[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