Bump minimal supported Python version from 3.8 to 3.10

.github/scripts/microbench_summary.py

@@ -14,7 +14,6 @@
 import argparse
 import bisect
 from pathlib import Path
-from typing import Dict, List
 
 def main():
     parser = argparse.ArgumentParser(
@@ -214,7 +213,7 @@ def get_op_pattern(base_op_name: str, get_backward: bool) -> tuple:
     else:
         return (base_op_name, f"{base_op_name} ")
 
-def process_l1_loss(content: str, case_name: str, data: List, columns: List):
+def process_l1_loss(content: str, case_name: str, data: list, columns: list):
     shape_matches = list(re.finditer(r"(shape\s*[:=].*?)(?=\n\S|$)", content))
     shape_lines = [match.group(0) for match in shape_matches]
     shape_positions = [match.start() for match in shape_matches]
@@ -281,7 +280,7 @@ def process_l1_loss(content: str, case_name: str, data: List, columns: List):
 
         data.append([record.get(col, "") for col in columns])
 
-def extract_times(content: str, pattern: str, get_backward: bool) -> List:
+def extract_times(content: str, pattern: str, get_backward: bool) -> list:
     lines = content.split('\n')
     results = []
     for line in lines:
@@ -297,8 +296,8 @@ def extract_times(content: str, pattern: str, get_backward: bool) -> List:
 
     return results
 
-def create_record(params: Dict, case_name: str, op_name: str,
-                 backward: str, time_us: float) -> Dict:
+def create_record(params: dict, case_name: str, op_name: str,
+                 backward: str, time_us: float) -> dict:
     return {
         "P": params.get("p", ""),
         **params,
@@ -316,7 +315,7 @@ def convert_to_us(value: float, unit: str) -> float:
         return value * 1_000_000
     return value
 
-def extract_params(text: str) -> Dict:
+def extract_params(text: str) -> dict:
     params = {}
     pairs = re.split(r'[;]', text.strip())
 

.github/scripts/op_perf_comparison.py

@@ -26,7 +26,7 @@ def preprocess_row(row):
 def display_row(record):
     formatted = {}
     for key, value in record.items():
-        if isinstance(value, (list, tuple, dict)):
+        if isinstance(value, list | tuple | dict):
             formatted[key] = str(value)
         elif value == "NULL":
             formatted[key] = "NULL"

.lintrunner.toml

@@ -34,7 +34,7 @@ init_command = [
     'mccabe==0.7.0',
     'pycodestyle==2.11.1',
     'pyflakes==3.1.0',
-    'torchfix==0.4.0 ; python_version >= "3.9" and python_version < "3.13"',
+    'torchfix==0.4.0 ; python_version < "3.13"',
 ]
 
 
@@ -83,11 +83,11 @@ init_command = [
     'python3',
     'tools/linter/adapters/pip_init.py',
     '--dry-run={{DRYRUN}}',
-    'numpy==1.26.4 ; python_version >= "3.9" and python_version <= "3.11"',
+    'numpy==1.26.4 ; python_version <= "3.11"',
     'numpy==2.1.0 ; python_version >= "3.12"',
     'expecttest==0.3.0',
     'mypy==1.13.0',
-    'sympy==1.13.0 ; python_version >= "3.9"',
+    'sympy==1.13.0',
     'types-requests==2.27.25',
     'types-PyYAML==6.0.7',
     'types-tabulate==0.8.8',

mypy-strict.ini

@@ -6,7 +6,7 @@
 # files.
 
 [mypy]
-python_version = 3.8
+python_version = 3.10
 plugins = mypy_plugins/check_mypy_version.py, numpy.typing.mypy_plugin
 
 cache_dir = .mypy_cache/strict

pyproject.toml

@@ -34,6 +34,7 @@ ignore = [
     "B023",
     "B028", # No explicit `stacklevel` keyword argument found
     "B904", # Migrate from TRY200
+    "B905", # Python>=3.10 specific suppressions
     "E402",
     "C408", # C408 ignored because we like the dict keyword argument syntax
     "E501", # E501 is not flexible enough, we're using B950 instead

test/xpu/distributed/test_c10d_ops_xccl.py

@@ -918,7 +918,8 @@ def test_all_to_all_single_none(self):
         out = torch.zeros(self.world_size, 2, dtype=send.dtype).to(device)
         dist.all_to_all_single(out, send)
         self.assertEqual(
-            out.tolist(), list(zip(range(self.world_size), range(self.world_size)))
+            out.tolist(),
+            list(zip(range(self.world_size), range(self.world_size))),
         )
 
