model.py 文件源码

def linear(input, output_dim, scope=None, stddev=None):
    if stddev:
        norm = tf.random_normal_initializer(stddev=stddev)
    else:
        norm = tf.random_normal_initializer(
            stddev=np.sqrt(2.0 / input.get_shape()[1].value)
        )
    const = tf.constant_initializer(0.0)
    with tf.variable_scope(scope or 'linear'):
        w = tf.get_variable(
            'w',
            [input.get_shape()[1], output_dim],
            initializer=norm
        )
        b = tf.get_variable('b', [output_dim], initializer=const)
    return tf.matmul(input, w) + b