Previously, cudagraphs and dynamic_shapes were incompatible and enabling
dynamic shapes would forcibly disable cudagraphs. This new strategy
I think is better. The idea is essentially that cudagraphs is an
"optimization" that happens to guard on every input. When cudagraphs
is on, we force everything static, and this automatically does the right
thing because we will force a recompile if sizes change.
This obsoletes https://github.com/pytorch/pytorch/pull/101813
Signed-off-by: Edward Z. Yang <ezyang@meta.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/103290
Approved by: https://github.com/voznesenskym, https://github.com/eellison
Skip all cuda graph-related unit tests by setting env var `PYTORCH_TEST_SKIP_CUDAGRAPH=1`
This PR refactors the `TEST_CUDA` python variable in test_cuda.py into common_utils.py. This PR also creates a new python variable `TEST_CUDA_GRAPH` in common_utils.py, which has an env var switch to turn off all cuda graph-related tests.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/103032
Approved by: https://github.com/malfet
PR to enable default workflow PyTorch 2.0 unit tests for the ROCm stack.
- Enables all the dynamo unit test suites
- Enables some of the inductor unit test suites
- `test_config`
- `test_cpp_wrapper` (cpu only)
- `test_minifier`
- `test_standalone_compile`
- `test_torchinductor_dynamic_shapes`
- `test_torchinductor_opinfo`
- `test_torchinductor`
- `test_triton_wrapper`
- Introduces TEST_WITH_ROCM conditions for unit test skip/fail dictionaries in test_torchinductor_dynamic_shapes.py and test_torchinductor_opinfo.py
Note this PR follows on from the discussions for the previous UT enablement PR https://github.com/pytorch/pytorch/pull/97988, we have opted to only enable a few inductor suites at the moment to ease the upstreaming effort as these files are changing very quickly.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/100981
Approved by: https://github.com/jithunnair-amd, https://github.com/malfet
Summary:
Replace _dynamo.config with an object instead of module
Current usage patterns of setting and reading fields on config will work
unchanged.
Only changes needed going forward:
1. import torch._dynamo.config will not work. However, just doing
import torch._dynamo is sufficient to access dynamo config
as torch._dynamo.config.
2. Files inside of _dynamo folder need to access config via
from torch._dynamo.config_util import config instead of
from torch._dynamo import config. Because _dynamo/__init__.py
imports some of the files so it would be circular import.
Test Plan:
Reviewers:
Subscribers:
Tasks:
Tags:
Fixes #ISSUE_NUMBER
Pull Request resolved: https://github.com/pytorch/pytorch/pull/96455
Approved by: https://github.com/williamwen42
