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Copy pathTestFXAPIBackwardCompatibility.test_function_back_compat-fx_backcompat_function_signatures.expect
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77 lines (77 loc) · 9.97 KB
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torch.fx._symbolic_trace.Tracer.__init__(self, autowrap_modules: Tuple[Callable] = (<module math>,), autowrap_functions: Tuple[Callable[..., Any], ...] = (,), param_shapes_constant: bool = False) -> None
torch.fx._symbolic_trace.Tracer.call_module(self, m: torch.nn.modules.module.Module, forward: Callable[..., Any], args: Tuple[Any, ...], kwargs: Dict[str, Any]) -> Any
torch.fx._symbolic_trace.Tracer.create_arg(self, a: Any) -> 'Argument'
torch.fx._symbolic_trace.Tracer.get_fresh_qualname(self, prefix: str) -> str
torch.fx._symbolic_trace.Tracer.is_leaf_module(self, m: torch.nn.modules.module.Module, module_qualified_name: str) -> bool
torch.fx._symbolic_trace.Tracer.path_of_module(self, mod: torch.nn.modules.module.Module) -> str
torch.fx._symbolic_trace.Tracer.trace(self, root: Union[torch.nn.modules.module.Module, Callable[..., Any]], concrete_args: Optional[Dict[str, Any]] = None) -> torch.fx.graph.Graph
torch.fx._symbolic_trace.symbolic_trace(root: Union[torch.nn.modules.module.Module, Callable[..., Any]], concrete_args: Optional[Dict[str, Any]] = None) -> torch.fx.graph_module.GraphModule
torch.fx._symbolic_trace.wrap(fn_or_name: torch.fx.node.Target) -> torch.fx.node.Target
torch.fx.graph.Graph.__init__(self, owning_module: 'Optional[GraphModule]' = None, tracer_cls: 'Optional[type[Tracer]]' = None, tracer_extras: 'Optional[dict[str, Any]]' = None) -> 'None'
torch.fx.graph.Graph.call_function(self, the_function: 'Callable[..., Any]', args: 'Optional[tuple[Argument, ...]]' = None, kwargs: 'Optional[dict[str, Argument]]' = None, type_expr: 'Optional[Any]' = None, name: 'Optional[str]' = None) -> 'Node'
torch.fx.graph.Graph.call_method(self, method_name: 'str', args: 'Optional[tuple[Argument, ...]]' = None, kwargs: 'Optional[dict[str, Argument]]' = None, type_expr: 'Optional[Any]' = None) -> 'Node'
torch.fx.graph.Graph.call_module(self, module_name: 'str', args: 'Optional[tuple[Argument, ...]]' = None, kwargs: 'Optional[dict[str, Argument]]' = None, type_expr: 'Optional[Any]' = None) -> 'Node'
torch.fx.graph.Graph.create_node(self, op: 'str', target: 'Target', args: 'Optional[tuple[Argument, ...]]' = None, kwargs: 'Optional[dict[str, Argument]]' = None, name: 'Optional[str]' = None, type_expr: 'Optional[Any]' = None) -> 'Node'
torch.fx.graph.Graph.eliminate_dead_code(self, is_impure_node: 'Optional[Callable[[Node], bool]]' = None) -> 'bool'
torch.fx.graph.Graph.erase_node(self, to_erase: 'Node') -> 'None'
torch.fx.graph.Graph.get_attr(self, qualified_name: 'str', type_expr: 'Optional[Any]' = None) -> 'Node'
torch.fx.graph.Graph.graph_copy(self, g: 'Graph', val_map: 'dict[Node, Node]', return_output_node: 'bool' = False) -> 'Optional[Argument]'
torch.fx.graph.Graph.inserting_after(self, n: 'Optional[Node]' = None) -> '_InsertPoint'
torch.fx.graph.Graph.inserting_before(self, n: 'Optional[Node]' = None) -> '_InsertPoint'
torch.fx.graph.Graph.lint(self) -> 'None'
torch.fx.graph.Graph.node_copy(self, node: 'Node', arg_transform: 'Callable[[Node], Argument]' = <function <lambda>>) -> 'Node'
torch.fx.graph.Graph.output(self, result: 'Argument', type_expr: 'Optional[Any]' = None)
torch.fx.graph.Graph.placeholder(self, name: 'str', type_expr: 'Optional[Any]' = None, default_value: 'Any') -> 'Node'
torch.fx.graph.Graph.print_tabular(self) -> 'None'
torch.fx.graph.Graph.python_code(self, root_module: 'str', verbose: 'bool' = False, include_stride: 'bool' = False, include_device: 'bool' = False, colored: 'bool' = False, expanded_def: 'bool' = False, record_func: 'bool' = False, additional_meta: 'Optional[list[str]]' = None) -> 'PythonCode'
