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Summary of Changes
Hello @hiworldwzj, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!
This pull request addresses a critical bug in the multinode distributed processing (DP) mode of the base_backend.py module. The fix ensures that inter-node broadcast operations correctly identify their source rank, which is essential for reliable communication and data synchronization across multiple nodes in a distributed inference setup.
Highlights
- Distributed Communication Fix: Corrected the source rank calculation for
dist.broadcastoperations within the_try_read_new_reqs_normalmethod. This ensures that in a multinode distributed processing setup, the broadcast originates from the correct rank, preventing potential communication issues.
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| self.node_broadcast_tensor.fill_(0) | ||
| dist.broadcast(self.node_broadcast_tensor, src=0, group=self.node_nccl_group, async_op=False) | ||
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| src_rank_id = self.args.node_rank * self.node_world_size |
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The calculation for src_rank_id can be simplified by deriving it from the existing rank properties of the class. The global rank of the master process in the node can be calculated as self.global_rank - self.rank_in_node. This avoids a direct dependency on self.args and leverages the established distributed rank properties, which can improve code consistency and maintainability.
src_rank_id = self.global_rank - self.rank_in_node1 participant
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