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Author SHA1 Message Date
PyTorch MergeBot
7614338b69 Revert "Add SVE128 ISA (#158932)" 
This reverts commit 92284fb2ff44f09a9c7df0d8cf6cac9903e376a4.

Reverted https://github.com/pytorch/pytorch/pull/158932 on behalf of https://github.com/malfet due to Hmm, but from OSS point of view, this is a no-op ([comment](https://github.com/pytorch/pytorch/pull/158932#issuecomment-3387961238))
 2025-10-10 01:17:02 +00:00
Nicolas De Carli
92284fb2ff Add SVE128 ISA (#158932) 
Summary: Partly Importing and adapting https://github.com/pytorch/pytorch/pull/138388, adding SVE128 as ISA.

Intention is to add SVE128 translation layers for Vectorized data types.
Idea is to have 1 PR per file, aside from the current one, plus a last one modifying cmake files to enable the new ISA selectively.

Tested current changes on a nightly run, to verify no regressions occur on systems leveraging SVE256.

No regressions spotted when running test_ops.py, a set of 34k unit tests. A machine leveraging SVE128 was used towards this testing.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/158932
Approved by: https://github.com/malfet
 2025-09-29 14:49:19 +00:00
maajidkhann
5a6ddbcc3b Extending the Pytorch vec backend for SVE (ARM) (#119571) 
**Motivation:**
In Pytorch, Aten vectorization supports multiple platforms, including x86 and Arm, as well as multiple data types. It provides a generic implementation of Vector (Vec) type that allows the programmer to write code packing various primitives (such as floats) within 256bit & 512bits registers. It can be extended to support other ISAs easily by adding more VecISA sub-classes.

**Reference Link:** https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/cpu/vec

**This PR:**

* Our goal with this contribution is to add support for SVE backend for Vec in the Aten vectorization for CPU backend which can be benefitted by any ARM architecture supported CPU's that supports SVE.

* More about SVE ISA for ARM: [https://developer.arm.com/Architectures/Scalable Vector Extensions](https://developer.arm.com/Architectures/Scalable%20Vector%20Extensions)

* We are using the ARM C Language Extensions for SVE (https://developer.arm.com/documentation/102699/0100/Optimizing-with-intrinsics ) to accelerate performance for various operators in the SVE backend for Vec.

* Currently we are adding support only for SVE ISA with the vector length of 256 bits (SVE 256). In future, we plan to extend this SVE support for other vector lengths as well.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/119571
Approved by: https://github.com/malfet, https://github.com/snadampal

Co-authored-by: Divya Kotadiya <divya.kotadiya@fujitsu.com>
 2024-09-18 18:59:10 +00:00
Xuehai Pan
f3fce597e9 [BE][Easy][17/19] enforce style for empty lines in import segments in torch/[a-c]*/ and torch/[e-n]*/ (#129769) 
See https://github.com/pytorch/pytorch/pull/129751#issue-2380881501. Most changes are auto-generated by linter.

You can review these PRs via:

```bash
git diff --ignore-all-space --ignore-blank-lines HEAD~1
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/129769
Approved by: https://github.com/ezyang
 2024-08-04 10:24:09 +00:00
zabboud
7f9fafed53 Resolve docstring errors in throughput_benchmark.py, weak.py, _traceback.py, file_baton.py, _contextlib.py, _device.py, cpp_backtrace.py, bundled_inputs.py, run_cpu.py, hooks.py, mobile_optimizer.py, _freeze.py, __init__.py, mkldnn.py, dlpack.py (#113311) 
Fixes #112633

Fixed errors relating to pydocstyle in the following files. The remaining errors are not covered in this issue. `torch/utils/dlpack.py` was not modified as the errors are relating to the function signature in the first line in the docstring which must be maintained as is for proper Sphinx interpretation.

```python
def from_dlpack(ext_tensor: Any) -> 'torch.Tensor':
    """from_dlpack(ext_tensor) -> Tensor
         .....
    """
```

pydocstyle torch/utils/_contextlib.py --count
before: 4
after: 0

pydocstyle torch/backends/mps/__init__.py --count
before: 8
after: 1

**remaining errors**
```
torch/backends/mps/__init__.py:1 at module level:
        D104: Missing docstring in public package
```

pydocstyle torch/backends/xeon/run_cpu.py --count
before: 13
after: 1

**remaining errors**
```
torch/backends/xeon/run_cpu.py:864 in public function `main`:
        D103: Missing docstring in public function
```

pydocstyle torch/backends/cpu/__init__.py --count
before: 2
after: 1

**remaining errors**
```
torch/backends/cpu/__init__.py:1 at module level:
        D104: Missing docstring in public package
```

pydocstyle torch/utils/cpp_backtrace.py --count
before: 4
after: 1

**remaining errors**
```
torch/utils/cpp_backtrace.py:1 at module level:
        D100: Missing docstring in public module
```

pydocstyle torch/utils/bundled_inputs.py --count
before: 8
after: 1

**remaining errors**
```
torch/utils/bundled_inputs.py:1 at module level:
        D100: Missing docstring in public module
```

pydocstyle torch/utils/file_baton.py --count
before: 8
after: 1

**remaining errors**
```
torch/utils/file_baton.py:1 at module level:
        D100: Missing docstring in public module
```

pydocstyle torch/utils/mobile_optimizer.py --count
before: 6
after: 1

**remaining errors**
```
torch/utils/mobile_optimizer.py:8 in public class `LintCode`:
        D101: Missing docstring in public class
```

pydocstyle torch/backends/opt_einsum/__init__.py --count
before: 7
after: 5

**remaining errors**
```
torch/backends/opt_einsum/__init__.py:1 at module level:
        D104: Missing docstring in public package
torch/backends/opt_einsum/__init__.py:67 in public function `set_flags`:
        D103: Missing docstring in public function
torch/backends/opt_einsum/__init__.py:77 in public function `flags`:
        D103: Missing docstring in public function
torch/backends/opt_einsum/__init__.py:93 in public class `OptEinsumModule`:
        D101: Missing docstring in public class
torch/backends/opt_einsum/__init__.py:94 in public method `__init__`:
        D107: Missing docstring in __init__
```

pydocstyle torch/utils/_device.py --count
before:  9
after: 6

**remaining errors**
```
torch/utils/_device.py:58 in public class `DeviceContext`:
        D101: Missing docstring in public class
torch/utils/_device.py:59 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/_device.py:62 in public method `__enter__`:
        D105: Missing docstring in magic method
torch/utils/_device.py:68 in public method `__exit__`:
        D105: Missing docstring in magic method
torch/utils/_device.py:73 in public method `__torch_function__`:
        D105: Missing docstring in magic method
torch/utils/_device.py:80 in public function `device_decorator`:
        D103: Missing docstring in public function

```

pydocstyle torch/utils/_freeze.py --count
before: 15
after: 7

**remaining errors**
```
torch/utils/_freeze.py:77 in public function `indent_msg`:
        D103: Missing docstring in public function
torch/utils/_freeze.py:89 in public class `FrozenModule`:
        D101: Missing docstring in public class
torch/utils/_freeze.py:100 in public class `Freezer`:
        D101: Missing docstring in public class
torch/utils/_freeze.py:101 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/_freeze.py:106 in public method `msg`:
        D102: Missing docstring in public method
torch/utils/_freeze.py:185 in public method `get_module_qualname`:
        D102: Missing docstring in public method
torch/utils/_freeze.py:206 in public method `compile_string`:
        D102: Missing docstring in public method

```

pydocstyle torch/utils/throughput_benchmark.py --count
before: 25
after: 8
**remaining errors**
```
torch/utils/throughput_benchmark.py:1 at module level:
        D100: Missing docstring in public module
torch/utils/throughput_benchmark.py:27 in public class `ExecutionStats`:
        D101: Missing docstring in public class
torch/utils/throughput_benchmark.py:28 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/throughput_benchmark.py:33 in public method `latency_avg_ms`:
        D102: Missing docstring in public method
torch/utils/throughput_benchmark.py:37 in public method `num_iters`:
        D102: Missing docstring in public method
torch/utils/throughput_benchmark.py:46 in public method `total_time_seconds`:
        D102: Missing docstring in public method
torch/utils/throughput_benchmark.py:50 in public method `__str__`:
        D105: Missing docstring in magic method
torch/utils/throughput_benchmark.py:94 in public method `__init__`:
