model.py 文件源码

def build_optimizer(loss, learning_rate, grad_clip):
    ''' 
    ??Optimizer

    loss: ??
    learning_rate: ???

    '''

    # ??clipping gradients
    tvars = tf.trainable_variables()
    grads, _ = tf.clip_by_global_norm(tf.gradients(loss, tvars), grad_clip)
    train_op = tf.train.AdamOptimizer(learning_rate)
    optimizer = train_op.apply_gradients(zip(grads, tvars))

    return optimizer