8000 PyTorch v1.0.0 multi-GPU compatibility issue · Issue #13 · ksw0306/FloWaveNet · GitHub
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PyTorch v1.0.0 multi-GPU compatibility issue #13

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@L0SG

Currently, we cannot run the multi-GPU training on PyTorch v1.0.0 due to a strange null gradient issue.

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  1. candlewill commented on Dec 21, 2018

    @candlewill

    Oh my God. I have trained on the multi-GPU version for one week with all of my four GPUs. In the params/flowavenet/ dir, only one checkpoint was generated.

    Thanks for pointing out this.

  2. L0SG commented on Dec 21, 2018

    @L0SG
    CollaboratorAuthor

    Oops, sorry about the delayed issue post in this repo. Filed the report to the PyTorch repo about two weeks ago, so please stick to v0.4.1 until the issue is resolved.

  3. L0SG commented on Feb 12, 2019

    @L0SG
    CollaboratorAuthor

    Update: the issue still persists in the latest 1.0.1 release.

  4. added a commit that references this issue on Apr 22, 2019
    3f4e65f
  5. reopened this on Apr 23, 2019
  6. L0SG commented on Apr 23, 2019

    @L0SG
    CollaboratorAuthor

    Note: DistributedDataParallel implementation from @1ytic circumvents the multi-GPU issue, so please use train_apex.py of the master branch until the issue from DataParallel (from train.py) is resolved.

  7. L0SG commented on Oct 10, 2019

    @L0SG
    CollaboratorAuthor

    Update: the issue was fixed with the 1.2.0 release. We'll keep this issue open for a while for a future reference.

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