metrics.py 文件源码

def write_summary(self, value, writer, step):
        # Check lengths are consistent
        names = self.define_names()
        value = np.squeeze(value)
        if len(value) != len(names):
            raise RuntimeError('Provided list of values is not consistent '
                               + ' with bins defined.')
        # Store each summary independently
        for i, n in enumerate(names):
            summ_name = self.interval_name(names[i])
            summ_tag = '/'.join([self.get_label(), summ_name])
            summ = tf.Summary(
                value=[tf.Summary.Value(tag=summ_tag,
                                        simple_value=float(value[i]))]
            )
            writer.add_summary(summ, step)