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fix SegResNetVAE docstring to match args #2113

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wyli merged 1 commit into from
Apr 29, 2021
Merged

fix SegResNetVAE docstring to match args #2113

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15 changes: 6 additions & 9 deletions monai/networks/nets/segresnet.py
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Expand Up @@ -181,6 +181,12 @@ class SegResNetVAE(SegResNet):
The model supports 2D or 3D inputs.

Args:
input_image_size: the size of images to input into the network. It is used to
determine the in_features of the fc layer in VAE.
vae_estimate_std: whether to estimate the standard deviations in VAE. Defaults to ``False``.
vae_default_std: if not to estimate the std, use the default value. Defaults to 0.3.
vae_nz: number of latent variables in VAE. Defaults to 256.
Where, 128 to represent mean, and 128 to represent std.
spatial_dims: spatial dimension of the input data. Defaults to 3.
init_filters: number of output channels for initial convolution layer. Defaults to 8.
in_channels: number of input channels for the network. Defaults to 1.
Expand All @@ -199,15 +205,6 @@ class SegResNetVAE(SegResNet):
- ``deconv``, uses transposed convolution layers.
- ``nontrainable``, uses non-trainable `linear` interpolation.
- ``pixelshuffle``, uses :py:class:`monai.networks.blocks.SubpixelUpsample`.

use_vae: if use the variational autoencoder (VAE) during training. Defaults to ``False``.
input_image_size: the size of images to input into the network. It is used to
determine the in_features of the fc layer in VAE. When ``use_vae == True``, please
ensure that this parameter is set. Defaults to ``None``.
vae_estimate_std: whether to estimate the standard deviations in VAE. Defaults to ``False``.
vae_default_std: if not to estimate the std, use the default value. Defaults to 0.3.
vae_nz: number of latent variables in VAE. Defaults to 256.
Where, 128 to represent mean, and 128 to represent std.
"""

def __init__(
Expand Down