Comments (3)
jsleep
commented on May 22, 2024
1
That's a great question, I believe we've tested with PyTorch1.3-1.9 in our team - the day that PyTorch move 2.0+ there may be some breaking change that we need to adapt to
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shatu
commented on May 22, 2024
1
I see. Maybe we should then update the DockerFile to reflect this. Currently, it'll fetch the most recent version of PyTorch, which might start breaking things with newer versions of PyTorch.
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jsleep
commented on May 22, 2024
we don't even really use that Dockerfile but may be I can add torch<=1.9 in the required deps setup.py, pymarlin depends completely on pytorch being installed and we should have some strict dependency on it (even if it hasn't been installed yet).
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Related Issues (20)
- DDP validation: All gather for flattened 1D tensors taking long time to complete HOT 4
- refactor to units of steps instead of epochs
- CustomArgParser doesn't support the yaml_file_arg_key functionality
- user defined save_best_checkpoint() hook HOT 1
- Custom Argparser doesn't support multi-level commandline override HOT 2
- DeepSpeed Trainer Backend
- Update installation documentation HOT 1
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- Easy self.log() and other QoL improvements such as sane defaults for module_interface
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- 这个真没必要
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- Link the blogposts?
- DDP Hangs with uneven batches
- Add support for uneven number of batches on different GPUs
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