Comments (5)
candlewill
commented on June 14, 2024
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.
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L0SG
commented on June 14, 2024
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.
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L0SG
commented on June 14, 2024
Update: the issue still persists in the latest 1.0.1 release.
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L0SG
commented on June 14, 2024
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.
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L0SG
commented on June 14, 2024
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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Related Issues (20)
- Periodic noise in flow based model? HOT 2
- problem when synthesize HOT 9
- CUDA State error HOT 2
- How long it take to finish training? HOT 2
- Poor synthetic audio quality HOT 4
- [Deleted]
- DataParralel takes too long HOT 1
- Why is the audio corresponding to the mel feature needed when synthesizing? HOT 3
- Do not understand where the text comes from HOT 1
- What is about the param (block_per_split) HOT 1
- Equation (3) and (5) in paper and implementation HOT 3
- Pretrained model HOT 1
- Please add to the README how many seconds it takes to synthesize a sentence HOT 2
- Command to generate synthesis from Tacotron-2 MELS ? HOT 1
- In causual mode, this expression will lead to a null tensor 'out' HOT 2
- BrokenPipeError: [Errno 32] Broken pipe in train.py HOT 1
- RuntimeError: CUDA error: out of memory in train.py HOT 1
- RuntimeError: Unknown error -1 HOT 1
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