[3/N] Apply py39 ruff fixes (pytorch#142115)

Fixes #ISSUE_NUMBER

Pull Request resolved: pytorch#142115
Approved by: https://github.com/ezyang

Author: cyyever

tools/autograd/gen_annotated_fn_args.py

@@ -20,7 +20,7 @@
 import os
 import textwrap
 from collections import defaultdict
-from typing import Any, Sequence, TYPE_CHECKING
+from typing import Any, TYPE_CHECKING
 
 import torchgen.api.python as python
 from torchgen.context import with_native_function
@@ -39,6 +39,8 @@
 
 
 if TYPE_CHECKING:
+    from collections.abc import Sequence
+
     from torchgen.model import Argument, BaseOperatorName, NativeFunction
 
 

tools/autograd/gen_autograd_functions.py

@@ -7,7 +7,7 @@
 
 from __future__ import annotations
 
-from typing import Sequence
+from typing import TYPE_CHECKING
 
 from torchgen.api.autograd import (
     Derivative,
@@ -47,6 +47,10 @@
 from .gen_inplace_or_view_type import VIEW_FUNCTIONS
 
 
+if TYPE_CHECKING:
+    from collections.abc import Sequence
+
+
 FUNCTION_DECLARATION = CodeTemplate(
     """\
 #ifdef _WIN32

tools/autograd/gen_python_functions.py

@@ -36,7 +36,7 @@
 import itertools
 import re
 from collections import defaultdict
-from typing import Callable, Iterable, Sequence
+from typing import Callable, TYPE_CHECKING
 
 import yaml
 
@@ -76,6 +76,10 @@
 from .gen_trace_type import should_trace
 
 
+if TYPE_CHECKING:
+    from collections.abc import Iterable, Sequence
+
+
 #
 # declarations blocklist
 # We skip codegen for these functions, for various reasons.

tools/autograd/gen_trace_type.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 import itertools
-from typing import Sequence
+from typing import TYPE_CHECKING
 
 from torchgen.api import cpp
 from torchgen.api.types import DispatcherSignature
@@ -11,6 +11,10 @@
 from torchgen.utils import FileManager
 
 
+if TYPE_CHECKING:
+    from collections.abc import Sequence
+
+
 # Note [Manual Backend kernels]
 # For these ops, we want to manually register to dispatch key Backend and
 # skip codegen-ed registeration to all keys before Backend.

tools/autograd/gen_variable_type.py

@@ -29,7 +29,7 @@
 from __future__ import annotations
 
 import re
-from typing import Callable, Sequence
+from typing import Callable, TYPE_CHECKING
 
 from torchgen.api import cpp
 from torchgen.api.autograd import (
@@ -105,6 +105,10 @@
 )
 
 
+if TYPE_CHECKING:
+    from collections.abc import Sequence
+
+
 # We don't set or modify grad_fn on these methods. Generally, they return
 # tensors that have requires_grad=False. In-place functions listed here will
 # not examine or modify requires_grad or grad_fn.

tools/autograd/load_derivatives.py

@@ -6,8 +6,8 @@
 from __future__ import annotations
 
 import re
-from collections import defaultdict
-from typing import Any, Counter, Dict, Sequence, Set, Tuple
+from collections import Counter, defaultdict
+from typing import Any, TYPE_CHECKING
 
 import yaml
 
@@ -53,7 +53,11 @@
 from torchgen.yaml_utils import YamlLoader
 
 
-DerivativeRet = Tuple[Dict[FunctionSchema, Dict[str, DifferentiabilityInfo]], Set[str]]
+if TYPE_CHECKING:
+    from collections.abc import Sequence
+
+
+DerivativeRet = tuple[dict[FunctionSchema, dict[str, DifferentiabilityInfo]], set[str]]
 
