data_pipeline.py 文件源码

def _batch_samples(self, sample):
    """Batch several samples together."""

    # Batch and shuffle
    if self.shuffle:
      samples = tf.train.shuffle_batch(
          sample,
          batch_size=self.batch_size,
          num_threads=self.nthreads,
          capacity=self.capacity,
          min_after_dequeue=self.min_after_dequeue)
    else:
      samples = tf.train.batch(
          sample,
          batch_size=self.batch_size,
          num_threads=self.nthreads,
          capacity=self.capacity)
    return samples