I.e. when `MTL_CAPTURE_ENABLED` environment variable is set to 1, one should be able to invoke wrap the code with `torch.mps.profiler.capture_metal` to generate gputrace for shaders invoked inside the context manager.
For example, code below:
```python
import torch
import os
def foo(x):
return x[:,::2].sin() + x[:, 1::2].cos()
if __name__ == "__main__":
os.environ["MTL_CAPTURE_ENABLED"] = "1"
x = torch.rand(32, 1024, device="mps")
with torch.mps.profiler.metal_capture("compiled_shader"):
torch.compile(foo)(x)
```
should capture the execution of a `torch.compile` generated shader
<img width="734" alt="image" src="https://github.com/user-attachments/assets/718ff64e-103b-4b11-b66c-c89cfc770b5d" />
Pull Request resolved: https://github.com/pytorch/pytorch/pull/144561
Approved by: https://github.com/manuelcandales
ghstack dependencies: #144559, #144560
Add non-package python modules to the public API checks.
The original change is to remove the `ispkg` check in this line
https://github.com/pytorch/pytorch/blob/main/docs/source/conf.py#L518
Everything else is to add the appropriate modules to the rst files, make sure every module we provide can be imported (fixed by either making optional dependencies optional or just deleting files that have been un-importable for 3 years), make API that are both modules and functions (like torch.autograd.gradcheck) properly rendered on the docs website without confusion and add every non-documented API to the allow list (~3k of them).
Next steps will be to try and fix these missing docs
Pull Request resolved: https://github.com/pytorch/pytorch/pull/110568
Approved by: https://github.com/zou3519
- Implement `MPSEventPool` to recycle events.
- Implement python bindings with `torch.mps.Event` class using the MPSEventPool backend. The current member functions of the Event class are `record()`, `wait()`, `synchronize()`, `query()`, and `elapsed_time()`.
- Add API to measure elapsed time between two event recordings.
- Added documentation for Event class to `mps.rst`.
- Added test case to `test_mps.py`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/102121
Approved by: https://github.com/albanD, https://github.com/kulinseth
- To check for Memory Leaks in `test_mps.py`, set the env-variable `PYTORCH_TEST_MPS_MEM_LEAK_CHECK=1` when running test_mps.py (used CUDA code as reference).
- Added support for the following new python interfaces in MPS module:
`torch.mps.[empty_cache(), set_per_process_memory_fraction(), current_allocated_memory(), driver_allocated_memory()]`
- Renamed `_is_mps_on_macos_13_or_newer()` to `_mps_is_on_macos_13_or_newer()`, and `_is_mps_available()` to `_mps_is_available()` to be consistent in naming with prefix `_mps`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94646
Approved by: https://github.com/malfet
- This PR is a prerequisite for the upcoming Memory Leak Detection PR.
- Enable global manual seeding via `torch.manual_seed()` + test case
- Add `torch.mps.synchronize()` to wait for MPS stream to finish + test case
- Enable the following python interfaces for MPS:
`torch.mps.[get_rng_state(), set_rng_state(), synchronize(), manual_seed(), seed()]`
- Added some test cases in test_mps.py
- Added `mps.rst` to document the `torch.mps` module.
- Fixed the failure with `test_public_bindings.py`
Description of new files added:
- `torch/csrc/mps/Module.cpp`: implements `torch._C` module functions for `torch.mps` and `torch.backends.mps`.
- `torch/mps/__init__.py`: implements Python bindings for `torch.mps` module.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94417
Approved by: https://github.com/albanD
- This PR is a prerequisite for the upcoming Memory Leak Detection PR.
- Enable global manual seeding via `torch.manual_seed()` + test case
- Add `torch.mps.synchronize()` to wait for MPS stream to finish + test case
- Enable the following python interfaces for MPS:
`torch.mps.[get_rng_state(), set_rng_state(), synchronize(), manual_seed(), seed()]`
- Added some test cases in test_mps.py
- Added `mps.rst` to document the `torch.mps` module.
- Fixed the failure with `test_public_bindings.py`
Description of new files added:
- `torch/csrc/mps/Module.cpp`: implements `torch._C` module functions for `torch.mps` and `torch.backends.mps`.
- `torch/mps/__init__.py`: implements Python bindings for `torch.mps` module.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94417
Approved by: https://github.com/albanD