 _GLOBAL_LOAD_DERIVATIVE_CACHE: dict[tuple[str, str], DerivativeRet] = {}
 
@@ -631,7 +635,7 @@ def set_up_derivatives(
             raise RuntimeError(
                 f"Not supported: for {specification},"
                 f"output_differentiability must either be "
-                f"List[bool] or a List[str] where each str is a "
+                f"list[bool] or a list[str] where each str is a "
                 f"condition. In the case where it is a condition, "
                 f"we only support single-output functions. "
                 f"Please file us an issue. "

tools/code_analyzer/gen_op_registration_allowlist.py

@@ -12,12 +12,11 @@
 
 import argparse
 from collections import defaultdict
-from typing import Dict, Set
 
 import yaml
 
 
-DepGraph = Dict[str, Set[str]]
+DepGraph = dict[str, set[str]]
 
 
 def canonical_name(opname: str) -> str:

tools/code_coverage/package/tool/print_report.py

@@ -2,13 +2,13 @@
 
 import os
 import subprocess
-from typing import IO, Tuple
+from typing import IO
 
 from ..oss.utils import get_pytorch_folder
 from ..util.setting import SUMMARY_FOLDER_DIR, TestList, TestStatusType
 
 
-CoverageItem = Tuple[str, float, int, int]
+CoverageItem = tuple[str, float, int, int]
 
 
 def key_by_percentage(x: CoverageItem) -> float:

tools/code_coverage/package/tool/summarize_jsons.py

@@ -31,7 +31,7 @@
     from .parser.coverage_record import CoverageRecord
 
 
-# coverage_records: Dict[str, LineInfo] = {}
+# coverage_records: dict[str, LineInfo] = {}
 covered_lines: dict[str, set[int]] = {}
 uncovered_lines: dict[str, set[int]] = {}
 tests_type: TestStatusType = {"success": set(), "partial": set(), "fail": set()}

tools/code_coverage/package/util/setting.py

@@ -2,7 +2,6 @@
 
 import os
 from enum import Enum
-from typing import Dict, List, Set
 
 
 # <project folder>
@@ -43,8 +42,8 @@ def __init__(
         self.test_type = test_type
 
 
-TestList = List[Test]
-TestStatusType = Dict[str, Set[str]]
+TestList = list[Test]
+TestStatusType = dict[str, set[str]]
 
 
 # option

tools/extract_scripts.py

@@ -6,13 +6,13 @@
 import re
 import sys
 from pathlib import Path
-from typing import Any, Dict
+from typing import Any
 from typing_extensions import TypedDict  # Python 3.11+
 
 import yaml
 
 
-Step = Dict[str, Any]
+Step = dict[str, Any]
 
 
 class Script(TypedDict):

tools/jit/gen_unboxing.py

@@ -7,7 +7,7 @@
 import sys
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Literal, Sequence, TYPE_CHECKING
+from typing import Literal, TYPE_CHECKING
 
 import yaml
 
@@ -22,6 +22,8 @@
 
 
 if TYPE_CHECKING:
+    from collections.abc import Sequence
+
     from torchgen.selective_build.selector import SelectiveBuilder
 
 

tools/linter/adapters/no_workflows_on_fork.py

@@ -22,7 +22,7 @@
 import re
 from enum import Enum
 from pathlib import Path
-from typing import Any, Callable, Dict, List, NamedTuple, Optional
+from typing import Any, Callable, NamedTuple, Optional
 
 from yaml import load
 
@@ -77,11 +77,11 @@ def gen_lint_message(
     )
 
 
-def check_file(filename: str) -> List[LintMessage]:
+def check_file(filename: str) -> list[LintMessage]:
     logging.debug("Checking file %s", filename)
 
     workflow = load_yaml(Path(filename))
-    bad_jobs: Dict[str, Optional[str]] = {}
+    bad_jobs: dict[str, Optional[str]] = {}
     if type(workflow) is not dict:
         return []
 
