Merge branch 'dev' into 5852-callable-partial

Project-MONAI · Jan 14, 2023 · 88babdd · 88babdd
2 parents 4093707 + 6cb4ced
commit 88babdd
Showing 1 changed file with 51 additions and 7 deletions.
diff --git a/monai/networks/nets/densenet.py b/monai/networks/nets/densenet.py
@@ -296,16 +296,27 @@ class DenseNet121(DenseNet):
 
     def __init__(
         self,
+        spatial_dims: int,
+        in_channels: int,
+        out_channels: int,
         init_features: int = 64,
         growth_rate: int = 32,
         block_config: Sequence[int] = (6, 12, 24, 16),
         pretrained: bool = False,
         progress: bool = True,
         **kwargs,
     ) -> None:
-        super().__init__(init_features=init_features, growth_rate=growth_rate, block_config=block_config, **kwargs)
+        super().__init__(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            out_channels=out_channels,
+            init_features=init_features,
+            growth_rate=growth_rate,
+            block_config=block_config,
+            **kwargs,
+        )
         if pretrained:
-            if kwargs["spatial_dims"] > 2:
+            if spatial_dims > 2:
                 raise NotImplementedError(
                     "Parameter `spatial_dims` is > 2 ; currently PyTorch Hub does not"
                     "provide pretrained models for more than two spatial dimensions."
@@ -318,16 +329,27 @@ class DenseNet169(DenseNet):
 
     def __init__(
         self,
+        spatial_dims: int,
+        in_channels: int,
+        out_channels: int,
         init_features: int = 64,
         growth_rate: int = 32,
         block_config: Sequence[int] = (6, 12, 32, 32),
         pretrained: bool = False,
         progress: bool = True,
         **kwargs,
     ) -> None:
-        super().__init__(init_features=init_features, growth_rate=growth_rate, block_config=block_config, **kwargs)
+        super().__init__(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            out_channels=out_channels,
+            init_features=init_features,
+            growth_rate=growth_rate,
+            block_config=block_config,
+            **kwargs,
+        )
         if pretrained:
-            if kwargs["spatial_dims"] > 2:
+            if spatial_dims > 2:
                 raise NotImplementedError(
                     "Parameter `spatial_dims` is > 2 ; currently PyTorch Hub does not"
                     "provide pretrained models for more than two spatial dimensions."
@@ -340,16 +362,27 @@ class DenseNet201(DenseNet):
 
     def __init__(
         self,
+        spatial_dims: int,
+        in_channels: int,
+        out_channels: int,
         init_features: int = 64,
         growth_rate: int = 32,
         block_config: Sequence[int] = (6, 12, 48, 32),
         pretrained: bool = False,
         progress: bool = True,
         **kwargs,
     ) -> None:
-        super().__init__(init_features=init_features, growth_rate=growth_rate, block_config=block_config, **kwargs)
+        super().__init__(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            out_channels=out_channels,
+            init_features=init_features,
+            growth_rate=growth_rate,
+            block_config=block_config,
+            **kwargs,
+        )
         if pretrained:
-            if kwargs["spatial_dims"] > 2:
+            if spatial_dims > 2:
                 raise NotImplementedError(
                     "Parameter `spatial_dims` is > 2 ; currently PyTorch Hub does not"
                     "provide pretrained models for more than two spatial dimensions."
@@ -362,14 +395,25 @@ class DenseNet264(DenseNet):
 
     def __init__(
         self,
+        spatial_dims: int,
+        in_channels: int,
+        out_channels: int,
         init_features: int = 64,
         growth_rate: int = 32,
         block_config: Sequence[int] = (6, 12, 64, 48),
         pretrained: bool = False,
         progress: bool = True,
         **kwargs,
     ) -> None:
-        super().__init__(init_features=init_features, growth_rate=growth_rate, block_config=block_config, **kwargs)
+        super().__init__(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            out_channels=out_channels,
+            init_features=init_features,
+            growth_rate=growth_rate,
+            block_config=block_config,
+            **kwargs,
+        )
         if pretrained:
             raise NotImplementedError("Currently PyTorch Hub does not provide densenet264 pretrained models.")