code: def test_read(
      self, tmpdir, async_queue, use_cuda_pinned_tensor, cuda_device
  ):
      _skip_for_invalid_environment(
          use_cuda_device=cuda_device,
          use_cuda_pinned_tensor=use_cuda_pinned_tensor,
      )
  
      ref_files = []
      for i in range(async_queue):
          f, _ = _do_ref_write(tmpdir, i)
          ref_files.append(f)
  
      single_submit = True
      overlap_events = True
      h = (
          AsyncIOBuilder()
          .load()
          .aio_handle(
              BLOCK_SIZE,
              QUEUE_DEPTH,
              single_submit,
              overlap_events,
              IO_PARALLEL,
          )
      )
  
      use_cpu_locked_tensor = False
      if cuda_device:
          aio_buffers = [
              torch.empty(
                  IO_SIZE,
                  dtype=torch.uint8,
                  device=get_accelerator().device_name(),
              )
              for _ in range(async_queue)
          ]
      elif use_cuda_pinned_tensor:
          aio_buffers = [
              get_accelerator().pin_memory(
                  torch.empty(IO_SIZE, dtype=torch.uint8, device="cpu")
              )
              for _ in range(async_queue)
          ]
      else:
          tmp_tensor = torch.empty(0, dtype=torch.uint8)
          aio_buffers = [
              h.new_cpu_locked_tensor(IO_SIZE, tmp_tensor)
              for _ in range(async_queue)
          ]
          use_cpu_locked_tensor = True
  
      _validate_handle_state(h, single_submit, overlap_events)
  
      for i in range(async_queue):
          read_status = h.async_pread(aio_buffers[i], ref_files[i])
          assert read_status == 0
  
      wait_status = h.wait()
      assert wait_status == async_queue
  
      for i in range(async_queue):
          with open(ref_files[i], "rb") as f:
              ref_buffer = list(f.read())
          assert ref_buffer == aio_buffers[i].tolist()
  
      if use_cpu_locked_tensor:
          for t in aio_buffers:
              h.free_cpu_locked_tensor(t)
  
imports: import pytest
  import os
  import filecmp
  import torch
  import deepspeed
  import deepspeed.comm
  from deepspeed.accelerator import get_accelerator
  from deepspeed.ops.op_builder import AsyncIOBuilder
  from unit.common import DistributedTest
label_desc: Use image node_id 1 for calling the TestAsyncQueue obj's underlying member method code with example usage: obj.test_read(tmpdir, async_queue, use_cuda_pinned_tensor, cuda_device) without return types