apply PEP8

pytorch_lightning/root_module/grads.py

@@ -4,6 +4,7 @@ Module to describe gradients
 
 from torch import nn
 
+
 class GradInformation(nn.Module):
 
     def grad_norm(self, norm_type):
@@ -17,11 +18,10 @@ class GradInformation(nn.Module):
                     norm = param_norm ** (1 / norm_type)
 
                     results['grad_{}_norm_{}'.format(norm_type, i)] = round(norm.data.cpu().numpy().flatten()[0], 3)
-                except Exception as e:
+                except Exception:
                     # this param had no grad
                     pass
 
         total_norm = total_norm ** (1. / norm_type)
         results['grad_{}_norm_total'.format(norm_type)] = round(total_norm.data.cpu().numpy().flatten()[0], 3)
         return results
-