add xccl high priority stream test #2049
Conversation
There was a problem hiding this comment.
Pull Request Overview
This PR adds a test for XCCL high priority stream functionality to the distributed communication test suite. It introduces a new test method that validates XCCL process group options, specifically testing the is_high_priority_stream configuration.
- Adds
_test_pass_xccl_optionshelper method for testing XCCL process group options - Implements
test_pass_xccl_options_high_priority_streamto verify high priority stream functionality
Tip: Customize your code reviews with copilot-instructions.md. Create the file or learn how to get started.
| # test the process group works as expected | ||
| t = torch.tensor([self.rank + 1] * 10).xpu(self.rank) | ||
| pg.allreduce(t).wait() | ||
| expected_tensor = torch.tensor([3] * 10).xpu(self.rank) |
There was a problem hiding this comment.
The magic number 3 in the expected tensor should be calculated explicitly. For a 2-GPU setup (world_size=2), the sum would be (0+1) + (1+1) = 3, but this calculation isn't obvious. Consider using sum(range(self.world_size)) + self.world_size or adding a comment explaining the calculation.
| expected_tensor = torch.tensor([3] * 10).xpu(self.rank) | |
| # The expected value is the sum of (rank + 1) for all ranks in the group | |
| expected_value = sum(rank + 1 for rank in range(self.world_size)) | |
| expected_tensor = torch.tensor([expected_value] * 10).xpu(self.rank) |
Copilot uses AI. Check for mistakes.
Support high priority stream for xccl, test case add in #2049 We need merge this pr first and upstream op register pytorch/pytorch#163049 and then test case could be pass --------- Co-authored-by: mengfei25 <[email protected]>
Support high priority stream for xccl, test case add in #2049 We need merge this pr first and upstream op register pytorch/pytorch#163049 and then test case could be pass --------- Co-authored-by: mengfei25 <[email protected]>
No description provided.