pretrained_word_embedding_TF_nn.py 文件源码

def batch_norm_layer(inp):
    """As explained in A. Gerón's book, in the default batch_normalization
    there is no scaling, i.e. gamma is set to 1. This makes sense for layers
    with no activation function or ReLU (like ours), since the next layers
    weights can take care of the scaling. In other circumstances, include
    scaling
    """
    # get the size from input tensor (remember, 1D convolution -> input tensor 3D)
    size = int(inp.shape[2])

    batch_mean, batch_var = tf.nn.moments(inp,[0])
    scale = tf.Variable(tf.ones([size]))
    beta  = tf.Variable(tf.zeros([size]))
    x = tf.nn.batch_normalization(inp,batch_mean,batch_var,beta,scale,
        variance_epsilon=1e-3)
    return x