evaluation.py 文件源码

def gradient_summaries(gvs, norm=True, ratio=True, histogram=True):
    """Register gradient summaries.

    Logs the global norm of the gradient, ratios of gradient_norm/uariable_norm and
    histograms of gradients.

    :param gvs: list of (gradient, variable) tuples
    :param norm: boolean, logs norm of the gradient if True
    :param ratio: boolean, logs ratios if True
    :param histogram: boolean, logs gradient histograms if True
    """

    with tf.name_scope('grad_summary'):
        if norm:
            grad_norm = tf.global_norm([gv[0] for gv in gvs])
            tf.summary.scalar('grad_norm', grad_norm)

        for g, v in gvs:
            var_name = v.name.split(':')[0]
            if g is None:
                print 'Gradient for variable {} is None'.format(var_name)
                continue

            if ratio:
                log_ratio((g, v), '/'.join(('grad_ratio', var_name)))

            if histogram:
                tf.summary.histogram('/'.join(('grad_hist', var_name)), g)