code: def test_record_stream_cuda(self, cuda_sleep):
      # This test detects unexpected block reallocation. For reliable test,
      # the stream to allocate tensors is isolated. The allocator will not
      # reuse free blocks which were allocated from another stream.
      stream_alloc = new_stream(torch.device("cuda"))
      with torch.cuda.stream(stream_alloc):
          x = torch.rand(1, device=torch.device("cuda"))
  
      stream = new_stream(torch.device("cuda"))
      record_stream(x, stream)
      with use_stream(stream):
          cuda_sleep(0.5)
  
      # 'x' is deleted at Python's perspective. But the block of 'x' is still
      # required for 'stream'. 'y' shouldn't be allocated to the block.
      data_ptr = x.data_ptr()
      del x
      stream_alloc.synchronize()
      with torch.cuda.stream(stream_alloc):
          y = torch.rand(1, device=torch.device("cuda"))
      assert y.data_ptr() != data_ptr
  
      # Pause Python until 'stream' finishes tasks queued. Now the block of
      # 'x' is free to be reallocated.
      wait_stream(CPUStream, stream)
      with torch.cuda.stream(stream_alloc):
          z = torch.rand(1, device=torch.device("cuda"))
      assert z.data_ptr() == data_ptr
  
imports: import pytest
  import torch
  from fairscale.nn.pipe.stream import CPUStream, current_stream, default_stream, get_device, is_cuda, new_stream, record_stream, use_device, use_stream, wait_stream
label_desc: Use image node_id 2 for calling the TestRecordStream obj's underlying member method code with example usage: obj.test_record_stream_cuda(cuda_sleep) without return types