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More cosmetic changes

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This commit is contained in:
blackfly 2020-04-11 18:12:37 +02:00
parent f80d9648c3
commit 4158586cb9
4 changed files with 17 additions and 18 deletions
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8
prototorch/functions/activations.py
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@ -8,9 +8,10 @@ ACTIVATIONS = dict()
# def register_activation(scriptf): # def register_activation(scriptf):
# ACTIVATIONS[scriptf.name] = scriptf # ACTIVATIONS[scriptf.name] = scriptf
# return scriptf # return scriptf
def register_activation(f): def register_activation(function):
ACTIVATIONS[f.__name__] = f """Add the activation function to the registry."""
return f ACTIVATIONS[function.__name__] = function
return function
@register_activation @register_activation
@ -55,6 +56,7 @@ def swish_beta(x, beta=torch.tensor([10])):
def get_activation(funcname): def get_activation(funcname):
"""Deserialize the activation function."""
if callable(funcname): if callable(funcname):
return funcname return funcname
if funcname in ACTIVATIONS: if funcname in ACTIVATIONS:

15
prototorch/functions/distances.py
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@ -4,8 +4,7 @@ import torch
def squared_euclidean_distance(x, y): def squared_euclidean_distance(x, y):
""" """Compute the squared Euclidean distance between :math:`x` and :math:`y`.
Compute the squared Euclidean distance between :math:`x` and :math:`y`.
Expected dimension of x is 2. Expected dimension of x is 2.
Expected dimension of y is 2. Expected dimension of y is 2.
@ -18,8 +17,7 @@ def squared_euclidean_distance(x, y):
def euclidean_distance(x, y): def euclidean_distance(x, y):
""" """Compute the Euclidean distance between :math:`x` and :math:`y`.
Compute the Euclidean distance between :math:`x` and :math:`y`.
Expected dimension of x is 2. Expected dimension of x is 2.
Expected dimension of y is 2. Expected dimension of y is 2.
@ -30,8 +28,7 @@ def euclidean_distance(x, y):
def lpnorm_distance(x, y, p): def lpnorm_distance(x, y, p):
r""" r"""Compute :math:`{\langle x, y \rangle}_p`.
Compute :math:`{\langle x, y \rangle}_p`.
Expected dimension of x is 2. Expected dimension of x is 2.
Expected dimension of y is 2. Expected dimension of y is 2.
@ -41,8 +38,7 @@ def lpnorm_distance(x, y, p):
def omega_distance(x, y, omega): def omega_distance(x, y, omega):
r""" r"""Omega distance.
Omega distance.
Compute :math:`{\langle \Omega x, \Omega y \rangle}_p` Compute :math:`{\langle \Omega x, \Omega y \rangle}_p`
@ -57,8 +53,7 @@ def omega_distance(x, y, omega):
def lomega_distance(x, y, omegas): def lomega_distance(x, y, omegas):
r""" r"""Localized Omega distance.
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`

8
prototorch/functions/initializers.py
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@ -7,9 +7,10 @@ import torch
INITIALIZERS = dict() INITIALIZERS = dict()
def register_initializer(func): def register_initializer(function):
INITIALIZERS[func.__name__] = func """Add the initializer to the registry."""
return func INITIALIZERS[function.__name__] = function
return function
def labels_from(distribution): def labels_from(distribution):
@ -84,6 +85,7 @@ def stratified_random(x_train, y_train, prototype_distribution):
def get_initializer(funcname): def get_initializer(funcname):
"""Deserialize the initializer."""
if callable(funcname): if callable(funcname):
return funcname return funcname
if funcname in INITIALIZERS: if funcname in INITIALIZERS: