Summary:
Some machines don't have a versionless `python` on their PATH, which breaks these existing shebangs.
I'm assuming that all the existing versionless `python` shebangs are meant to be `python3` and not `python2`; please let me know if my assumption was incorrect for any of these.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/58275
Test Plan: CI.
Reviewed By: zhouzhuojie
Differential Revision: D28428143
Pulled By: samestep
fbshipit-source-id: 6562be3d12924db72a92a0207b060ef740f61ebf
Summary:
There is a module called `2to3` which you can target for future specifically to remove these, the directory of `caffe2` has the most redundant imports:
```2to3 -f future -w caffe2```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45033
Reviewed By: seemethere
Differential Revision: D23808648
Pulled By: bugra
fbshipit-source-id: 38971900f0fe43ab44a9168e57f2307580d36a38
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/41687
Specifically, this makes a new library (lazy), which can be used from both core
and workspace.
This allows workspace.Createnet to trigger lazy loading of dyndep dependencies.
Test Plan: Added a unit test specifically for workspace.CreateNet
Reviewed By: dzhulgakov
Differential Revision: D22441877
fbshipit-source-id: 3a9d1af9962585d08ea2566c9c85bec7377d39f2
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/41343
Currently caffe2.InitOpLibrary does the dll import uniliaterally. Instead if we make a lazy version and use it, then many pieces of code which do not need the caffe2urrenoperators get a lot faster.
One a real test, the import time went from 140s to 68s. 8s.
This also cleans up the algorithm slightly (although it makes a very minimal
difference), by parsing the list of operators once, rather than every time a
new operator is added, since we defer the RefreshCall until after we've
imported all the operators.
The key way we maintain safety, is that as soon as someone does an operation
which requires a operator (or could), we force importing of all available
operators.
Future work could include trying to identify which code is needed for which
operator and only import the needed ones. There may also be wins available by
playing with dlmopen (which opens within a namespace), or seeing if the dl
flags have an impact (I tried this and didn't see an impact, but dlmopen may
make it better).
Note that this was previously landed and reverted. The issue was that if a import failed and raised an exception, the specific library would not be removed from the lazy imports. This caused our tests which had libraries that failed to poison all other tests that ran after it. This has been fixed and a unit test has been added for this case (to help make it obvious what failed).
Test Plan:
I added a new test a lazy_dyndep_test.py (copied from all_compare_test.py).
I'm a little concerned that I don't see any explicit tests for dyndep, but this
should provide decent coverage.
I've added a specific test to handle the poisoning issues mentioned above, which caused the previous version to get reverted.
Differential Revision: D22506369
fbshipit-source-id: 7395df4778e8eb0220630c570360b99a7d60eb83
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/39488
Currently caffe2.InitOpLibrary does the dll import uniliaterally. Instead if we make a lazy version and use it, then many pieces of code which do not need the caffe2urrenoperators get a lot faster.
One a real test, the import time went from 140s to 68s. 8s.
This also cleans up the algorithm slightly (although it makes a very minimal
difference), by parsing the list of operators once, rather than every time a
new operator is added, since we defer the RefreshCall until after we've
imported all the operators.
The key way we maintain safety, is that as soon as someone does an operation
which requires a operator (or could), we force importing of all available
operators.
Future work could include trying to identify which code is needed for which
operator and only import the needed ones. There may also be wins available by
playing with dlmopen (which opens within a namespace), or seeing if the dl
flags have an impact (I tried this and didn't see an impact, but dlmopen may
make it better).
Test Plan:
I added a new test a lazy_dyndep_test.py (copied from all_compare_test.py).
I'm a little concerned that I don't see any explicit tests for dyndep, but this
should provide decent coverage.
Differential Revision: D21870844
fbshipit-source-id: 3f65fedb65bb48663670349cee5e1d3e22d560ed
