Add docs

prototorch/modules/prototypes.py

@@ -25,40 +25,9 @@ class _Prototypes(torch.nn.Module):
 
 
 class Prototypes1D(_Prototypes):
-    r"""Create a learnable set of one-dimensional prototypes.
+    """Create a learnable set of one-dimensional prototypes.
 
-    TODO Complete this doc-string
-
-    Kwargs:
-        prototypes_per_class: number of prototypes to use per class.
-            Default: ``1``
-        prototype_initializer: prototype initializer.
-            Default: ``'ones'``
-        prototype_distribution: prototype distribution vector.
-            Default: ``None``
-        input_dim: dimension of the incoming data.
-        nclasses: number of classes.
-        data: If set to ``None``, data-dependent initializers will be ignored.
-            Default: ``None``
-
-    Shape:
-        - Input: :math:`(N, H_{in})`
-            where :math:`H_{in} = \text{input_dim}`.
-        - Output: :math:`(N, H_{out})`
-            where :math:`H_{out} = \text{total_prototypes}`.
-
-    Attributes:
-        prototypes: the learnable weights of the module of shape
-            :math:`(\text{total_prototypes}, \text{prototype_dimension})`.
-        prototype_labels: the non-learnable labels of the prototypes.
-
-    Examples:
-
-        >>> p = Prototypes1D(input_dim=20, nclasses=10)
-        >>> input = torch.randn(128, 20)
-        >>> output = m(input)
-        >>> print(output.size())
-        torch.Size([20, 10])
+    TODO Complete this doc-string.
     """
     def __init__(self,
                  prototypes_per_class=1,