mirror of
https://github.com/pytorch/pytorch.git
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a43c4c3972
Continued code migration to enable ruff `UP035`. Most changes are about moving `Callable` from `typing` to `from collections.abc`. Pull Request resolved: https://github.com/pytorch/pytorch/pull/164423 Approved by: https://github.com/ezyang
452 lines
13 KiB
Python
452 lines
13 KiB
Python
import enum
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from collections.abc import Callable
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from typing import Any, Optional, TypeAlias
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import torch
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# TODO: We should move the `GuardManagerType`
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# defined in `guards.py` here and update other
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# imports
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GuardManagerType: TypeAlias = enum.Enum
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class GlobalStateGuard:
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def check(self) -> bool: ...
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def reason(self) -> str: ...
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class LeafGuard:
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def verbose_code_parts(self) -> list[str]: ...
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class RelationalGuard: ...
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class GuardDebugInfo:
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verbose_code_parts: list[str]
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result: bool
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num_guards_executed: int
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class GuardManager:
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def check(self, value: Any) -> bool: ...
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def check_verbose(self, value: Any) -> GuardDebugInfo: ...
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# Accessors
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def globals_dict_manager(
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self,
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f_globals: dict[str, Any],
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def framelocals_manager(
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self,
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key: tuple[str, int],
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def dict_getitem_manager(
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self,
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key: Any,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def grad_manager(
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self,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def generic_getattr_manager(
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self,
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attr: str,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def getitem_manager(
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self,
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key: Any,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def get_generic_dict_manager(
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self,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def list_getitem_manager(
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self,
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key: Any,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def tuple_getitem_manager(
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self,
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key: Any,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def set_getitem_manager(
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self,
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index: Any,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def func_defaults_manager(
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self,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def func_kwdefaults_manager(
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self,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def tuple_iterator_getitem_manager(
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self,
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index: Any,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def weakref_call_manager(
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self,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def call_function_no_args_manager(
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self,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def global_weakref_manager(
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self,
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global_name: str,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def type_manager(
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self,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def getattr_manager(
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self,
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attr: str,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def tensor_property_size_manager(
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self,
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idx: int,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def tensor_property_shape_manager(
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self,
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idx: int,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def tensor_property_storage_offset_manager(
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self,
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idx: int,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def indexed_manager(
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self,
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idx: int,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def lambda_manager(
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self,
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python_lambda: Callable[..., Any],
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def get_root(self) -> RootGuardManager: ...
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def get_source(self) -> str: ...
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def fail_count(self) -> int: ...
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def get_child_managers(self) -> list[GuardManager]: ...
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def repr(self) -> str: ...
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def type_of_guarded_value(self) -> str: ...
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def get_leaf_guards(self) -> list[LeafGuard]: ...
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def get_accessors(self) -> list[GuardManager]: ...
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def is_guarded_value_immutable(self) -> bool: ...
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def is_tag_safe(self) -> bool: ...
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def is_tag_safe_root(self) -> bool: ...
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def has_no_accessors(self) -> bool: ...
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def has_object_aliasing_guard(self) -> bool: ...
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def get_type_of_guarded_value(self) -> type: ...
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def type_dict_manager(
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self,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def type_mro_manager(
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self,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def code_manager(
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self,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def closure_manager(
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self,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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# Leaf guards
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def add_lambda_guard(
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self, user_lambda: Callable[..., Any], verbose_code_parts: list[str]
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) -> None: ...
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def add_id_match_guard(
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self, id_val: int, verbose_code_parts: list[str]
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) -> None: ...
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def add_equals_match_guard(
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self,
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equals_val: Any,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_global_state_guard(
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self, initial_state: Any, verbose_code_parts: list[str]
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) -> None: ...
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def add_torch_function_mode_stack_guard(
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self, initial_stack: list[Any], verbose_code_parts: list[str]
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) -> None: ...
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def add_mapping_keys_guard(
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self, value: Any, verbose_code_parts: list[str]
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) -> None: ...
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def add_dict_length_check_guard(
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self, value: int, verbose_code_parts: list[str]
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) -> None: ...
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def add_length_check_guard(
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self, value: int, verbose_code_parts: list[str]
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) -> None: ...
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def add_true_match_guard(
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self,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_false_match_guard(
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self,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_none_match_guard(
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self,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_not_none_guard(
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self,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_dispatch_key_set_guard(
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self,
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dispatch_key: Any,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_tensor_match_guard(
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self,
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value: Any,
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sizes: list[int],
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strides: list[int],
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tensor_name: str,
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verbose_code_parts: list[str],
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ptype: Any,
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dispatch_keys: Any,
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) -> None: ...
