reader.py 文件源码

def parallel_reader(self, min_queue_examples=1024):
        """Parallel record reader

            Primarily used for Training ops

        Args:
            min_queue_examples: min number of queue examples after dequeue

        Returns
            a single item from the tfrecord files
        """
        with tf.name_scope('parallel_reader'):
            data_files = self.dataset.data_files()
            filename_queue = tf.train.string_input_producer(
                data_files, num_epochs=self.num_epochs, shuffle=self.shuffle)
            if self.shuffle:
                examples_queue = tf.RandomShuffleQueue(
                    capacity=self.capacity, min_after_dequeue=min_queue_examples, dtypes=[tf.string])
            else:
                examples_queue = tf.FIFOQueue(
                    capacity=self.capacity, dtypes=[tf.string])

            enqueue_ops = []
            for _reader in self._readers:
                _, value = _reader.read(filename_queue)
                enqueue_ops.append(examples_queue.enqueue([value]))
            tf.train.queue_runner.add_queue_runner(
                tf.train.queue_runner.QueueRunner(examples_queue, enqueue_ops))
            return examples_queue.dequeue()