Use it to unwrap any functorch-wrapped tensor. I don't recommend using
the output in a program since it breaks the semantics of the transforms,
but it seems useful for debugging.
I will note that some people have wanted to get intermediate values out
of an e.g. grad transform, so this might be a way to do that...
Test Plan:
- tests
Pull Request resolved: https://github.com/pytorch/pytorch/pull/146528
Approved by: https://github.com/Chillee
Fixes#124550
Also moves `graph.eliminate_dead_code()` call to a few lines after
`_inline_module(...)` in `const_fold.py`
* Test plan:
Add a new test on `test_eager_transforms.py` to ensure the reported
issue was indeed fixed
Pull Request resolved: https://github.com/pytorch/pytorch/pull/133364
Approved by: https://github.com/zou3519
Add similar semantics for creating a buffer object similar to creating a parameter. This is done by introducing a new Buffer class that can be used for type disambiguation. The underlying functionality of registering a buffer remains the same as the register_buffer method has not been changed. The persistent parameter in the Buffer type is to indicate whether a buffer object should be persistent or not. Other non-test changes have to do with getting the new Buffer type recognized by inductor and dynamo. Remaining changes are test changes to make sure that the Buffer type can be used as a drop in replacement for register_buffer as it just leads to register_buffer being called. The addition of this new functionality still allows for normal tensors to be used as buffers so these changes are intended to be backwards compatible.
Fixes#35735
Co-authored-by: Mikayla Gawarecki <mikaylagawarecki@gmail.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/125971
Approved by: https://github.com/albanD, https://github.com/anijain2305, https://github.com/mlazos
Fixes#130284Fixes#130653
- Add `torch.library.register_vmap` to custom ops
- Add `register_vmap` for operators in ops in custom_op_db.
- Make `torch.autograd.Function` support kwarg-only kwargs for vmap
- test operators in op_db with `tests/test_vmap`.
- change `test_vmap` to allow custom `out_dim` and allow "None" in `out_dim` when testing.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/130589
Approved by: https://github.com/zou3519
Fixes#130284Fixes#130653
- Add `torch.library.register_vmap` to custom ops
- Add `register_vmap` for operators in ops in custom_op_db.
- Make `torch.autograd.Function` support kwarg-only kwargs for vmap
- test operators in op_db with `tests/test_vmap`.
- change `test_vmap` to allow custom `out_dim` and allow "None" in `out_dim` when testing.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/130589
Approved by: https://github.com/zou3519
0.12.0 Major Updates:
- Add context manager to temporarily set the dictionary sorting mode
- Add accessor APIs
- Use `stable` tag for `pybind11` for Python 3.13 support
- Fix potential segmentation fault for pickling support
0.12.1 Updates:
- Fix warning regression during import when launch with strict warning filters
Closes#130155
Pull Request resolved: https://github.com/pytorch/pytorch/pull/130139
Approved by: https://github.com/zou3519
ghstack dependencies: #130895
There's no reason to ban them for vmap or jvp, because without the
{grad, vjp} transforms those just act above PyTorch autograd, which will
end up saving regular Tensors.
Test Plan:
- some tests
Pull Request resolved: https://github.com/pytorch/pytorch/pull/131191
Approved by: https://github.com/drisspg
0.12.0 Major Updates:
- Add context manager to temporarily set the dictionary sorting mode
- Add accessor APIs
- Use `stable` tag for `pybind11` for Python 3.13 support
- Fix potential segmentation fault for pickling support
0.12.1 Updates:
- Fix warning regression during import when launch with strict warning filters
Closes#130155
Pull Request resolved: https://github.com/pytorch/pytorch/pull/130139
Approved by: https://github.com/zou3519
This PR:
* Sets a random seed before generating each sample for an OpInfo test. It does this by intercepting the sample input iterator via `TrackedInputIter`, optionally setting the seed to a test name specific seed before each iterator call (default is to set the seed).
* Some quick and dirty benchmarking shows (hopefully) negligible overhead from setting the random seed before each sample input generation. For a trivial (single assert) test that uses `@ops`:
* Uncovered a bunch of test issues:
* Test breakdown (>100 total)
* A lot of tolerance issues (tweaked tolerance values to fix)
* 1 broken OpInfo (`sample_inputs_masked_fill` was generating a sample of the wrong dtype)
* 3 actually broken semantics (for masked tensor; added xfails)
* 4 Jacobian mismatches (added xfails)
* 2 nan results (skip for now, need fixing)
* 3 results too far from reference result (add xfails)
* Skips MPS tests for now (there are so many failures!). Those will default to the old behavior.