 

test/xpu/test_modules_xpu.py

@@ -270,7 +270,7 @@ def _test_multiple_device_transfer(self, device, dtype, module_info, training):
             if torch.cuda.device_count() >= 2:
                 # === test cross-GPU transfer works
                 def _to_device1(objs):
-                    if isinstance(objs, (tuple, list)):
+                    if isinstance(objs, tuple | list):
                         return type(objs)(_to_device1(item) for item in objs)
                     elif isinstance(objs, dict):
                         return {name: _to_device1(item) for name, item in objs.items()}

test/xpu/test_tensor_creation_ops_xpu.py

@@ -7,7 +7,7 @@
 import unittest
 import warnings
 from itertools import combinations, combinations_with_replacement, permutations, product
-from typing import Any, Dict, List, Tuple
+from typing import Any
 
 import numpy as np
 import torch
@@ -4852,11 +4852,11 @@ def test_astensor_consistency(self, device):
             True,
             42,
             1.0,
-            # Homogeneous Lists
+            # Homogeneous lists
             [True, True, False],
             [1, 2, 3, 42],
             [0.0, 1.0, 2.0, 3.0],
-            # Mixed Lists
+            # Mixed lists
             [True, False, 0],
             [0.0, True, False],
             [0, 1.0, 42],
@@ -4894,7 +4894,7 @@ def test_numpy_scalars(self, device):
     def test_default_device(self, device):
         original = torch.arange(5)
 
-        examples: List[Tuple[Any, Dict]] = [
+        examples: list[tuple[Any, dict]] = [
             (3, {}),
             (original, {}),
             (to_numpy(original), {}),

test/xpu/test_torch_xpu.py

@@ -23,7 +23,6 @@
 from functools import partial
 from itertools import chain, combinations, permutations, product
 from multiprocessing.reduction import ForkingPickler
-from typing import Tuple
 
 import numpy as np
 import torch
@@ -120,10 +119,8 @@
     torch._C._get_privateuse1_backend_name(),
 )
 
-from typing import List
 
-
-def my_get_all_device_types_xpu() -> List[str]:
+def my_get_all_device_types_xpu() -> list[str]:
     devices = [
         "cpu",
     ]
@@ -487,7 +484,7 @@ def test_set_storage(self, device, dtype):
 
     def _check_storage_meta(self, s, s_check):
         self.assertTrue(
-            isinstance(s, (torch.UntypedStorage, torch.TypedStorage))
+            isinstance(s, torch.UntypedStorage | torch.TypedStorage)
             and isinstance(s_check, type(s)),
             (
                 "s and s_check must both be one of UntypedStorage or "
@@ -4138,7 +4135,7 @@ def test_errors_index_copy(self, device):
 
     def _prepare_data_for_index_copy_and_add_deterministic(
         self, dim: int, device: torch.device
-    ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+    ) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
         assert dim >= 0 and dim < 3
         a = [5, 4, 3]
         a[dim] = 2000

tools/linter/adapters/_linter.py

@@ -12,7 +12,8 @@
 from functools import cached_property
 from pathlib import Path
 from tokenize import generate_tokens, TokenInfo
-from typing import Any, Iterator, Sequence
+from typing import Any
+from collections.abc import Iterator, Sequence
 from typing_extensions import Never
 
 

tools/linter/adapters/docstring_linter.py

@@ -4,7 +4,8 @@
 import token
 from functools import cached_property
 from pathlib import Path
-from typing import Iterator, Sequence, TYPE_CHECKING
+from typing import TYPE_CHECKING
+from collections.abc import Iterator, Sequence
 
 
 _PARENT = Path(__file__).parent.absolute()