Adds a ruff lint rule to ban raising raw exceptions. Most of these should at the very least be runtime exception, value errors, type errors or some other errors. There are hundreds of instance of these bad exception types already in the codebase, so I have noqa'd most of them. Hopefully this error code will get commiters to rethink what exception type they should raise when they submit a PR.
I also encourage people to gradually go and fix all the existing noqas that have been added so they can be removed overtime and our exception typing can be improved.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/124570
Approved by: https://github.com/ezyang
Fixes#112589
Fixed errors relating to pydocstyle in the following files. The remaining errors are related to docstrings at the module level and at methods within each module (see details below)
pydocstyle torch/cuda/_utils.py --count
before: 3
after: 0
pydocstyle torch/cuda/jiterator.py --count
before: 3
after: 1
**remaining errors:**
```
torch/cuda/jiterator.py:1 at module level:
D100: Missing docstring in public module
```
pydocstyle torch/cuda/graphs.py --count
before: 25
after: 7
**remaining errors:**
```
torch/cuda/graphs.py:1 at module level:
D100: Missing docstring in public module
torch/cuda/graphs.py:54 in public method `__new__`:
D102: Missing docstring in public method
torch/cuda/graphs.py:108 in public method `debug_dump`:
D205: 1 blank line required between summary line and description (found 0)
torch/cuda/graphs.py:108 in public method `debug_dump`:
D400: First line should end with a period (not ':')
torch/cuda/graphs.py:150 in public method `__init__`:
D107: Missing docstring in __init__
torch/cuda/graphs.py:172 in public method `__enter__`:
D105: Missing docstring in magic method
torch/cuda/graphs.py:186 in public method `__exit__`:
D105: Missing docstring in magic method
```
pydocstyle torch/cuda/_sanitizer.py --count
before: 35
after: 31
**remaining errors:**
```
torch/cuda/_sanitizer.py:43 in public class `AccessType`:
D101: Missing docstring in public class
torch/cuda/_sanitizer.py:47 in public method `__str__`:
D105: Missing docstring in magic method
torch/cuda/_sanitizer.py:84 in public method `__init__`:
D107: Missing docstring in __init__
torch/cuda/_sanitizer.py:96 in public method `__str__`:
D105: Missing docstring in magic method
torch/cuda/_sanitizer.py:139 in public method `__init__`:
D107: Missing docstring in __init__
torch/cuda/_sanitizer.py:142 in public method `__str__`:
D105: Missing docstring in magic method
torch/cuda/_sanitizer.py:218 in public class `StreamSynchronizations`:
D101: Missing docstring in public class
torch/cuda/_sanitizer.py:219 in public method `__init__`:
D107: Missing docstring in __init__
torch/cuda/_sanitizer.py:256 in public method `create_stream`:
D102: Missing docstring in public method
torch/cuda/_sanitizer.py:268 in public method `create_event`:
D102: Missing docstring in public method
torch/cuda/_sanitizer.py:272 in public method `delete_event`:
D102: Missing docstring in public method
torch/cuda/_sanitizer.py:276 in public method `update_seq_num`:
D102: Missing docstring in public method
torch/cuda/_sanitizer.py:280 in public method `record_state`:
D102: Missing docstring in public method
torch/cuda/_sanitizer.py:291 in public method `stream_wait_for_event`:
D102: Missing docstring in public method
torch/cuda/_sanitizer.py:298 in public method `all_streams_wait_for_event`:
D102: Missing docstring in public method
torch/cuda/_sanitizer.py:307 in public method `all_streams_wait_for_stream`:
D102: Missing docstring in public method
torch/cuda/_sanitizer.py:316 in public method `sync_all_streams`:
D102: Missing docstring in public method
torch/cuda/_sanitizer.py:323 in public method `is_ordered_after`:
D102: Missing docstring in public method
torch/cuda/_sanitizer.py:339 in public method `__init__`:
D107: Missing docstring in __init__
torch/cuda/_sanitizer.py:460 in public function `zip_by_key`:
D103: Missing docstring in public function
torch/cuda/_sanitizer.py:466 in public function `zip_arguments`:
D103: Missing docstring in public function
torch/cuda/_sanitizer.py:478 in public class `ArgumentHandler`:
D101: Missing docstring in public class
torch/cuda/_sanitizer.py:479 in public method `__init__`:
D107: Missing docstring in __init__
torch/cuda/_sanitizer.py:505 in public method `parse_inputs`:
D102: Missing docstring in public method
torch/cuda/_sanitizer.py:520 in public method `parse_outputs`:
D102: Missing docstring in public method
torch/cuda/_sanitizer.py:527 in public class `CUDASanitizerDispatchMode`:
D101: Missing docstring in public class
torch/cuda/_sanitizer.py:528 in public method `__init__`:
D107: Missing docstring in __init__
torch/cuda/_sanitizer.py:562 in public method `__torch_dispatch__`:
D105: Missing docstring in magic method
torch/cuda/_sanitizer.py:597 in public method `__init__`:
D107: Missing docstring in __init__
torch/cuda/_sanitizer.py:601 in public method `enable`:
D102: Missing docstring in public method
torch/cuda/_sanitizer.py:605 in public method `__del__`:
D105: Missing docstring in magic method
```
pydocstyle torch/storage.py --count
before: 90
after: 37
**remaining errors:**
```
torch/storage.py:1 at module level:
D100: Missing docstring in public module
torch/storage.py:310 in public class `UntypedStorage`:
D101: Missing docstring in public class
torch/storage.py:311 in public method `__getitem__`:
D105: Missing docstring in magic method
torch/storage.py:317 in public method `is_cuda`:
D102: Missing docstring in public method
torch/storage.py:321 in public method `is_hpu`:
D102: Missing docstring in public method
torch/storage.py:325 in public method `share_memory_`:
D102: Missing docstring in public method
torch/storage.py:444 in public class `TypedStorage`:
D101: Missing docstring in public class
torch/storage.py:453 in public method `fill_`:
D102: Missing docstring in public method
torch/storage.py:458 in public method `__new__`:
D102: Missing docstring in public method
torch/storage.py:530 in public method `__init__`:
D107: Missing docstring in __init__
torch/storage.py:599 in public method `is_cuda`:
D102: Missing docstring in public method
torch/storage.py:604 in public method `is_hpu`:
D102: Missing docstring in public method
torch/storage.py:624 in public method `__len__`:
D105: Missing docstring in magic method
torch/storage.py:653 in public method `__setitem__`:
D105: Missing docstring in magic method
torch/storage.py:681 in public method `__getitem__`:
D105: Missing docstring in magic method
torch/storage.py:715 in public method `copy_`:
D102: Missing docstring in public method
torch/storage.py:723 in public method `nbytes`:
D102: Missing docstring in public method
torch/storage.py:731 in public method `type`:
D102: Missing docstring in public method
torch/storage.py:744 in public method `cuda`:
D102: Missing docstring in public method
torch/storage.py:751 in public method `hpu`:
D102: Missing docstring in public method
torch/storage.py:758 in public method `element_size`:
D102: Missing docstring in public method
torch/storage.py:766 in public method `get_device`:
D102: Missing docstring in public method
torch/storage.py:770 in public method `__str__`:
D105: Missing docstring in magic method
torch/storage.py:781 in public method `__repr__`:
D105: Missing docstring in magic method
torch/storage.py:785 in public method `__iter__`:
D105: Missing docstring in magic method
torch/storage.py:789 in public method `__copy__`:
D105: Missing docstring in magic method
torch/storage.py:793 in public method `__deepcopy__`:
D105: Missing docstring in magic method
torch/storage.py:801 in public method `__sizeof__`:
D105: Missing docstring in magic method
torch/storage.py:877 in public method `device`:
D102: Missing docstring in public method
torch/storage.py:881 in public method `size`:
D102: Missing docstring in public method
torch/storage.py:891 in public method `pickle_storage_type`:
D102: Missing docstring in public method
torch/storage.py:902 in public method `__reduce__`:
D105: Missing docstring in magic method
torch/storage.py:907 in public method `data_ptr`:
D102: Missing docstring in public method
torch/storage.py:915 in public method `resize_`:
D102: Missing docstring in public method
torch/storage.py:931 in public method `from_buffer`:
D102: Missing docstring in public method
torch/storage.py:1032 in public method `from_file`:
D402: First line should not be the function's "signature"
torch/storage.py:1075 in public method `is_shared`:
D102: Missing docstring in public method
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/113227
Approved by: https://github.com/kit1980
### Description
Enables jiterator for ROCm builds. This includes necessary porting when hiprtc and nvrtc behavior differed. This also ported ROCm versus CUDA differences w.r.t. MAX_DIMS and NUM_THREADS from the non-jiterator code paths into jiterator.