**before (no seed setting):**
```
real 0m21.306s
user 0m19.053s
sys 0m5.192s
```
**after (with seed setting):**
```
real 0m21.905s
user 0m19.578s
sys 0m5.390s
```
* Utilizing the above for reproducible sample input generation, adds support for restricting the iterator to a single sample input. This is done via an env var `PYTORCH_OPINFO_SAMPLE_INPUT_INDEX` and its usage is included in the repro command.
```
======================================================================
ERROR: test_bar_add_cuda_uint8 (__main__.TestFooCUDA.test_bar_add_cuda_uint8)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/jbschlosser/branches/testing_updates/torch/testing/_internal/common_device_type.py", line 971, in test_wrapper
return test(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/home/jbschlosser/branches/testing_updates/test/test_ops.py", line 2671, in test_bar
self.assertFalse(True)
AssertionError: True is not false
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/jbschlosser/branches/testing_updates/torch/testing/_internal/common_utils.py", line 2816, in wrapper
method(*args, **kwargs)
File "/home/jbschlosser/branches/testing_updates/torch/testing/_internal/common_utils.py", line 2816, in wrapper
method(*args, **kwargs)
File "/home/jbschlosser/branches/testing_updates/torch/testing/_internal/common_device_type.py", line 419, in instantiated_test
result = test(self, **param_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/jbschlosser/branches/testing_updates/torch/testing/_internal/common_utils.py", line 1426, in wrapper
fn(*args, **kwargs)
File "/home/jbschlosser/branches/testing_updates/torch/testing/_internal/common_device_type.py", line 982, in test_wrapper
raise new_e from e
Exception: Caused by sample input at index 3: SampleInput(input=Tensor[size=(10, 5), device="cuda:0", dtype=torch.uint8], args=TensorList[Tensor[size=(), device="cuda:0", dtype=torch.uint8]], kwargs={}, broadcasts_input=False, name='')
To execute this test, run the following from the base repo dir:
PYTORCH_OPINFO_SAMPLE_INPUT_INDEX=3 python test/test_ops.py -k TestFooCUDA.test_bar_add_cuda_uint8
This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
----------------------------------------------------------------------
Ran 1 test in 0.037s
FAILED (errors=1)
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/128238
Approved by: https://github.com/janeyx99, https://github.com/justinchuby
Use `typing_extensions.deprecated` for deprecation annotation if possible. Otherwise, add `category=FutureWarning` to `warnings.warn("message")` if the category is missing.
Note that only warnings that their messages contain `[Dd]eprecat(ed|ion)` are updated in this PR.
Resolves#126888
- #126888
This PR is split from PR #126898.
- #126898
------
Pull Request resolved: https://github.com/pytorch/pytorch/pull/127689
Approved by: https://github.com/Skylion007
Use `typing_extensions.deprecated` for deprecation annotation if possible. Otherwise, add `category=FutureWarning` to `warnings.warn("message")` if the category is missing.
Note that only warnings that their messages contain `[Dd]eprecat(ed|ion)` are updated in this PR.
UPDATE: Use `FutureWarning` instead of `DeprecationWarning`.
Resolves#126888
- #126888
Pull Request resolved: https://github.com/pytorch/pytorch/pull/126898
Approved by: https://github.com/albanD
The `usort` config in `pyproject.toml` has no effect due to a typo. Fixing the typo make `usort` do more and generate the changes in the PR. Except `pyproject.toml`, all changes are generated by `lintrunner -a --take UFMT --all-files`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/127126
Approved by: https://github.com/kit1980
The `usort` config in `pyproject.toml` has no effect due to a typo. Fixing the typo make `usort` do more and generate the changes in the PR. Except `pyproject.toml`, all changes are generated by `lintrunner -a --take UFMT --all-files`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/127126
Approved by: https://github.com/kit1980
ghstack dependencies: #127122, #127123, #127124, #127125
The `usort` config in `pyproject.toml` has no effect due to a typo. Fixing the typo make `usort` do more and generate the changes in the PR. Except `pyproject.toml`, all changes are generated by `lintrunner -a --take UFMT --all-files`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/127125
Approved by: https://github.com/Skylion007
ghstack dependencies: #127122, #127123, #127124
TF32 causes issues with the tolerances here; we might also consider migrating some of the `with_tf32_off` tests in this file to `tf32_on_and_off` in case it would be useful to get signal for TF32.
CC @malfet @atalman
Pull Request resolved: https://github.com/pytorch/pytorch/pull/124104
Approved by: https://github.com/zou3519
