def _try_fetch()

in replay_buffer.py [0:0]


    def _try_fetch(self):
        if self._samples_since_last_fetch < self._fetch_every:
            return
        self._samples_since_last_fetch = 0
        try:
            worker_id = torch.utils.data.get_worker_info().id
        except:
            worker_id = 0
        eps_fns = sorted(self._replay_dir.glob('*.npz'), reverse=True)
        fetched_size = 0
        for eps_fn in eps_fns:
            eps_idx, eps_len = [int(x) for x in eps_fn.stem.split('_')[1:]]
            if eps_idx % self._num_workers != worker_id:
                continue
            if eps_fn in self._episodes.keys():
                break
            if fetched_size + eps_len > self._max_size:
                break
            fetched_size += eps_len
            if not self._store_episode(eps_fn):
                break