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Fix docstring formatting for network_type
Signed-off-by: Mohammad Amanour Rahman <[email protected]>
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monai/losses/perceptual.py

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@@ -49,8 +49,7 @@ class PerceptualLoss(nn.Module):
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Args:
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spatial_dims: number of spatial dimensions.
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network_type: str | PercetualNetworkType = PercetualNetworkType.alex,
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One of:
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network_type: type of network for perceptual loss. One of:
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- "alex"
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- "vgg"
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- "squeeze"
@@ -62,15 +61,15 @@ class PerceptualLoss(nn.Module):
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fake_3d_ratio: ratio of how many slices per axis are used in the 2.5D approach.
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cache_dir: path to cache directory to save the pretrained network weights.
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pretrained: whether to load pretrained weights. This argument only works when using networks from
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LIPIS or Torchvision. Defaults to ``"True"``.
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LIPIS or Torchvision. Defaults to ``True``.
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pretrained_path: if `pretrained` is `True`, users can specify a weights file to be loaded
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via using this argument. This argument only works when ``"network_type"`` is "resnet50".
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Defaults to `None`.
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pretrained_state_dict_key: if `pretrained_path` is not `None`, this argument is used to
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extract the expected state dict. This argument only works when ``"network_type"`` is "resnet50".
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Defaults to `None`.
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channel_wise: if True, the loss is returned per channel. Otherwise the loss is averaged over the channels.
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Defaults to ``False``.
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Defaults to ``False``.
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"""
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def __init__(

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