Fixes#144976
Using appoach ① `IO[bytes]`, but could also try with a protocol.
## Notes:
- moved `torch.serialization.FILE_LIKE` to `torch.types.FileLike`
- Use `FileLike` annotation where it makes sense
- made sure those functions also support `os.PathLike`
- Replaced `isinstance(x, io.BytesIO)` with `isinstance(x, (io.IOBase, IO))` where appropriate.
- Replaced `BinaryIO` with `IO[bytes]` (the two ABCs are almost identical, the only difference is that `BinaryIO` allows `bytearray` input to `write`, whereas `IO[bytes]` only `bytes`)
- needed to make `torch.serialization._opener` generic to avoid LSP violations.
- skipped `torch/onnx/verification` for now (functions use `BytesIO.getvalue` which is not part of the `IO[bytes]` ABC, but it kind of seems that this is redundant, as e.g. `onnx.load` supports `str | PathLike[str] | IO[bytes]` directly...
Pull Request resolved: https://github.com/pytorch/pytorch/pull/144994
Approved by: https://github.com/ezyang, https://github.com/Skylion007
Summary:
fixes two issues:
- when exporting with debug=True, the list of error-causing modules and a dependency path to them is not printed correctly, there's a missing newline after the path, meaning the name of the module for the next error is on the wrong line, which makes the output a confusing mess to read
- when a pickled object references more than one mocked module directly, the error message incorrectly repeats the same information, claiming the referenced attribute is present in several different libraries, because the if condition references the last seen module name while walking the pickle ops, not the module name from the enclosing block `for module_name in all_dependencies:`. this is confusing because one error will print as O(all_dependencies) errors, all with different module names but the same attribute name
Differential Revision: D56578035
Pull Request resolved: https://github.com/pytorch/pytorch/pull/124943
Approved by: https://github.com/JonAmazon, https://github.com/houseroad
Adds a ruff lint rule to ban raising raw exceptions. Most of these should at the very least be runtime exception, value errors, type errors or some other errors. There are hundreds of instance of these bad exception types already in the codebase, so I have noqa'd most of them. Hopefully this error code will get commiters to rethink what exception type they should raise when they submit a PR.
I also encourage people to gradually go and fix all the existing noqas that have been added so they can be removed overtime and our exception typing can be improved.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/124570
Approved by: https://github.com/ezyang
Summary: Unless we register triton to be a special import, FX graph import mechanism imports it as `from fx-generated._0 import triton as triton` which is obviously broken.
Test Plan:
I could not figure out how to write a test for this but
```
buck2 run 'fbcode//mode/dev-nosan' fbcode//tgif/lib/tests/gpu_tests:lowering_pass_test -- -r test_default_ait_lowering_multi_hardwares
```
now passes
Differential Revision: D54990782
Pull Request resolved: https://github.com/pytorch/pytorch/pull/122041
Approved by: https://github.com/aakhundov
In particular this ensures we release the GIL when serializing:
- PyBytes objects (this is how we get the pickle object)
- Storage objects
Other string-like objects keep the gil which is fine because we only use this for very small strings today (for endianess) and so releasing the GIL is not important there
Co-authored-by: Mikayla Gawarecki <mikaylagawarecki@gmail.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/120818
Approved by: https://github.com/colesbury
Summary: IL generates massive function names: which meant that the pickle opcode used is BINUNICODE instead of the short version -- and then it would silently get skipped while pickling with protocol 4.
Differential Revision: D44815351
Pull Request resolved: https://github.com/pytorch/pytorch/pull/98674
Approved by: https://github.com/ezyang
Summary:
Makes torch.package debugging more transparent by
1. Pointing out not implictily externed modules in the standard library.
2. Creating a debug mode for users to find the source of broken modules.
Test Plan: Run package tests
Differential Revision: D42728753
Pull Request resolved: https://github.com/pytorch/pytorch/pull/92939
Approved by: https://github.com/kurman
Summary:
As title.
Saw this while working on another diff.
`storage` won't be defined in the `else` case. But this causes pyre to freak out.
Test Plan: Unit tests.
Differential Revision: D41751229
Pull Request resolved: https://github.com/pytorch/pytorch/pull/90306
Approved by: https://github.com/PaliC
Summary: To get source for a particular module, the "correct" thing to do is to check the module's spec and use `get_source` if it's a SourceFileLoader, since subclasses may look elsewhere than the `__file__`, and the spec will give the source of truth. For torch packager, however, we prefer to use linecache, but the loader could still change the file, so we figure out the file for the module using the spec's loader rather than using `module.__file__`, if possible.
Test Plan: This code path will get exercised by CI. Also added a test for remapped files.
Differential Revision: D41412983
Pull Request resolved: https://github.com/pytorch/pytorch/pull/90258
Approved by: https://github.com/PaliC
Summary:
In this logic, we are traversing the entries to find the module for STACK_GLOBAL entries.
