srch

23.11.2019 · local_rank is supplied to the developer to indicate that a particular instance of the training script should use the “local_rank” GPU device. For illustration, in the example above provided by @spanev , p1 is passed local_rank 0 indicating it should use GPU device id 0.

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Nov 23, 2019 · local_rank is supplied to the developer to indicate that a particular instance of the training script should use the “local_rank” GPU device. For illustration, in the example above provided by @spanev , p1 is passed local_rank 0 indicating it should use GPU device id 0.

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27.07.2021 · local_rank could be read from args.local_rank if torch.distributed is applied. otherwise local_rank doesn’t exist in args, right? how could I get node id and rank in my code? H-Huang (Howard Huang) July 28, 2021, 3:12pm

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Nov 21, 2019 · 1 Answer1. Show activity on this post. Your local_rank depends on self.distributed==True or self.distributed!=0 which means 'WORLD_SIZE' needs to be in os.environ so just add the environment variable WORLD_SIZE (which should be an integer)

13.11.2019 · So this involves kind of "distributed" training with the term local_rank in the script above, especially when local_rank equals 0 or -1 like in line 83. After reading some materials from distributed computation I guess that local_rank is like an ID for a machine. And 0 may mean this machine is the "main" or "head" in the computation.

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Nov 13, 2019 · So this involves kind of "distributed" training with the term local_rank in the script above, especially when local_rank equals 0 or -1 like in line 83. After reading some materials from distributed computation I guess that local_rank is like an ID for a machine. And 0 may mean this machine is the "main" or "head" in the computation.