It generally recommended to use `is/is not` to compare types. Therefore this series of changes apply this suggestion in the code base, and it aims to finally enabling related linter checks.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/165037
Approved by: https://github.com/mlazos
This is a lot of files changed! Don't panic! Here's how it works:
* Previously, we set `follow_imports = silent` for our mypy.ini configuration. Per https://mypy.readthedocs.io/en/stable/running_mypy.html#follow-imports, what this does is whenever we have an import to a module which is not listed as a file to be typechecked in mypy, we typecheck it as normal but suppress all errors that occurred in that file.
* When mypy is run inside lintrunner, the list of files is precisely the files covered by the glob in lintrunner.toml, but with files in excludes excluded.
* The top-level directive `# mypy: ignore-errors` instructs mypy to typecheck the file as normal, but ignore all errors.
* Therefore, it should be equivalent to set `follow_imports = normal`, if we put `# mypy: ignore-errors` on all files that were previously excluded from the file list.
* Having done this, we can remove the exclude list from .lintrunner.toml, since excluding a file from typechecking is baked into the files themselves.
* torch/_dynamo and torch/_inductor were previously in the exclude list, because they were covered by MYPYINDUCTOR. It is not OK to mark these as `# mypy: ignore-errors` as this will impede typechecking on the alternate configuration. So they are temporarily being checked twice, but I am suppressing the errors in these files as the configurations are not quite the same. I plan to unify the configurations so this is only a temporary state.
* There were some straggler type errors after these changes somehow, so I fixed them as needed. There weren't that many.
In the future, to start type checking a file, just remove the ignore-errors directive from the top of the file.
The codemod was done with this script authored by GPT-4:
```
import glob
exclude_patterns = [
...
]
for pattern in exclude_patterns:
for filepath in glob.glob(pattern, recursive=True):
if filepath.endswith('.py'):
with open(filepath, 'r+') as f:
content = f.read()
f.seek(0, 0)
f.write('# mypy: ignore-errors\n\n' + content)
```
Signed-off-by: Edward Z. Yang <ezyang@meta.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/118414
Approved by: https://github.com/thiagocrepaldi, https://github.com/albanD
We spend somewhere on the order 1% in `sympy.Expr.free_symbols` as it is called millions of times.
Most of the time we actually just want to know "is this a constant", however `e.is_constant()` is
horribly slow. It turns out though that there is another propery `is_number` that does what we want.
> property is_number:
>
> Returns True if self has no free symbols and no undefined functions (AppliedUndef, to be precise). It will be faster
> than if not self.free_symbols, however, since is_number will fail as soon as it hits a free symbol or undefined
> function.
Even further, we also avoid the overhead of building the unnecessary set object.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/112688
Approved by: https://github.com/lezcano
High level approach:
1. I generated a bunch of data comparing FlashAttention and Cutlass implementations (https://pastebin.com/pe0j3YeK)
2. I trained a decision tree using standard train/val split methodology and hyperparameter sweeps (https://pastebin.com/fjYX1HjR).
2a. I did a bunch of feature augmentation to capture interactions between features.
The heuristic I ended up with is:
```
use_flash = seq_len / (num_heads * batch_size) > 6
```
TL;DR: On my dataset, where FlashAttention and Cutlass differ by more than 10%, the existing heuristic achieves 69% accuracy. My new heuristic achieves 94% accuracy.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/99644
Approved by: https://github.com/ngimel, https://github.com/drisspg
This will be the last disruptive functorch internals change.
Why are we moving these files?
- As a part of rationalizing functorch we are moving the code in
functorch/_src to torch/_functorch
- This is so that we can offer the functorch APIs as native PyTorch APIs
(coming soon) and resolve some internal build issues.
Why are we moving all of these files at once?
- It's better to break developers all at once rather than many times
Test Plan:
- wait for tests
Pull Request resolved: https://github.com/pytorch/pytorch/pull/90091
Approved by: https://github.com/anijain2305, https://github.com/ezyang
This will be the last disruptive functorch internals change.
Why are we moving these files?
- As a part of rationalizing functorch we are moving the code in
functorch/_src to torch/_functorch
- This is so that we can offer the functorch APIs as native PyTorch APIs
(coming soon) and resolve some internal build issues.
Why are we moving all of these files at once?
- It's better to break developers all at once rather than many times
Test Plan:
- wait for tests
Pull Request resolved: https://github.com/pytorch/pytorch/pull/88756
Approved by: https://github.com/ezyang