### Testing
CI with ciflow/trunk label to force running ROCm workflows that are currently trunk-only.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77982
Approved by: https://github.com/ngimel
You can now do a lot of crazy things about redefining the behavior of an operator, and still be fast in cuda !!!
Example 1: swapping where's branches
```
code_string = "template <typename T> T inverted_where(bool cond, T a, T b){ return !cond ? a : b; }"
jitted_fn = torch.cuda.jiterator._create_jit_fn(code_string)
my_lib = torch.library.Library("aten", "IMPL")
my_lib.impl('aten::where.self', jitted_fn, "CUDA")
# torch.where is now overridden
```
Example 2: approximate gelu with relu
```
code_string = "template <typename T> T fast_gelu(T a){ return a > 0 ? a : 0;}"
jitted_fn = torch.cuda.jiterator._create_jit_fn(code_string)
my_lib = torch.library.Library("aten", "IMPL")
my_lib.impl('aten::gelu', jitted_fn, "CUDA")
# torch.nn.GELU and torch.nn.function.gelu are now overridden
```
Example 3: clipping output for numerical unstable kernels
```
code_string = "template <typename T> T clipped_exp(T a){ return a > T(10.0) ? T(22026.4657948) : exp(a); }"
jitted_fn = torch.cuda.jiterator._create_jit_fn(code_string)
my_lib = torch.library.Library("aten", "IMPL")
my_lib.impl('aten::exp', jitted_fn, "CUDA")
# torch.exp(x) and x.exp() are now overridden
```
Example 4: Simulate buggy hardware behaviors
```
code_string = "template <typename T> T buggy_add(T a, T b){ return a + b + T(1); }"
jitted_fn = torch.cuda.jiterator._create_jit_fn(code_string)
my_lib = torch.library.Library("aten", "IMPL")
my_lib.impl('aten::add.Tensor', jitted_fn, "CUDA")
torch.add(x, y), "x + y" and x.add(y) are now overridden
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77121
Approved by: https://github.com/anjali411
This PR allows user to author a CUDA kernel in python.
```
from torch.cuda.jiterator import create_jit_fn
code_string = "template <typename T> T my_kernel(T x, T y, T alpha) { return -x * y + x - y + alpha; }"
jitted_fn = create_jit_fn(code_string, alpha=0)
a = torch.rand(3, device='cuda')
b = torch.rand(3, device='cuda')
result = jitted_fn(a, b, alpha=1.0)
```
Limitations:
- Only supports elementwise kernel
- 1~8 tensor inputs (empty input, e.g. factory methods, is not supported)
- inputs tensors must live in cuda device
- cpu Scalar is not supported
- kwargs must be pre-declared when calling create_jit_fn
- kwargs must be convertible to at::Scalar, one of float64, int64_t, bool. (complex not support for now)
TODOs:
- [x] consolidate union and c10::variant implementation
- [x] plug into existing op testing framework
- [ ] rename files, place files in the right folder
- [ ] place util functions in the right file
- [x] enforce assumptions in python interface e.g <8 inputs, kwargs types
- [x] Add user-facing documentation
Pull Request resolved: https://github.com/pytorch/pytorch/pull/76394
Approved by: https://github.com/mruberry
