🎨 Format Python code with psf/black

pina/adaptive_functions/adaptive_linear.py

@@ -1,10 +1,11 @@
 """ Implementation of adaptive linear layer. """
+
 import torch
 from torch.nn.parameter import Parameter
 
 
 class AdaptiveLinear(torch.nn.Module):
-    '''
+    """
     Implementation of soft exponential activation.
     Shape:
         - Input: (N, *) where * means, any number of additional
@@ -19,16 +20,16 @@ class AdaptiveLinear(torch.nn.Module):
         >>> a1 = soft_exponential(256)
         >>> x = torch.randn(256)
         >>> x = a1(x)
-    '''
+    """
 
     def __init__(self):
-        '''
+        """
         Initialization.
         INPUT:
             - in_features: shape of the input
             - aplha: trainable parameter
             aplha is initialized with zero value by default
-        '''
+        """
         super(AdaptiveLinear, self).__init__()
 
         self.scale = Parameter(torch.tensor(1.0))
@@ -38,8 +39,8 @@ class AdaptiveLinear(torch.nn.Module):
         self.translate.requiresGrad = True  # set requiresGrad to true!
 
     def forward(self, x):
-        '''
+        """
         Forward pass of the function.
         Applies the function to the input elementwise.
-        '''
+        """
         return self.scale * (x + self.translate)