Minor cosmetic changes

RELEASE.md

@@ -3,8 +3,8 @@
 ## Release 0.1.1-dev0
 
 ### Includes
-  - Bugfixes.
-  - 100% test coverage.
+-  Minor bugfixes.
+-  100% line coverage.
 
 ## Release 0.1.0-dev0
 

prototorch/functions/activations.py

@@ -16,18 +16,24 @@ def register_activation(f):
 @register_activation
 # @torch.jit.script
 def identity(x, beta=torch.tensor([0])):
-    """:math:`f(x) = x`."""
+    """Identity activation function.
+
+    Definition:
+    :math:`f(x) = x`
+    """
     return x
 
 
 @register_activation
 # @torch.jit.script
 def sigmoid_beta(x, beta=torch.tensor([10])):
-    r""":math:`f(x) = \\frac{1}{1 + e^{-\\beta x}}`.
+    r"""Sigmoid activation function with scaling.
+
+    Definition:
+    :math:`f(x) = \frac{1}{1 + e^{-\beta x}}`
 
     Keyword Arguments:
-    __________________
-        beta (float): Parameter :math:`\\beta`
+        beta (`torch.tensor`): Scaling parameter :math:`\beta`
     """
     out = torch.reciprocal(1.0 + torch.exp(-int(beta.item()) * x))
     return out
@@ -36,11 +42,13 @@ def sigmoid_beta(x, beta=torch.tensor([10])):
 @register_activation
 # @torch.jit.script
 def swish_beta(x, beta=torch.tensor([10])):
-    r""":math:`f(x) = \\frac{x}{1 + e^{-\\beta x}}`.
+    r"""Swish activation function with scaling.
+
+    Definition:
+    :math:`f(x) = \frac{x}{1 + e^{-\beta x}}`
 
     Keyword Arguments:
-    __________________
-        beta (float): Parameter :math:`\\beta`
+        beta (`torch.tensor`): Scaling parameter :math:`\beta`
     """
     out = x * sigmoid_beta(x, beta=beta)
     return out
@@ -49,8 +57,6 @@ def swish_beta(x, beta=torch.tensor([10])):
 def get_activation(funcname):
     if callable(funcname):
         return funcname
-    else:
     if funcname in ACTIVATIONS:
         return ACTIVATIONS.get(funcname)
-        else:
     raise NameError(f'Activation {funcname} was not found.')

prototorch/functions/distances.py

@@ -30,8 +30,8 @@ def euclidean_distance(x, y):
 
 
 def lpnorm_distance(x, y, p):
-    """
-    Compute :math:`{\\langle x, y \\rangle}_p`.
+    r"""
+    Compute :math:`{\langle x, y \rangle}_p`.
 
     Expected dimension of x is 2.
     Expected dimension of y is 2.
@@ -41,10 +41,10 @@ def lpnorm_distance(x, y, p):
 
 
 def omega_distance(x, y, omega):
-    """
+    r"""
     Omega distance.
 
-    Compute :math:`{\\langle \\Omega x, \\Omega y \\rangle}_p`
+    Compute :math:`{\langle \Omega x, \Omega y \rangle}_p`
 
     Expected dimension of x is 2.
     Expected dimension of y is 2.
@@ -57,10 +57,10 @@ def omega_distance(x, y, omega):
 
 
 def lomega_distance(x, y, omegas):
-    """
+    r"""
     Localized Omega distance.
 
-    Compute :math:`{\\langle \\Omega_k x, \\Omega_k y_k \\rangle}_p`
+    Compute :math:`{\langle \Omega_k x, \Omega_k y_k \rangle}_p`
 
     Expected dimension of x is 2.
     Expected dimension of y is 2.

prototorch/functions/initializers.py

@@ -86,8 +86,6 @@ def stratified_random(x_train, y_train, prototype_distribution):
 def get_initializer(funcname):
     if callable(funcname):
         return funcname
-    else:
     if funcname in INITIALIZERS:
         return INITIALIZERS.get(funcname)
-        else:
     raise NameError(f'Initializer {funcname} was not found.')