NPU Stream的使用

用户进行异步拷贝需要用到Stream相关接口，MindIE Torch没有C++的Stream相关接口，而是直接复用libtorch的c10::Stream和c10::StreamGuard接口。MindIE Torch的Python相关Stream接口定义请参考API参考(Python)。

具体使用方法如下：

• C++伪代码示例如下：

  // create stream
  c10::Stream stream1 = c10::Stream(c10::Stream::DEFAULT, at::Device("npu:0"));
  c10::Stream stream2 = c10::Stream(c10::Stream::UNSAFE, at::Device("npu:0"), 10);
  
  // set stream
  c10::StreamGuard streamGuard(stream1); // 构造StreamGuard，并设置当前stream为stream1
  streamGuard.reset_stream(stream2); // 设置当前stream为stream2 
  
  // stream synchronize
  stream.synchronize();

• Python伪代码示例如下：

  # create stream
  stream1 = mindietorch.npu.Stream()
  stream2 = mindietorch.npu.Stream("npu:0")
  stream3 = mindietorch.npu.Stream(device = 0, stream_id = 10) 
  
  # set stream
  mindietorch.npu.set_stream(stream1) #方式1
  with mindietorch.npu.stream(stream2): #方式2    
      self.assertTrue(mindietorch.npu.current_stream() == stream2) # assertTrue是unittest.TestCase中的断言。
  
  # stream synchronize
  stream.synchronize()