Whereas :class:`~pytorch_lightning.plugins.training_type.DDPPlugin` only performs 1 transfer to sync gradients, making DDP MUCH faster than DP. When using DDP plugins, set find_unused_parameters=False. By default we have set find_unused_parameters to True for compatibility reasons that have been observed in the past (see the discussion for more ...
Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters. This flag results in an extra traversal of ...
I think switch find_unused_parameters=True by default to False is a breaking change, but in docs, it doesn't mention, yet no clear instructions to set to True. 2 Replies
31.08.2021 · [W reducer.cpp:1050] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters, consider turning this flag off.
When using DDP on a multi-node cluster, set NCCL parameters¶. NCCL is the NVIDIA Collective Communications Library which is used under the hood by PyTorch to handle communication across nodes and GPUs. There are reported benefits in terms of speedups when adjusting NCCL parameters as seen in this issue.In the issue we see a 30% speed improvement when training …
15.06.2021 · Did you try to add the suggested find_unused_parameters=True argument and if so, did you get any other error? be7f984b2f2e66ba7969 (杜明軒) June 17, 2021, 1:23am #3
Marking a parameter gradient as ready does not help DDP skip buckets as for now, but it will prevent DDP from waiting for absent gradients forever during the backward pass. Note that traversing the autograd graph introduces extra overheads, so applications should only set find_unused_parameters to True when necessary.
29.01.2021 · g the keyword argument `find_unused_parameters=True` to `torch.nn.parallel.DistributedDataParallel`; (2) making sure all `f orward` function outputs participate in calculating loss. If you already have done the above two steps, then the distribute ... pytorch 中如果使用 ...
19.01.2021 · Using pytorch-lightning to train PixelCL on multi-gpu lucidrains/pixel-level-contrastive-learning#11. Open. ahmed-bensaad mentioned this issue on Feb 2. Added parameter for returning positive pixels pairs lucidrains/pixel-level-contrastive-learning#12. Closed.