• tf.reduce_mean （求向量的均值）等价于

  1N∑i=1Nxi

1. 对权值矩阵进行 l2 正则

def variable_with_weight_loss(shape, stddev, w1):    var = tf.Variable(tf.truncated_normal(shape, stddev=stddev))    if w1 is not None:        weight_loss = tf.multiply(tf.nn.l2_loss(var), w1, name='weight_loss')        tf.add_to_collections('losses', weight_loss)    return var

2. binary cross entropy

def bin_cross_entropy(preds, targets):    eps = 1e-12    return tf.reduce_mean(-targets*tf.log(preds+eps)-(1-targets)*tf.log(1-preds+eps))