7ae7768617cba5863ecd14f1169fa75682897fbc,torch/distributed/optim/zero_redundancy_optimizer.py,ZeroRedundancyOptimizer,_broadcast_params,#ZeroRedundancyOptimizer#,443

Before Change

                )

        // Consume all async calls
        while len(self.work_handles) > 0:
            work_handle = self.work_handles.popleft()
            work_handle.wait()

    def _update_param_groups(self, local_to_global: bool = False) -> None:
        Sync learning rate and other optimizer attributes (needed to support schedulers).

        If the global param groups have been altered, and we want to make sure

After Change

                    handles.append(dist.broadcast(tensor=bucket, src=global_src_rank, group=self.group, async_op=True))

        // Wait for all the calls
        _ = list(map(lambda x: x.wait(), handles))

    def _update_param_groups(self, local_to_global: bool = False) -> None:
        Sync learning rate and other optimizer attributes (needed to support schedulers).

Instances