def on_epoch_end(self, pbar, epoch, last_metrics, **kwargs):
        "Put the various losses in the recorder and show a sample image."
        if not hasattr(self, 'last_gen') or not self.show_img: return
        data = self.learn.data
        img = self.last_gen[0]
        norm = getattr(data,'norm',False)
        if norm and norm.keywords.get('do_y',False): img = data.denorm(img)
        img = data.train_ds.y.reconstruct(img)
        self.imgs.append(img)
        self.titles.append(f'Epoch {epoch}')
        pbar.show_imgs(self.imgs, self.titles)
        return add_metrics(last_metrics, [getattr(self.smoothenerG,'smooth',None),getattr(self.smoothenerC,'smooth',None)])
def on_epoch_end ( self , pbar , epoch , last_metrics , ** kwargs ) : if not hasattr ( self , 'last_gen' ) or not self . show_img : return data = self . learn . data img = self . last_gen [ 0 ] norm = getattr ( data , 'norm' , False ) if norm and norm . keywords . get ( 'do_y' , False ) : img = data . denorm ( img ) img = data . train_ds . y . reconstruct ( img ) self . imgs . append ( img ) self . titles . append ( f'Epoch {epoch}' ) pbar . show_imgs ( self . imgs , self . titles ) return add_metrics ( last_metrics , [ getattr ( self . smoothenerG , 'smooth' , None ) , getattr ( self . smoothenerC , 'smooth' , None ) ] )
Put the various losses in the recorder and show a sample image.