Need to revert due to internal hangs: S437700
This reverts commit b6c1490cc0.
Revert "[dynamo] implement IteratorVariable and polyfill fallbacks for enumerate (#131725)"
This reverts commit 2576dbbc35.
Revert "[dynamo] add itertools repeat/count bytecode reconstruction (#131716)"
This reverts commit 35b4de32fa.
Revert "[dynamo] add lazy IteratorVariable implementations for map and zip (#131413)"
This reverts commit 7d282d8755.
Fixes #ISSUE_NUMBER
Pull Request resolved: https://github.com/pytorch/pytorch/pull/132528
Approved by: https://github.com/ZainRizvi
Need to revert due to internal hangs: S437700
This reverts commit b6c1490cc0.
Revert "[dynamo] implement IteratorVariable and polyfill fallbacks for enumerate (#131725)"
This reverts commit 2576dbbc35.
Revert "[dynamo] add itertools repeat/count bytecode reconstruction (#131716)"
This reverts commit 35b4de32fa.
Revert "[dynamo] add lazy IteratorVariable implementations for map and zip (#131413)"
This reverts commit 7d282d8755.
Fixes #ISSUE_NUMBER
Pull Request resolved: https://github.com/pytorch/pytorch/pull/132528
Approved by: https://github.com/ZainRizvi
Fixes https://github.com/pytorch/pytorch/issues/130750.
Repro of lazy/eager `map` discrepancy without `islice`:
```python
def fn(a, b):
y = 1
def f(x):
nonlocal y
y += 1
return x
l = list(zip([a, b], map(f, [1, 2, 3, 4])))
return a + y
```
The major change is that we implement `MapVariable` and `ZipVariable` based on `IteratorVariable`. Before, `map` and `zip` were being traced by immediately unpacking the result as a `TupleVariable`, which is wrong in cases such as the example above.
`MapVariable`s are not allowed to be unpacked while `ZipVariable`s can only be unpacked if all of its iterables can also be unpacked.
We also add new `[has_]force_unpack_var_sequence` methods to `VariableTracker` for the case where it is safe to unpack the entire sequence lazily, e.g., when building a list from a map (i.e. `list(map(f, ...))`).
Pull Request resolved: https://github.com/pytorch/pytorch/pull/131413
Approved by: https://github.com/anijain2305
The original motivation for MYPYINDUCTOR was a faster type checking configuration that only checked a subset of files. With the removal of `follow_imports = ignore`, we are now able to use dmypy to do fast incremental typechecking, eliminating the need for this.
Perhaps erroneously, when I tee'ed up this PR I elected to delete the `follow_imports = skip` designations in the mypy-inductor.ini. This lead to a number of extra type error suppressions that I manually edited. You will need to review.
Signed-off-by: Edward Z. Yang <ezyang@meta.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/118432
Approved by: https://github.com/Skylion007
ghstack dependencies: #118414, #118418
We want to get to a point where most UserErrors link to exportdb examples. This PR makes passing case names non-optional to make this intent clearer and encourage developers who raise UserErrors to make or point to examples that make fixing such errors more obvious for users.
In addition, sometimes there are multiple examples that are relevant to an error. Thus this PR also enables passing multiple case names.
Retry of #110733 which was reverted due to a landrace.
Differential Revision: [D50087148](https://our.internmc.facebook.com/intern/diff/D50087148/)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/110878
Approved by: https://github.com/gmagogsfm, https://github.com/tugsbayasgalan
We want to get to a point where most `UserError`s link to `exportdb` examples. This PR makes passing case names non-optional to make this intent clearer and encourage developers who raise `UserError`s to make or point to examples that make fixing such errors more obvious for users.
In addition, sometimes there are multiple examples that are relevant to an error. Thus this PR also enables passing multiple case names.
Differential Revision: [D50020465](https://our.internmc.facebook.com/intern/diff/D50020465/)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/110733
Approved by: https://github.com/zhxchen17
Ideally all `_dynamo.exc.UserError`s should have "case names", i.e., link to examples in `exportdb`.
This PR adds case names to several instances of `_dynamo.exc.UserError`. In particular, looking at coverage based on `UserErrorType`:
* `DYNAMIC_CONTROL_FLOW`, `ANTI_PATTERN`, and `STANDARD_LIBRARY` are fully covered.
* `CONSTRAINT_VIOLATION` and `DYNAMIC_DIM` have no coverage. We don't seem to have any dedicated examples of specifying dynamic shapes in `exportdb` (although they are used in some other examples without explanation, to avoid some specialization that would make such examples moot).
* `INVALID_INPUT` is only partly covered. Frankly this is tedious to cover via examples.
Differential Revision: [D49928518](https://our.internmc.facebook.com/intern/diff/D49928518/)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/110555
Approved by: https://github.com/angelayi, https://github.com/ydwu4
Fix: #107315
This PR enables dynamo to trace through the `pytree` API by inlining its functions. In
order to do so, a few details of `pytree` had to be changed.
In summary, this PR:
- Introduces `TreeSpecVariable` for representing `TreeSpec` instances
- Specializes `<type>.__bases__` call, returning a `TupleVariable`
- Enables the call to `id` builtin function for every variable that implements
`as_python_constant` method
- Specializes `ConstantVariable.call_method` for its (un)flatten functions
- Implements `UserDefinedObjectVariable.as_python_constant`
- Modifies `pytree` by:
- Make `SUPPORTED_NODES` a map of ids (instead of types) to `NodeDef`
- Removed `functools.wraps` function, since it can't be inlined
Pull Request resolved: https://github.com/pytorch/pytorch/pull/108533
Approved by: https://github.com/ezyang, https://github.com/voznesenskym
ghstack dependencies: #109201
RFC: https://github.com/pytorch/rfcs/pull/54
First commit is the contents of https://github.com/Quansight-Labs/numpy_pytorch_interop/
We have already been using this in core for the last few months as a external dependency. This PR pulls all these into core.
In the next commits, I do a number of things in this order
- Fix a few small issues
- Make the tests that this PR adds pass
- Bend backwards until lintrunner passes
- Remove the optional dependency on `torch_np` and simply rely on the upstreamed code
- Fix a number dynamo tests that were passing before (they were not tasting anything I think) and are not passing now.
Missing from this PR (but not blocking):
- Have a flag that deactivates tracing NumPy functions and simply breaks. There used to be one but after the merge stopped working and I removed it. @lezcano to investigate.
- https://github.com/pytorch/pytorch/pull/106431#issuecomment-1667079543. @voznesenskym to submit a fix after we merge.
All the tests in `tests/torch_np` take about 75s to run.
This was a work by @ev-br, @rgommers @honno and I. I did not create this PR via ghstack (which would have been convenient) as this is a collaboration, and ghstack doesn't allow for shared contributions.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/106211
Approved by: https://github.com/ezyang
