +205,8 @@ def test_write_4d(self):
                 writer_obj.set_metadata({"affine": np.diag([1.4, 1, 1, 1]), "original_affine": np.diag([1, 1.4, 1, 1])})
                 writer_obj.write(image_name, verbose=True)
                 out = nib.load(image_name)
-                np.testing.assert_allclose(out.get_fdata(), [[[[0, 1], [2, 3], [4, 5]]]])
-                np.testing.assert_allclose(out.affine, np.diag([1, 1.4, 1, 1]))
+                np.testing.assert_allclose(out.get_fdata(), [[[[0, 1], [2, 3], [4, 5]]]], atol=1e-4, rtol=1e-4)
+                np.testing.assert_allclose(out.affine, np.diag([1, 1.4, 1, 1]), atol=1e-4, rtol=1e-4)
 
                 image_name = os.path.join(out_dir, "test1.nii.gz")
                 img = p(np.arange(5).reshape((1, 1, 5, 1)))
@@ -232,8 +232,10 @@ def test_write_5d(self):
                 np.testing.assert_allclose(
                     out.get_fdata(),
                     np.array([[[[[0.0, 1.0], [2.0, 3.0]], [[4.0, 5.0], [6.0, 7.0]], [[8.0, 9.0], [10.0, 11.0]]]]]),
+                    atol=1e-4,
+                    rtol=1e-4,
                 )
-                np.testing.assert_allclose(out.affine, np.diag([1.4, 1, 1, 1]))
+                np.testing.assert_allclose(out.affine, np.diag([1.4, 1, 1, 1]), atol=1e-4, rtol=1e-4)
 
                 image_name = os.path.join(out_dir, "test1.nii.gz")
                 img = p(np.arange(10).reshape((1, 1, 5, 1, 2)))

tests/test_to_tensord.py

@@ -20,7 +20,6 @@
 
 cp, _ = optional_import("cupy")
 
-
 im = [[1, 2], [3, 4]]
 
 TESTS = [(im, (2, 2))]