@@ -106,7 +106,7 @@ def check_file(filename: str) -> List[LintMessage]:
             pass
         else:
             if_statement = str(if_statement)
-            valid_checks: List[Callable[[str], bool]] = [
+            valid_checks: list[Callable[[str], bool]] = [
                 lambda x: "github.repository == 'pytorch/pytorch'" in x
                 and "github.event_name != 'schedule' || github.repository == 'pytorch/pytorch'"
                 not in x,

tools/linter/adapters/workflow_consistency_linter.py

@@ -11,11 +11,15 @@
 from collections import defaultdict
 from enum import Enum
 from pathlib import Path
-from typing import Any, Iterable, NamedTuple
+from typing import Any, NamedTuple, TYPE_CHECKING
 
 from yaml import dump, load
 
 
+if TYPE_CHECKING:
+    from collections.abc import Iterable
+
+
 # Safely load fast C Yaml loader/dumper if they are available
 try:
     from yaml import CSafeLoader as Loader

tools/nightly.py

@@ -50,16 +50,11 @@
 from datetime import datetime
 from pathlib import Path
 from platform import system as platform_system
-from typing import (
-    Any,
-    Callable,
-    cast,
-    Generator,
-    Iterable,
-    Iterator,
-    NamedTuple,
-    TypeVar,
-)
+from typing import Any, Callable, cast, NamedTuple, TYPE_CHECKING, TypeVar
+
+
+if TYPE_CHECKING:
+    from collections.abc import Generator, Iterable, Iterator
 
 
 try:

tools/nightly_hotpatch.py

@@ -7,7 +7,7 @@
 import sys
 import tempfile
 import urllib.request
-from typing import cast, List, NoReturn, Optional
+from typing import cast, NoReturn, Optional
 
 
 def parse_arguments() -> argparse.Namespace:
@@ -74,7 +74,7 @@ def get_pytorch_path() -> str:
     try:
         import torch
 
-        torch_paths: List[str] = cast(List[str], torch.__path__)
+        torch_paths: list[str] = cast(list[str], torch.__path__)
         torch_path: str = torch_paths[0]
         parent_path: str = os.path.dirname(torch_path)
         print(f"PyTorch is installed at: {torch_path}")
@@ -114,9 +114,10 @@ def download_patch(pr_number: int, repo_url: str, download_dir: str) -> str:
     patch_file = os.path.join(download_dir, f"pr-{pr_number}.patch")
     print(f"Downloading PR #{pr_number} patch from {patch_url}...")
     try:
-        with urllib.request.urlopen(patch_url) as response, open(
-            patch_file, "wb"
-        ) as out_file:
+        with (
+            urllib.request.urlopen(patch_url) as response,
+            open(patch_file, "wb") as out_file,
+        ):
             shutil.copyfileobj(response, out_file)
         if not os.path.isfile(patch_file):
             print(f"Failed to download patch for PR #{pr_number}")

tools/onnx/gen_diagnostics.py

@@ -17,7 +17,8 @@
 import string
 import subprocess
 import textwrap
-from typing import Any, Mapping, Sequence
+from collections.abc import Mapping, Sequence
+from typing import Any
 
 import yaml
 
@@ -56,7 +57,7 @@ def format(  # type: ignore[override]
         self,
         level: infra.Level,
         {message_arguments}
-    ) -> Tuple[infra.Rule, infra.Level, str]:
+    ) -> tuple[infra.Rule, infra.Level, str]:
         \"\"\"Returns a tuple of (Rule, Level, message) for this Rule.
 
         Message template: {message_template}

tools/packaging/split_wheel.py

@@ -26,7 +26,7 @@
 import subprocess
 import sys
 from pathlib import Path
-from typing import Dict, List, Optional
+from typing import Optional
 
 
 logging.basicConfig(
@@ -56,7 +56,7 @@ def requirements_installed() -> bool:
         return False
 
 
-def setup_py(cmd_args: List[str], extra_env: Optional[Dict[str, str]] = None) -> None:
+def setup_py(cmd_args: list[str], extra_env: Optional[dict[str, str]] = None) -> None:
     if extra_env is None:
         extra_env = {}
     cmd = [sys.executable, str(SETUP_PY_PATH), *cmd_args]