Fix torch.compile on nn.module instead of on LightningModule
#587
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Tests can be fixed by merging this PR #585 |
ashleve
reviewed
Jul 29, 2023
Codecov ReportPatch coverage:
Additional details and impacted files@@ Coverage Diff @@
## main #587 +/- ##
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+ Coverage 83.75% 84.03% +0.28%
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Files 11 11
Lines 357 357
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+ Hits 299 300 +1
+ Misses 58 57 -1
☔ View full report in Codecov by Sentry. |
ashleve
approved these changes
Aug 24, 2023
| @@ -21,6 +21,7 @@ channels: | |||
| # compatibility is usually guaranteed | |||
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| dependencies: | |||
| - python=3.10 | |||
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Is python 3.10 required for torch compile?
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Yeah, unfortunately
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Are you sure? I see here that only python 3.8 is required.
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I forget exactly the error I got, so I'll try to recreate it to show that 3.10 is required, for posterity's sake.
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Thanks for PR, you can set it to ready if you want me to merge |
ashleve
changed the title
torch.compile on nn.module instead of on LightningModule
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Revert this fix as it has been fixed in PyTorch? |
I noticed this recently as well. I'm currently testing it for myself. I'm not sure which version of PyTorch fixes this problem as I don't see a version mentioned in the comment Lightning-AI/pytorch-lightning#17177 (comment) but I'll try to find it. |
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Alright, so I created a new conda environment with the following packages installed: This was from the following # reasons you might want to use `environment.yaml` instead of `requirements.txt`:
# - pip installs packages in a loop, without ensuring dependencies across all packages
# are fulfilled simultaneously, but conda achieves proper dependency control across
# all packages
# - conda allows for installing packages without requiring certain compilers or
# libraries to be available in the system, since it installs precompiled binaries
name: lightning-hydra-template-py38
channels:
- pytorch
- nvidia
- conda-forge
- defaults
# it is strongly recommended to specify versions of packages installed through conda
# to avoid situation when version-unspecified packages install their latest major
# versions which can sometimes break things
# current approach below keeps the dependencies in the same major versions across all
# users, but allows for different minor and patch versions of packages where backwards
# compatibility is usually guaranteed
dependencies:
- pytorch=2.0.1
- pytorch-cuda=11.8
- torchvision=0.15
- lightning=2.0.7
- torchmetrics=1.1.2
- hydra-core=1.3
- rich=13.3
- pre-commit=3.3 # dev
- pytest=7.2 # dev
- pydantic=2.1 # dev, required by pytest
- python=3.8
# --------- loggers --------- #
# - wandb
# - neptune-client
# - mlflow
# - comet-ml
# - aim>=3.16.2 # no lower than 3.16.2, see https://github.com/aimhubio/aim/issues/2550
- pip>=23
- pip:
- hydra-colorlog==1.2.0
- rootutils==1.0.7Then I ran Finally, this is my environment info (using This is with the setup where |
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What does this PR do?
Related to this issue Lightning-AI/pytorch-lightning#17177.
Before submitting
pytestcommand?pre-commit run -acommand?Did you have fun?
Make sure you had fun coding 🙃