tensorflow.py 文件源码

def train(self, optimizer,
              training_set: Iterable[Tuple[QASetting, List[Answer]]],
              batch_size: int, max_epochs=10, hooks=tuple(),
              l2=0.0, clip=None, clip_op=tf.clip_by_value, summary_writer=None, **kwargs):
        """
        This method trains the reader (and changes its state).

        Args:
            optimizer: TF optimizer
            training_set: the training instances.
            batch_size: size of training batches
            max_epochs: maximum number of epochs
            hooks: TrainingHook implementations that are called after epochs and batches
            l2: whether to use l2 regularization
            clip: whether to apply gradient clipping and at which value
            clip_op: operation to perform for clipping
        """
        batches, loss, min_op, summaries = self._setup_training(
            batch_size, clip, optimizer, training_set, summary_writer, l2, clip_op, **kwargs)

        self._train_loop(min_op, loss, batches, hooks, max_epochs, summaries, summary_writer, **kwargs)