diff --git a/pina/model/layers/orthogonal.py b/pina/model/layers/orthogonal.py
index 1d7cddd..32a0607 100644
--- a/pina/model/layers/orthogonal.py
+++ b/pina/model/layers/orthogonal.py
@@ -49,22 +49,20 @@ class OrthogonalBlock(torch.nn.Module):
 
         result = torch.zeros_like(X, requires_grad=self._requires_grad)
         X_0 = torch.select(X, self.dim, 0).clone()
-        result_0 = X_0/torch.linalg.norm(X_0)
+        result_0 = X_0 / torch.linalg.norm(X_0)
         result = self._differentiable_copy(result, 0, result_0)
 
         # iterate over the rest of the basis with Gram-Schmidt
         for i in range(1, X.shape[self.dim]):
             v = torch.select(X, self.dim, i).clone()
             for j in range(i):
-                vj = torch.select(result,self.dim,j).clone()
-                v = v - torch.sum(v * vj,
-                               dim=self.dim, keepdim=True) * vj
-            #result_i = torch.select(result, self.dim, i)
-            result_i = v/torch.linalg.norm(v)
+                vj = torch.select(result, self.dim, j).clone()
+                v = v - torch.sum(v * vj, dim=self.dim, keepdim=True) * vj
+            # result_i = torch.select(result, self.dim, i)
+            result_i = v / torch.linalg.norm(v)
             result = self._differentiable_copy(result, i, result_i)
         return result
 
-
     def _differentiable_copy(self, result, idx, value):
         """
         Perform a differentiable copy operation on a tensor.
@@ -79,7 +77,7 @@ class OrthogonalBlock(torch.nn.Module):
         """
         return result.index_copy(
             self.dim, torch.tensor([idx]), value.unsqueeze(self.dim)
-            )
+        )
 
     @property
     def dim(self):
@@ -104,8 +102,10 @@ class OrthogonalBlock(torch.nn.Module):
         # check consistency
         check_consistency(value, int)
         if value not in [0, 1, -1]:
-            raise IndexError('Dimension out of range (expected to be in '
-                             f'range of [-1, 1], but got {value})')
+            raise IndexError(
+                "Dimension out of range (expected to be in "
+                f"range of [-1, 1], but got {value})"
+            )
         # assign value
         self._dim = value