- added a few __all__'s

inferno/extensions/containers/graph.py

@@ -12,6 +12,9 @@
 from ...utils.exceptions import assert_
 
 
+__all__ = ['NNGraph', 'Graph']
+
+
 class NNGraph(nx.DiGraph):
     """A NetworkX DiGraph, except that node and edge ordering matters."""
     # We don't copy torch tensors, only to have them deleted.

inferno/extensions/containers/sequential.py

@@ -2,6 +2,9 @@
 from ...utils import python_utils as pyu
 
 
+__all__ = ['Sequential1', 'Sequential2']
+
+
 class Sequential1(nn.Sequential):
     """Like torch.nn.Sequential, but with a few extra methods."""
     def __len__(self):

inferno/extensions/criteria/core.py

@@ -3,6 +3,9 @@
 from ...utils.exceptions import assert_, ShapeError, NotTorchModuleError
 
 
+__all__ = ['Criteria', 'As2DCriterion']
+
+
 class Criteria(nn.Module):
     """Aggregate multiple criteria to one."""
     def __init__(self, *criteria):

inferno/extensions/criteria/set_similarity_measures.py

@@ -3,6 +3,9 @@
 from torch.autograd import Variable
 
 
+__all__ = ['SorensenDiceLoss']
+
+
 class SorensenDiceLoss(nn.Module):
     """
     Computes a loss scalar, which when minimized maximizes the Sorensen-Dice similarity

inferno/extensions/initializers/base.py

@@ -1,6 +1,13 @@
 import torch.nn.init as init
 
 
+__all__ = ['Initializer',
+           'Initialization',
+           'WeightInitFunction',
+           'BiasInitFunction',
+           'TensorInitFunction']
+
+
 class Initializer(object):
     """
     Base class for all initializers.

inferno/extensions/initializers/presets.py

@@ -5,6 +5,9 @@
 from .base import Initialization, Initializer
 
 
+__all__ = ['Constant', 'OrthogonalWeightsZeroBias', 'KaimingNormalWeightsZeroBias']
+
+
 class Constant(Initializer):
     """Initialize with a constant."""
     def __init__(self, constant):

inferno/extensions/layers/activations.py

@@ -2,6 +2,8 @@
 import torch.nn as nn
 from ...utils.torch_utils import where
 
+__all__ = ['SELU']
+
 
 class SELU(nn.Module):
     def forward(self, input):

inferno/extensions/layers/convolutional.py

@@ -3,6 +3,16 @@
 from ..initializers import Initializer
 
 
+__all__ = ['ConvActivation',
+           'ConvELU2D', 'ConvELU3D',
+           'ConvSigmoid2D', 'ConvSigmoid3D',
+           'DeconvELU2D', 'DeconvELU3D',
+           'StridedConvELU2D', 'StridedConvELU3D',
+           'DilatedConvELU2D', 'DilatedConvELU3D',
+           'Conv2D', 'Conv3D',
+           'BNReLUConv2D']
+
+
 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/device.py

@@ -2,6 +2,8 @@
 from ...utils.python_utils import from_iterable
 from ...utils.exceptions import assert_, DeviceError
 
+__all__ = ['DeviceTransfer']
+
 
 class DeviceTransfer(nn.Module):
     """Layer to transfer variables to a specified device."""

inferno/extensions/layers/reshape.py

@@ -5,6 +5,13 @@
 from ...utils import python_utils as pyu
 
 
+__all__ = ['View', 'AsMatrix', 'Flatten',
+           'As3D', 'As2D',
+           'Concatenate', 'Cat',
+           'ResizeAndConcatenate', 'PoolCat',
+           'Sum', 'Split']
+
+
 class View(nn.Module):
     def __init__(self, as_shape):
         super(View, self).__init__()