update

mupixutils.py

@@ -190,7 +190,7 @@ def train(d_model, g_model, gan_model, dataset, output_path, val_dataset = None,
                 val_loss = mse/((ssim+1)/2) # scaling ssim on 0,1 instead of -1,1 : trouble when ssim is <0
                 with open(output_path+"/log.txt", 'a') as file:
                         # file.write("[Loss] Val loss at epoch %d : MSE[%.3e], SSIM[%.3e], Validation_Loss[%.3e]\n"%(current_epoch,mse,ssim,val_loss))
-                        file.write("[Loss] Val loss at epoch ",str(current_epoch)," : MSE[",str(mse),"], SSIM[",str(ssim),"], Validation_Loss[",str(val_loss),"]\n")
+                        file.write("[Loss] Val loss at epoch "+str(current_epoch)+" : MSE["+str(mse)+"], SSIM["+str(ssim)+"], Validation_Loss["+str(val_loss)+"]\n")
                 if val_loss < best_val_loss:
                     best_val_loss = np.copy(val_loss)
                     g_model.save(output_path+"/networks/Generator")
@@ -214,7 +214,7 @@ def train(d_model, g_model, gan_model, dataset, output_path, val_dataset = None,
                     else :
                         with open(output_path+"/log.txt", 'a') as file:
                             # file.write("[Patience]: Reached at epoch %d with best validation loss :[%.3e]\n"%(current_epoch,val_loss))
-                            file.write("[Patience]: Reached at epoch ",str(current_epoch),"with best validation loss :[",str(val_loss),"]\n")
+                            file.write("[Patience]: Reached at epoch "+str(current_epoch)+"with best validation loss :["+str(val_loss)+"]\n")
                         break
 
             gc.collect()