Remove auxillary-VAE

- Keep only VAE models with one encoder and one decoder
- More complex VAE/VED models will be a part of a separate package

atomai/models/__init__.py

@@ -1,7 +1,7 @@
 from .segmentor import Segmentor
 from .imspec import ImSpec
-from .dgm import BaseVAE, VAE, rVAE, jVAE, jrVAE, ssVAE
+from .dgm import BaseVAE, VAE, rVAE, jVAE, jrVAE
 from .loaders import load_model, load_ensemble
 
-__all__ = ["Segmentor", "ImSpec", "BaseVAE", "VAE", "rVAE", "ssVAE",
+__all__ = ["Segmentor", "ImSpec", "BaseVAE", "VAE", "rVAE",
            "jVAE", "jrVAE", "load_model", "load_ensemble"]

atomai/models/dgm/__init__.py

@@ -2,6 +2,5 @@
 from .rvae import rVAE
 from .jvae import jVAE
 from .jrvae import jrVAE
-from .aux_vae import ssVAE
 
-__all__ = ["BaseVAE", "VAE", "rVAE", "jVAE", "jrVAE", "ssVAE"]
+__all__ = ["BaseVAE", "VAE", "rVAE", "jVAE", "jrVAE"]

atomai/nets/__init__.py

@@ -1,11 +1,11 @@
 from .blocks import ConvBlock, DilatedBlock, ResBlock, ResModule, UpsampleBlock
 from .ed import (SignalDecoder, SignalED, SignalEncoder, convDecoderNet,
                  convEncoderNet, coord_latent, fcDecoderNet, fcEncoderNet,
-                 rDecoderNet, init_imspec_model, init_VAE_nets, fcClassifier)
+                 rDecoderNet, init_imspec_model, init_VAE_nets)
 from .fcnn import Unet, dilnet, SegResNet, ResHedNet, init_fcnn_model
 
 __all__ = ['ConvBlock', 'ResBlock', 'ResModule', 'UpsampleBlock', 'DilatedBlock',
            'init_fcnn_model', 'SegResNet', 'Unet', 'ResHedNet', 'dilnet', 'fcEncoderNet',
            'fcDecoderNet',  'convEncoderNet', 'convDecoderNet', 'rDecoderNet',
            'coord_latent', 'load_model', 'load_ensemble', 'init_imspec_model',
-           'init_VAE_nets', 'SignalEncoder', 'SignalDecoder', 'SignalED', 'fcClassifier']
+           'init_VAE_nets', 'SignalEncoder', 'SignalDecoder', 'SignalED']