code: def __init__(
      self, pool_size: int, buffer_size: int, embedding_dim: int
  ):
      super().__init__()
  
      self.pool_size = pool_size
      self.buffer_size = buffer_size
      self.embedding_dim = embedding_dim
  
      self._device = torch.device("cpu")
      self._pull_queue = []
      self._push_cache = [None] * pool_size
      self._push_streams = [None] * pool_size
      self._pull_streams = [None] * pool_size
      self._cpu_buffers = [None] * pool_size
      self._cuda_buffers = [None] * pool_size
      self._pull_index = -1
      self._push_index = -1
  
imports: from typing import Optional, Callable
  import torch
  from torch import Tensor
  from torch.cuda import Stream
  from dig_ext.sync import synchronize, read_async, write_async
label_desc: Use image node_id 1 to create a new AsyncIOPool object from inherited base classes: torch.nn with example: obj = AsyncIOPool(pool_size, buffer_size, embedding_dim)