According to 2837241f22/Lib/pickletools.py (L1799) we need to look for GET, BINGET and LONG_BINGET.
So this diff updates that. Also while testing, I found some cases of empty modules, for cases such as tanh. For this I added the option to skip processing when this is the case.
Test Plan: Tested with f392778829
Differential Revision: D41748595
Pull Request resolved: https://github.com/pytorch/pytorch/pull/90223
Approved by: https://github.com/PaliC
### Description
Since the major changes for `_TypedStorage` and `_UntypedStorage` are now complete, they can be renamed to be public.
`TypedStorage._untyped()` is renamed to `TypedStorage.untyped()`.
Documentation for storages is improved as well.
### Issue
Fixes#82436
### Testing
N/A
Pull Request resolved: https://github.com/pytorch/pytorch/pull/82438
Approved by: https://github.com/ezyang
Summary:
Applies new import merging and sorting from µsort v1.0.
When merging imports, µsort will make a best-effort to move associated
comments to match merged elements, but there are known limitations due to
the diynamic nature of Python and developer tooling. These changes should
not produce any dangerous runtime changes, but may require touch-ups to
satisfy linters and other tooling.
Note that µsort uses case-insensitive, lexicographical sorting, which
results in a different ordering compared to isort. This provides a more
consistent sorting order, matching the case-insensitive order used when
sorting import statements by module name, and ensures that "frog", "FROG",
and "Frog" always sort next to each other.
For details on µsort's sorting and merging semantics, see the user guide:
https://usort.readthedocs.io/en/stable/guide.html#sorting
Test Plan: S271899
Reviewed By: lisroach
Differential Revision: D36402110
Pull Request resolved: https://github.com/pytorch/pytorch/pull/78973
Approved by: https://github.com/osalpekar
Summary: This adds logs for usage of deploy and package. These can be used to track where it's being used in production so we can support it better.
Test Plan: no functional changes - existing tests
Reviewed By: PaliC
Differential Revision: D36258876
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77097
Approved by: https://github.com/PaliC
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72237
add a generic zip file reader/writer to torch.package in order to get rid of dependency on torch for non torchscript / tensor related usages of package. This also enables users to create a derived class from the zip file reader/writer classes to have their own serialization/deserialization if it's desired for performance needs.
https://www.internalfb.com/intern/diff/D35423079/ was reverted due to this refactor changing the name of where most of the implementation components of PackageExporter/PackageImporter come from like ModuleActionType_ etc.
This diff also changes the import paths where these components come from to point to the correct file compared to D35423079
Test Plan: Imported from OSS
Reviewed By: malfet
Differential Revision: D35423079
Pulled By: PaliC
fbshipit-source-id: 31abc4364d5fd007911cfb67cf36ebfac5d786f4
(cherry picked from commit 023b0d1445e0b1e1bb7a03c660cd62eb9d26d2a6)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74702
- add flag in constructor.
- add if condition routing to extern c-extension in method `_intern_module`.
- add unit test for the new condition.
Test Plan: Imported from OSS
Reviewed By: PaliC
Differential Revision: D35124731
fbshipit-source-id: a4b7fdf3210e0ad4bfd1ea30fd94595d10405987
(cherry picked from commit 57239a77ae099328025ab2d634e7880bd14a473b)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74610
Adding python version to exported package and reading it on import as per this issue in github https://github.com/pytorch/pytorch/issues/74068
ghstack-source-id: 152003088
Test Plan: CI Tests
Reviewed By: PaliC
Differential Revision: D35062709
fbshipit-source-id: 04091a1255a09b96255112a60d31df127c424193
(cherry picked from commit ed39fd54b8b20918dac89a2873ecccf06aafd724)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74315
Now instead of spitting out a NotImplemented Error when the Package Exporter finds an object for a mocked module, it combines these errors with the rest of the Packaging Errors of PackageExporter to get something like
```
torch.package.package_exporter.PackagingError:
* Module was mocked out, but is still being used in the package.Please intern or extern the mocked modules if objects are supposed to be inthe package.
package_a
Context: Object(s) '['PackageASubpackageObject']' from module package_a was mocked out during packaging but is being used in resource - obj.pkl in package obj.
package_a.subpackage
Context: Object(s) '['PackageASubpackageObject']' from module package_a.subpackage was mocked out during packaging but is being used in resource - obj.pkl in package obj.
```
This makes it significantly easier to fix mocked object errors as they all should appear at once.
Test Plan: Imported from OSS
Reviewed By: d4l3k
Differential Revision: D34951973
Pulled By: PaliC
fbshipit-source-id: 01ee4ba3767967ef9a9bcd69ad86362ebc100b2d
(cherry picked from commit 900edd270ee8f5802fc6e56df08fff6b073ac6f2)
