base_aligner.py 文件源码

def add_training_op(self, loss):
        #optimizer = tf.train.AdamOptimizer(self.config.lr)
        #optimizer = tf.train.AdagradOptimizer(self.config.lr)
        optclass = getattr(tf.train, self.config.optimizer + 'Optimizer')
        assert issubclass(optclass, tf.train.Optimizer)
        optimizer = optclass(self.config.learning_rate)

        gradient_var_pairs = optimizer.compute_gradients(loss)
        vars = [x[1] for x in gradient_var_pairs]
        gradients = [x[0] for x in gradient_var_pairs]
        if self.config.gradient_clip > 0:
            clipped, _ = tf.clip_by_global_norm(gradients, self.config.gradient_clip)
        else:
            clipped = gradients

        self.grad_norm = tf.global_norm(clipped)
        train_op = optimizer.apply_gradients(zip(clipped, vars))
        return train_op