model_func.py 文件源码

def _variable_with_weight_decay(name, shape, wd = 0.0):
    """Helper to create an initialized Variable with weight decay.

    Note that the Variable is initialized with a xavier initialization.
    A weight decay is added only if one is specified.

    #Args:
            name: name of the variable
            shape: list of ints
            wd: add L2Loss weight decay multiplied by this float. If None, weight
                    decay is not added for this Variable.

    Returns:
            Variable Tensor
    """
    var = _variable_on_cpu(name, shape, tf.contrib.layers.xavier_initializer())
    # print("change var")
    # var = tf.Variable(tf.truncated_normal(shape, mean= 0.0, stddev = 1.0), name = name)
    if wd != 0.0:
        weight_decay = tf.mul(tf.nn.l2_loss(var), wd, name='weight_loss')
        tf.add_to_collection('losses', weight_decay)
    return var