fix Project-MONAI#7940

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>

monai/apps/auto3dseg/hpo_gen.py

@@ -53,7 +53,7 @@ def update_params(self, *args, **kwargs):
         raise NotImplementedError
 
     @abstractmethod
-    def set_score(self):
+    def set_score(self, *args, **kwargs):
         """Report the evaluated results to HPO."""
         raise NotImplementedError
 

monai/data/meta_tensor.py

@@ -505,7 +505,7 @@ def peek_pending_rank(self):
         a = self.pending_operations[-1].get(LazyAttr.AFFINE, None) if self.pending_operations else self.affine
         return 1 if a is None else int(max(1, len(a) - 1))
 
-    def new_empty(self, size, dtype=None, device=None, requires_grad=False):
+    def new_empty(self, size, dtype=None, device=None, requires_grad=False):  # type: ignore[override]
         """
         must be defined for deepcopy to work
 
@@ -580,7 +580,7 @@ def ensure_torch_and_prune_meta(
             img.affine = MetaTensor.get_default_affine()
         return img
 
-    def __repr__(self):
+    def __repr__(self, *, Any = ...):
         """
         Prints a representation of the tensor.
         Prepends "meta" to ``torch.Tensor.__repr__``.

monai/networks/layers/simplelayers.py

@@ -452,7 +452,7 @@ def get_binary_kernel(window_size: Sequence[int], dtype=torch.float, device=None
 
 def median_filter(
     in_tensor: torch.Tensor,
-    kernel_size: Sequence[int] = (3, 3, 3),
+    kernel_size: Sequence[int] | int = (3, 3, 3),
     spatial_dims: int = 3,
     kernel: torch.Tensor | None = None,
     **kwargs,

monai/networks/nets/quicknat.py

@@ -42,7 +42,7 @@ class SkipConnectionWithIdx(SkipConnection):
     Inherits from SkipConnection but provides the indizes with each forward pass.
     """
 
-    def forward(self, input, indices):
+    def forward(self, input, indices):  # type: ignore[override]
         return super().forward(input), indices
 
 
@@ -57,7 +57,7 @@ class SequentialWithIdx(nn.Sequential):
     def __init__(self, *args):
         super().__init__(*args)
 
-    def forward(self, input, indices):
+    def forward(self, input, indices):  # type: ignore[override]
         for module in self:
             input, indices = module(input, indices)
         return input, indices
@@ -165,7 +165,7 @@ def _get_layer(self, in_channels, out_channels, dilation):
         )
         return nn.Sequential(conv.get_submodule("adn"), conv.get_submodule("conv"))
 
-    def forward(self, input, _):
+    def forward(self, input, _):  # type: ignore[override]
         i = 0
         result = input
         result1 = input  # this will not stay this value, needed here for pylint/mypy
@@ -215,7 +215,7 @@ def __init__(self, in_channels: int, max_pool, se_layer, dropout, kernel_size, n
         super().__init__(in_channels, se_layer, dropout, kernel_size, num_filters)
         self.max_pool = max_pool
 
-    def forward(self, input, indices=None):
+    def forward(self, input, indices=None):  # type: ignore[override]
         input, indices = self.max_pool(input)
 
         out_block, _ = super().forward(input, None)
@@ -243,7 +243,7 @@ def __init__(self, in_channels: int, un_pool, se_layer, dropout, kernel_size, nu
         super().__init__(in_channels, se_layer, dropout, kernel_size, num_filters)
         self.un_pool = un_pool
 
-    def forward(self, input, indices):
+    def forward(self, input, indices):  # type: ignore[override]
         out_block, _ = super().forward(input, None)
         out_block = self.un_pool(out_block, indices)
         return out_block, None
@@ -270,7 +270,7 @@ def __init__(self, in_channels: int, se_layer, dropout, max_pool, un_pool, kerne
         self.max_pool = max_pool
         self.un_pool = un_pool
 
-    def forward(self, input, indices):
+    def forward(self, input, indices):  # type: ignore[override]
         out_block, indices = self.max_pool(input)
         out_block, _ = super().forward(out_block, None)
         out_block = self.un_pool(out_block, indices)

monai/transforms/croppad/array.py

@@ -459,10 +459,10 @@ class SpatialCrop(Crop):
 
     def __init__(
         self,
-        roi_center: Sequence[int] | NdarrayOrTensor | None = None,
-        roi_size: Sequence[int] | NdarrayOrTensor | None = None,
-        roi_start: Sequence[int] | NdarrayOrTensor | None = None,
-        roi_end: Sequence[int] | NdarrayOrTensor | None = None,
+        roi_center: Sequence[int] | int | NdarrayOrTensor | None = None,
+        roi_size: Sequence[int] | int | NdarrayOrTensor | None = None,
+        roi_start: Sequence[int] | int | NdarrayOrTensor | None = None,
+        roi_end: Sequence[int] | int | NdarrayOrTensor | None = None,
         roi_slices: Sequence[slice] | None = None,
         lazy: bool = False,
     ) -> None:

monai/transforms/croppad/dictionary.py

@@ -438,10 +438,10 @@ class SpatialCropd(Cropd):
     def __init__(
         self,
         keys: KeysCollection,
-        roi_center: Sequence[int] | None = None,
-        roi_size: Sequence[int] | None = None,
-        roi_start: Sequence[int] | None = None,
-        roi_end: Sequence[int] | None = None,
+        roi_center: Sequence[int] | int | None = None,
+        roi_size: Sequence[int] | int | None = None,
+        roi_start: Sequence[int] | int | None = None,
+        roi_end: Sequence[int] | int | None = None,
         roi_slices: Sequence[slice] | None = None,
         allow_missing_keys: bool = False,
         lazy: bool = False,

monai/visualize/class_activation_maps.py

@@ -214,7 +214,7 @@ def _upsample_and_post_process(self, acti_map, x):
         acti_map = self.upsampler(img_spatial)(acti_map)
         return self.postprocessing(acti_map)
 
-    def __call__(self):
+    def __call__(self, **kwargs):
         raise NotImplementedError()
 
 

tests/test_subpixel_upsample.py

@@ -55,9 +55,9 @@
     (2, 1, 32, 16, 8),
 ]
 
-TEST_CASE_SUBPIXEL.append(TEST_CASE_SUBPIXEL_2D_EXTRA)
-TEST_CASE_SUBPIXEL.append(TEST_CASE_SUBPIXEL_3D_EXTRA)
-TEST_CASE_SUBPIXEL.append(TEST_CASE_SUBPIXEL_CONV_BLOCK_EXTRA)
+TEST_CASE_SUBPIXEL.append(TEST_CASE_SUBPIXEL_2D_EXTRA)  # type: ignore
+TEST_CASE_SUBPIXEL.append(TEST_CASE_SUBPIXEL_3D_EXTRA)  # type: ignore
+TEST_CASE_SUBPIXEL.append(TEST_CASE_SUBPIXEL_CONV_BLOCK_EXTRA)  # type: ignore
 
 # add every test back with the pad/pool sequential component omitted
 for tests in list(TEST_CASE_SUBPIXEL):