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Fix constructors for DenseNet derived classes #5846

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merged 5 commits into from
Jan 14, 2023
Merged

Fix constructors for DenseNet derived classes #5846

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b7427d2
Fix constructors for DenseNet derived classes
pzaffino Jan 12, 2023
978c167
Apply suggestions from code review
wyli Jan 14, 2023
ad88bd8
Merge branch 'dev' into dev
wyli Jan 14, 2023
d02335d
[MONAI] code formatting
monai-bot Jan 14, 2023
d8dd09f
Merge branch 'dev' into dev
wyli Jan 14, 2023
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58 changes: 51 additions & 7 deletions monai/networks/nets/densenet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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."
Expand All @@ -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."
Expand All @@ -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."
Expand All @@ -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.")

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