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adhere to lazy import rules #668
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Summary: Pull Request resolved: facebookresearch#668 Lazy import changes `Python` import semantics, specifically when it comes to initialization of packages/modules: https://www.internalfb.com/intern/wiki/Python/Cinder/Onboarding/Tutorial/Lazy_Imports/Troubleshooting/ For example, this pattern is not guaranteed to work: ``` import torch.optim ... torch.optim._multi_tensor.Adam # may fail to resolve _multi_tensor ``` And this is guaranteed to work: ``` import torch.optim._multi_tensor ... torch.optim._multi_tensor.Adam # will always work ``` A recent change to `PyTorch` changed module initialization logic in a way that exposed this issue. But the code has been working for years? This is the nature of undefined behavior, any change in the environment (in this the `PyTorch` code base can make it fail. Reviewed By: wat3rBro Differential Revision: D58876582
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Summary: Pull Request resolved: facebookresearch#668 Lazy import changes `Python` import semantics, specifically when it comes to initialization of packages/modules: https://www.internalfb.com/intern/wiki/Python/Cinder/Onboarding/Tutorial/Lazy_Imports/Troubleshooting/ For example, this pattern is not guaranteed to work: ``` import torch.optim ... torch.optim._multi_tensor.Adam # may fail to resolve _multi_tensor ``` And this is guaranteed to work: ``` import torch.optim._multi_tensor ... torch.optim._multi_tensor.Adam # will always work ``` A recent change to `PyTorch` changed module initialization logic in a way that exposed this issue. But the code has been working for years? This is the nature of undefined behavior, any change in the environment (in this the `PyTorch` code base can make it fail. Reviewed By: wat3rBro Differential Revision: D58876582
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Summary:
Lazy import changes
Pythonimport semantics, specifically when it comes to initialization of packages/modules: https://www.internalfb.com/intern/wiki/Python/Cinder/Onboarding/Tutorial/Lazy_Imports/Troubleshooting/For example, this pattern is not guaranteed to work:
And this is guaranteed to work:
A recent change to
PyTorchchanged module initialization logic in a way that exposed this issue.But the code has been working for years? This is the nature of undefined behavior, any change in the environment (in this the
PyTorchcode base can make it fail.Differential Revision: D58876582