Merge pull request #144 from inferno-pytorch/model_zoo

Implement model zoo

inferno/extensions/layers/__init__.py

@@ -3,29 +3,23 @@
 from .convolutional import *
 from .device import *
 from .reshape import *
-from .unet_base import *
-from .res_unet import *
-from .building_blocks import *
+from .convolutional_blocks import *
 
 #######################################################
-# the following is to make the sphinx example 
+# the following is to make the sphinx example
 # gallery makes proper cross-references
 from .activations       import _all as _activations_all
 from .convolutional     import _all as _convolutional_all
 from .device            import _all as _device_all
 from .reshape           import _all as _reshape_all
-from .unet_base         import _all as _unet_base_all
-from .res_unet          import _all as _res_unet_all
-from .building_blocks   import _all as _building_blocks_all
+from .convolutional_blocks   import _all as _convolutional_blocks_all
 from .identity          import _all as _identity_all
 
 __all__.extend(_activations_all)
 __all__.extend(_convolutional_all)
 __all__.extend(_device_all)
 __all__.extend(_reshape_all)
-__all__.extend(_unet_base_all)
-__all__.extend(_res_unet_all)
-__all__.extend(_building_blocks_all)
+__all__.extend(_convolutional_blocks_all)
 __all__.extend(_identity_all)
 
 _all = __all__

inferno/extensions/layers/convolutional.py

@@ -19,6 +19,7 @@
            'ConvReLU2D', 'ConvReLU3D']
 _all = __all__
 
+
 class ConvActivation(nn.Module):
     """Convolutional layer with 'SAME' padding followed by an activation."""
     def __init__(self, in_channels, out_channels, kernel_size, dim, activation,

inferno/extensions/layers/prefab.py → inferno/extensions/layers/convolutional_blocks.py

@@ -1,8 +1,11 @@
-from .convolutional import BNReLUConv2D, BNReLUDeconv2D, Conv2D, Deconv2D
 import torch.nn as nn
+from .convolutional import BNReLUConv2D, BNReLUDeconv2D, Conv2D, Deconv2D
 from ...utils import python_utils as pyu
 from ...utils.exceptions import assert_
 
+__all__ = ['ResidualBlock', 'PreActSimpleResidualBlock']
+_all = __all__
+
 
 class ResidualBlock(nn.Module):
     def __init__(self, layers, resample=None):