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def add_dynamic_indices_guard(
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self,
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value: set[Any],
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verbose_code_parts: list[str],
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) -> None: ...
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def add_no_hasattr_guard(
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self,
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attr_name: str,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_dict_contains_guard(
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self,
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contains: bool,
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key: Any,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_type_match_guard(
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self,
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value: int,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_dict_version_guard(
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self,
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value: Any,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_set_contains_guard(
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self,
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contains: bool,
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item: Any,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_dual_level_match_guard(
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self,
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level: int,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_float_is_nan_guard(
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self,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_complex_is_nan_guard(
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self,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_tuple_iterator_length_guard(
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self,
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length: int,
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type_id: int,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_range_iterator_match_guard(
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self,
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start: int,
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stop: int,
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step: int,
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type_id: int,
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verbose_code_parts: list[str],
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) -> None: ...
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def add_default_device_guard(
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self,
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verbose_code_parts: list[str],
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) -> None: ...
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def mark_tag_safe(self) -> None: ...
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def mark_tag_safe_root(self) -> None: ...
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class RootGuardManager(GuardManager):
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def get_epilogue_lambda_guards(self) -> list[LeafGuard]: ...
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def add_epilogue_lambda_guard(
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self,
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guard: LeafGuard,
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verbose_code_parts: list[str],
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) -> None: ...
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def clone_manager(
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self, clone_filter_fn: Callable[[GuardManager], bool]
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) -> RootGuardManager: ...
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def attach_compile_id(self, compile_id: str) -> None: ...
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class DictGuardManager(GuardManager):
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def get_key_manager(
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self,
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index: int,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def get_value_manager(
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self,
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index: int,
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source: str,
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example_value: Any,
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guard_manager_enum: GuardManagerType,
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) -> GuardManager: ...
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def get_key_value_managers(
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self,
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) -> dict[int, tuple[GuardManager, GuardManager]]: ...
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# Guard accessor stubs
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class GuardAccessor: ...
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class DictGetItemGuardAccessor(GuardAccessor): ...
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class GetGenericDictGuardAccessor(GuardAccessor): ...
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class TypeDictGuardAccessor(GuardAccessor): ...
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class TypeMROGuardAccessor(GuardAccessor): ...
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class ClosureGuardAccessor(GuardAccessor): ...
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class TupleGetItemGuardAccessor(GuardAccessor): ...
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class TypeGuardAccessor(GuardAccessor): ...
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class CodeGuardAccessor(GuardAccessor): ...
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class FuncDefaultsGuardAccessor(GuardAccessor): ...
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class FuncKwDefaultsGuardAccessor(GuardAccessor): ...
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class GetAttrGuardAccessor(GuardAccessor):
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def get_attr_name(self) -> str: ...
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def install_object_aliasing_guard(
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x: GuardManager,
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y: GuardManager,
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verbose_code_parts: list[str],
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) -> None: ...
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def install_no_tensor_aliasing_guard(
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guard_managers: list[GuardManager],
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tensor_names: list[str],
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verbose_code_parts: list[str],
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) -> None: ...
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def install_storage_overlapping_guard(
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overlapping_guard_managers: list[GuardManager],
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non_overlapping_guard_managers: list[GuardManager],
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verbose_code_parts: list[str],
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) -> None: ...
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def install_symbolic_shape_guard(
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guard_managers: list[GuardManager],
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nargs_int: int,
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nargs_float: int,
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py_addr: int,
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py_addr_keep_alive: Any,
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verbose_code_parts: list[str],
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) -> None: ...
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def profile_guard_manager(
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guard_manager: GuardManager,
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f_locals: dict[str, Any],
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n_iters: int,
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) -> float: ...
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class TensorGuards:
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def __init__(
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self,
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*,
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dynamic_dims_sizes: list[torch.SymInt | None] | None = None,
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dynamic_dims_strides: list[torch.SymInt | None] | None = None,
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) -> None: ...
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def check(self, *args: Any) -> bool: ...
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def check_verbose(
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self, *args: Any, tensor_check_names: Optional[list[str]] = None
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) -> bool | str: ...
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def assert_size_stride(
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item: torch.Tensor,
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size: torch.types._size,
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stride: torch.types._size,
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op_name: str | None = None,
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) -> None: ...
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def assert_alignment(
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item: torch.Tensor,
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alignment: int,
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op_name: str | None = None,
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) -> None: ...
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def check_obj_id(obj: object, expected: int) -> bool: ...
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def check_type_id(obj: object, expected: int) -> bool: ...
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def dict_version(d: dict[Any, Any]) -> int: ...
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def compute_overlapping_tensors(
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tensors: list[torch.Tensor], symbolic: bool = True
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) -> set[int]: ...
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