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Documentation for v0.1 version (#199)

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* Adding Equations, solving typos
* improve _code.rst
* the team rst and restuctore index.rst
* fixing errors

---------

Co-authored-by: Dario Coscia <dariocoscia@dhcp-015.eduroam.sissa.it>
This commit is contained in:
Dario Coscia
2023-11-08 14:39:00 +01:00
committed by Nicola Demo
parent 3f9305d475
commit 8b7b61b3bd
144 changed files with 2741 additions and 1766 deletions
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22
pina/adaptive_functions/adaptive_tanh.py
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@@ -1,6 +1,7 @@
import torch
from torch.nn.parameter import Parameter
class AdaptiveTanh(torch.nn.Module):
'''
Implementation of soft exponential activation.
@@ -18,7 +19,8 @@ class AdaptiveTanh(torch.nn.Module):
>>> x = torch.randn(256)
>>> x = a1(x)
'''
def __init__(self, alpha = None):
def __init__(self, alpha=None):
'''
Initialization.
INPUT:
@@ -31,17 +33,19 @@ class AdaptiveTanh(torch.nn.Module):
# initialize alpha
if alpha == None:
self.alpha = Parameter(torch.tensor(1.0)) # create a tensor out of alpha
self.alpha = Parameter(
torch.tensor(1.0)) # create a tensor out of alpha
else:
self.alpha = Parameter(torch.tensor(alpha)) # create a tensor out of alpha
self.alpha.requiresGrad = True # set requiresGrad to true!
self.alpha = Parameter(
torch.tensor(alpha)) # create a tensor out of alpha
self.alpha.requiresGrad = True # set requiresGrad to true!
self.scale = Parameter(torch.tensor(1.0))
self.scale.requiresGrad = True # set requiresGrad to true!
self.scale.requiresGrad = True # set requiresGrad to true!
self.translate = Parameter(torch.tensor(0.0))
self.translate.requiresGrad = True # set requiresGrad to true!
self.translate.requiresGrad = True # set requiresGrad to true!
def forward(self, x):
'''
@@ -49,4 +53,6 @@ class AdaptiveTanh(torch.nn.Module):
Applies the function to the input elementwise.
'''
x += self.translate
return self.scale * (torch.exp(self.alpha * x) - torch.exp(-self.alpha * x))/(torch.exp(self.alpha * x) + torch.exp(-self.alpha * x))
return self.scale * (torch.exp(self.alpha * x) - torch.exp(
-self.alpha * x)) / (torch.exp(self.alpha * x) +
torch.exp(-self.alpha * x))