trainer.py 文件源码

def __init__(self, config, model):
        assert isinstance(model, Model)
        self.config = config
        self.model = model
        self.opt = tf.train.AdagradOptimizer(config.init_lr)
        self.loss = model.get_loss()
        self.var_list = model.get_var_list()
        self.global_step = model.get_global_step()
        self.ema_op = model.ema_op
        self.summary = model.summary
        self.grads = self.opt.compute_gradients(self.loss, var_list=self.var_list)
        opt_op = self.opt.apply_gradients(self.grads, global_step=self.global_step)

        # Define train op
        with tf.control_dependencies([opt_op]):
            self.train_op = tf.group(self.ema_op)