This PR adds support for list subclasses. Among other things are
1) Tracking the mutations on internal vts like `_dict_vt` and `_list_vt` using sources. This helps identify if there was a mutation in the underlying data structures, and we need to reconstruct it.
2) `UserDefinedObjectVariable` now has a new method - `is_modified` which `side_effect` infra relies upon to check mutations in the underlying vts (like `_dict_vt`).
3) `reconstruction` logic ensures that we use `dict.__getitem__` and `list.__getitem__` methods. This is super important because we don't want to call the overridden `__getitem__` methods.
If this PR is hard to review, please let me know. I can break it into several small PRs.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/146819
Approved by: https://github.com/StrongerXi, https://github.com/jansel
See the comment [here](https://github.com/pytorch/pytorch/issues/132014#issuecomment-2379547400) (cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov @XilunWu @rec) - this PR updates `_unsafe_set_version_counter` to accept a list of tensors, for overhead-sensitive users (e.g. distributed) who need to hide VC bumps from autograd on a large list of tensors without wanting to suffer the overhead of going from python->C++ separately for every tensor in the list.
I left the binding in pybind, and used a `std::vector`. if we **really** need to optimize overhead even further, we could write a manual cpython binding.
I use this updated API in the next PR to fix FSDP2, so that it properly hides the VC of all `all_gather_buffer` tensors in its call to `split_with_sizes_copy.out(all_gather_buffers)`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/137921
Approved by: https://github.com/awgu, https://github.com/albanD
This reintroduces the change backed out by #145393 and fixes the underlying problem.
Although using a BuiltinVariable was better than nothing when we saw a GenericAlias it had problems if there was a graph break and we had to reconstruct the original python code which BuiltinVariable did as a simple `list` instead of a `list[int]`.
This changes it to use a TypingVariable instead and then teaches TypingVariable how to reconstruct.
Original commit changeset: 77b9193acb23
python test/dynamo/test_repros.py ReproTests.test_graph_break_on_jit_isinstance
Pull Request resolved: https://github.com/pytorch/pytorch/pull/145554
Approved by: https://github.com/anijain2305
ghstack dependencies: #145551, #145552, #145553
BuiltinVariable.call_hasattr() overrides the base class - but actually behaves differently. The base is `obj.call_hasattr(tx, attr)` but BuiltinVariable's version is `<unused>.call_hasattr(tx, obj, attr)`.
The BuiltinVariable version is used as a pattern from `call_self_handler()` for `BuiltinVariable(hasattr)`. I think the other version is just used for internal `hasattr(obj, name)` so I renamed that one to `call_obj_hasattr`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/145551
Approved by: https://github.com/anijain2305
This patch applies a local and practical workaround for custom dict
construction when multiple inheritance is involved.
Handling multiple inheritance in general could be a lot more involved,
so I created #142414 to track that.
Fixes#141118.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/142416
Approved by: https://github.com/jansel
This patch applies a local and practical workaround for custom dict
construction when multiple inheritance is involved.
Handling multiple inheritance in general could be a lot more involved,
so I created #142414 to track that.
Fixes#141118.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/142416
Approved by: https://github.com/jansel
As title, this also uncovered a few invalid use cases; the cases that
cause error are fixed in separate patches prior to this patch, and the
rest are fixed in this patch.
This patch also moves a few `.source` mutation to variable construction,
to increase the coverage of the validation.
Fixes#133027.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/141717
Approved by: https://github.com/jansel
ghstack dependencies: #141713, #141714, #141715, #141902, #141716
* Automatically applies ruff rule 401. Turns loops into equivalent list comprehensions which are faster and do not leak the scope of the loop variables.
* list comprehensions not only often have better typing, but are 50+% faster than for loops on overhead. They also preserve length information etc and are better for the interpreter to optimize.
* Manually went back and made mypy happy after the change.
* Also fixed style lints in files covered by flake8 but not by pyfmt
Pull Request resolved: https://github.com/pytorch/pytorch/pull/140980
Approved by: https://github.com/justinchuby, https://github.com/malfet
This patch adds 2 simple methods `VariableTracker.is_mutable()` and
`VariableTracker.is_immutable()`, which helps clarify intention. For
instance, rather than writing
```python
if var.mutation_type:
...
```
After this patch one can write
```python
if var.is_mutable():
...
```
This patch also simplifies `mutation_type` propagation in some
`ListVariable` methods.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/139341
Approved by: https://github.com/mlazos, https://github.com/anijain2305
ghstack dependencies: #139339, #139340
This patch addresses the renaming part of #133027, specifically, it
renames the following and adds documentation for relevant classes.
1. `VariableTracker.mutable_local` to `mutation_type`
2. `MatableLocal `to `ValueMutationNew`
3. `MutableSideEffects `to `ValueMutationExisting`
4. `MutableLocalSource` to `SourceType`
5. `MutableLocalSource.Local` to `New`
Note that (2), (3) and (5) are mainly to bring consistency between them
and `AttributeMutationNew`, `AttributeMutationExisting`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/139339
Approved by: https://github.com/jansel, https://github.com/mlazos, https://github.com/anijain2305
