(self, losses, subset='train')
return metrics_df
Prepare loss metrics using a list of tuples of the format: (epoch, loss)
        Where epoch is an integer and loss is a float 
        Returns a dataframe formatted for output
Prepare loss metrics using a list of tuples of the format: (epoch, loss)
        Where epoch is an integer and loss is a float 
        Returns a dataframe formatted for output
Prepare loss metrics using a list of tuples of the format : ( epoch loss ) Where epoch is an integer and loss is a float Returns a dataframe formatted for output
def _prep_losses(self, losses, subset='train'):
        """
        Prepare loss metrics using a list of tuples of the format: (epoch, loss)
        Where epoch is an integer and loss is a float 
        Returns a dataframe formatted for output
        """
        columns = ["metric", "value"]
        metrics_df = pd.DataFrame(losses, columns=columns)
        metrics_df.loc[:,'model'] = self.model
        metrics_df.loc[:,'subset'] = subset
        metrics_df = metrics_df[['model', 'subset'] + columns]

        return metrics_df
def _prep_losses ( self , losses , subset = 'train' ) : columns = [ "metric" , "value" ] metrics_df = pd . DataFrame ( losses , columns = columns ) metrics_df . loc [ : , 'model' ] = self . model metrics_df . loc [ : , 'subset' ] = subset metrics_df = metrics_df [ [ 'model' , 'subset' ] + columns ] return metrics_df