        D107: Missing docstring in __init__

```

pydocstyle torch/utils/hooks.py --count

before: 14
after: 11

**remaining errors**
```
torch/utils/hooks.py:1 at module level:
        D100: Missing docstring in public module
torch/utils/hooks.py:23 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/hooks.py:34 in public method `remove`:
        D102: Missing docstring in public method
torch/utils/hooks.py:44 in public method `__getstate__`:
        D105: Missing docstring in magic method
torch/utils/hooks.py:50 in public method `__setstate__`:
        D105: Missing docstring in magic method
torch/utils/hooks.py:64 in public method `__enter__`:
        D105: Missing docstring in magic method
torch/utils/hooks.py:67 in public method `__exit__`:
        D105: Missing docstring in magic method
torch/utils/hooks.py:82 in public function `warn_if_has_hooks`:
        D103: Missing docstring in public function
torch/utils/hooks.py:103 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/hooks.py:188 in public method `setup_input_hook`:
        D102: Missing docstring in public method
torch/utils/hooks.py:197 in public method `setup_output_hook`:
        D102: Missing docstring in public method
```

pydocstyle torch/utils/_traceback.py --count
before: 19
after: 14

**remaining errors**
```
torch/utils/_traceback.py:47 in public function `report_compile_source_on_error`:
        D103: Missing docstring in public function
torch/utils/_traceback.py:160 in public class `CapturedTraceback`:
        D101: Missing docstring in public class
torch/utils/_traceback.py:163 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/_traceback.py:167 in public method `cleanup`:
        D102: Missing docstring in public method
torch/utils/_traceback.py:170 in public method `summary`:
        D102: Missing docstring in public method
torch/utils/_traceback.py:182 in public method `__getstate__`:
        D105: Missing docstring in magic method
torch/utils/_traceback.py:190 in public method `extract`:
        D205: 1 blank line required between summary line and description (found 0)
torch/utils/_traceback.py:190 in public method `extract`:
        D400: First line should end with a period (not 't')
torch/utils/_traceback.py:213 in public method `format`:
        D205: 1 blank line required between summary line and description (found 0)
torch/utils/_traceback.py:213 in public method `format`:
        D400: First line should end with a period (not 'f')
torch/utils/_traceback.py:213 in public method `format`:
        D401: First line should be in imperative mood (perhaps 'Format', not 'Formats')
torch/utils/_traceback.py:224 in public method `format_all`:
        D200: One-line docstring should fit on one line with quotes (found 3)
torch/utils/_traceback.py:247 in private function `_extract_symbolized_tb`:
        D205: 1 blank line required between summary line and description (found 0)
torch/utils/_traceback.py:247 in private function `_extract_symbolized_tb`:
        D400: First line should end with a period (not 'f')
```

pydocstyle torch/utils/mkldnn.py --count
before: 28
after: 26

**remaining errors**
```
torch/utils/mkldnn.py:1 at module level:
        D100: Missing docstring in public module
torch/utils/mkldnn.py:4 in public class `MkldnnLinear`:
        D101: Missing docstring in public class
torch/utils/mkldnn.py:5 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/mkldnn.py:19 in public method `__getstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:23 in public method `__setstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:29 in public method `forward`:
        D102: Missing docstring in public method
torch/utils/mkldnn.py:75 in public class `MkldnnConv1d`:
        D101: Missing docstring in public class
torch/utils/mkldnn.py:76 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/mkldnn.py:82 in public method `__setstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:88 in public class `MkldnnConv2d`:
        D101: Missing docstring in public class
torch/utils/mkldnn.py:89 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/mkldnn.py:100 in public method `__setstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:110 in public class `MkldnnConv3d`:
        D101: Missing docstring in public class
torch/utils/mkldnn.py:111 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/mkldnn.py:122 in public method `__setstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:133 in public class `MkldnnBatchNorm`:
        D101: Missing docstring in public class
torch/utils/mkldnn.py:136 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/mkldnn.py:155 in public method `__getstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:163 in public method `__setstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:171 in public method `forward`:
        D102: Missing docstring in public method
torch/utils/mkldnn.py:184 in public class `MkldnnPrelu`:
        D101: Missing docstring in public class
torch/utils/mkldnn.py:185 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/mkldnn.py:190 in public method `__getstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:194 in public method `__setstate__`:
        D105: Missing docstring in magic method
torch/utils/mkldnn.py:199 in public method `forward`:
        D102: Missing docstring in public method
torch/utils/mkldnn.py:205 in public function `to_mkldnn`:
        D103: Missing docstring in public function
```

pydocstyle torch/utils/weak.py --count
before: 32
after: 30

**remaining errors**
```
torch/utils/weak.py:1 at module level:
        D100: Missing docstring in public module
torch/utils/weak.py:42 in public class `WeakIdRef`:
        D101: Missing docstring in public class
torch/utils/weak.py:45 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/weak.py:54 in public method `__call__`:
        D102: Missing docstring in public method
torch/utils/weak.py:61 in public method `__hash__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:64 in public method `__eq__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:84 in public class `WeakIdKeyDictionary`:
        D101: Missing docstring in public class
torch/utils/weak.py:87 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/weak.py:131 in public method `__delitem__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:135 in public method `__getitem__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:138 in public method `__len__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:145 in public method `__repr__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:148 in public method `__setitem__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:151 in public method `copy`:
        D102: Missing docstring in public method
torch/utils/weak.py:162 in public method `__deepcopy__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:172 in public method `get`:
        D102: Missing docstring in public method
torch/utils/weak.py:175 in public method `__contains__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:182 in public method `items`:
        D102: Missing docstring in public method
torch/utils/weak.py:189 in public method `keys`:
        D102: Missing docstring in public method
torch/utils/weak.py:198 in public method `values`:
        D102: Missing docstring in public method
torch/utils/weak.py:216 in public method `popitem`:
        D102: Missing docstring in public method
torch/utils/weak.py:224 in public method `pop`:
        D102: Missing docstring in public method
torch/utils/weak.py:228 in public method `setdefault`:
        D102: Missing docstring in public method
torch/utils/weak.py:231 in public method `update`:
        D102: Missing docstring in public method
torch/utils/weak.py:241 in public method `__ior__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:245 in public method `__or__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:252 in public method `__ror__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:262 in public method `__eq__`:
        D105: Missing docstring in magic method
torch/utils/weak.py:276 in public method `__init__`:
        D107: Missing docstring in __init__
torch/utils/weak.py:280 in public method `__call__`:
        D102: Missing docstring in public method

```

@mikaylagawarecki @jbschlosser @svekars
Pull Request resolved: https://github.com/pytorch/pytorch/pull/113311
Approved by: https://github.com/ezyang
 2023-11-15 17:40:04 +00:00
Edward Z. Yang
3bf922a6ce Apply UFMT to low traffic torch modules (#106249) 
Signed-off-by: Edward Z. Yang <ezyang@meta.com>

Pull Request resolved: https://github.com/pytorch/pytorch/pull/106249
Approved by: https://github.com/Skylion007
 2023-07-29 23:37:30 +00:00
vfdev-5
6a12f10b08 Publicly exposing torch.backends.cpu.get_cpu_capability() (#100164) 
Description:

- As suggested by Nikita, created `torch.backends.cpu` submodule and exposed `get_cpu_capability`.

- In torchvision Resize method we want to know current cpu capability in order to pick appropriate codepath depending on cpu capablities

Newly coded vectorized resize of uint8 images on AVX2 supported CPUs is now faster than older way (uint8->float->resize->uint8). However, on non-avx hardware (e.g. Mac M1) certain configs are slower using native uint8.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/100164
Approved by: https://github.com/albanD, https://github.com/malfet
 2023-05-03 19:02:07 +00:00