torch.fx.graph_module.GraphModule.__init__(self, root: 'torch.nn.Module | dict[str, Any]', graph: 'Graph', class_name: 'str' = 'GraphModule') -> 'None'
torch.fx.graph_module.GraphModule.add_submodule(self, target: 'str', m: 'torch.nn.Module') -> 'bool'
torch.fx.graph_module.GraphModule.delete_all_unused_submodules(self) -> 'None'
torch.fx.graph_module.GraphModule.delete_submodule(self, target: 'str') -> 'bool'
torch.fx.graph_module.GraphModule.recompile(self) -> 'PythonCode'
torch.fx.graph_module.reduce_graph_module(body: 'dict[str, Any]', import_block: 'str') -> 'torch.nn.Module'
torch.fx.graph_module.reduce_package_graph_module(importer: 'PackageImporter', body: 'dict[str, Any]', generated_module_name: 'str') -> 'torch.nn.Module'
torch.fx.interpreter.Interpreter.__init__(self, module: torch.nn.modules.module.Module, garbage_collect_values: bool = True, graph: Optional[torch.fx.graph.Graph] = None) -> None
torch.fx.interpreter.Interpreter.boxed_run(self, args_list: List[Any]) -> Any
torch.fx.interpreter.Interpreter.call_function(self, target: 'Target', args: Tuple[torch.fx.node.Argument, ...], kwargs: Dict[str, Any]) -> Any
torch.fx.interpreter.Interpreter.call_method(self, target: 'Target', args: Tuple[torch.fx.node.Argument, ...], kwargs: Dict[str, Any]) -> Any
torch.fx.interpreter.Interpreter.call_module(self, target: 'Target', args: Tuple[torch.fx.node.Argument, ...], kwargs: Dict[str, Any]) -> Any
torch.fx.interpreter.Interpreter.fetch_args_kwargs_from_env(self, n: torch.fx.node.Node) -> Tuple[Tuple[Any, ...], Dict[str, Any]]
torch.fx.interpreter.Interpreter.fetch_attr(self, target: str) -> Any
torch.fx.interpreter.Interpreter.get_attr(self, target: 'Target', args: Tuple[torch.fx.node.Argument, ...], kwargs: Dict[str, Any]) -> Any
torch.fx.interpreter.Interpreter.map_nodes_to_values(self, args: torch.fx.node.Argument, n: torch.fx.node.Node) -> torch.fx.node.Argument
torch.fx.interpreter.Interpreter.output(self, target: 'Target', args: Tuple[torch.fx.node.Argument, ...], kwargs: Dict[str, Any]) -> Any
torch.fx.interpreter.Interpreter.placeholder(self, target: 'Target', args: Tuple[torch.fx.node.Argument, ...], kwargs: Dict[str, Any]) -> Any
torch.fx.interpreter.Interpreter.run(self, *args: Any, initial_env: Optional[Dict[torch.fx.node.Node, Any]] = None, enable_io_processing: bool = True) -> Any
torch.fx.interpreter.Interpreter.run_node(self, n: torch.fx.node.Node) -> Any
torch.fx.interpreter.Transformer.__init__(self, module: torch.fx.graph_module.GraphModule) -> None
torch.fx.interpreter.Transformer.call_function(self, target: 'Target', args: Tuple[torch.fx.node.Argument, ...], kwargs: Dict[str, Any]) -> Any
torch.fx.interpreter.Transformer.call_module(self, target: 'Target', args: Tuple[torch.fx.node.Argument, ...], kwargs: Dict[str, Any]) -> Any
torch.fx.interpreter.Transformer.get_attr(self, target: 'Target', args: Tuple[torch.fx.node.Argument, ...], kwargs: Dict[str, Any]) -> torch.fx.proxy.Proxy
torch.fx.interpreter.Transformer.placeholder(self, target: 'Target', args: Tuple[torch.fx.node.Argument, ...], kwargs: Dict[str, Any]) -> torch.fx.proxy.Proxy
torch.fx.interpreter.Transformer.transform(self) -> torch.fx.graph_module.GraphModule
torch.fx.node.Node.__init__(self, graph: 'Graph', name: str, op: str, target: 'Target', args: Tuple[Argument, ...], kwargs: Dict[str, Argument], return_type: Optional[Any] = None) -> None
torch.fx.node.Node.append(self, x: 'Node') -> None
torch.fx.node.Node.format_node(self, placeholder_names: Optional[List[str]] = None, maybe_return_typename: Optional[List[str]] = None, include_tensor_metadata: bool = False) -> Optional[str]
torch.fx.node.Node.insert_arg(self, idx: int, arg: torch.fx.node.Argument) -> None
torch.fx.node.Node.prepend(self, x: 'Node') -> None
torch.fx.node.Node.replace_all_uses_with(self, replace_with: 'Node', delete_user_cb: Optional[Callable[[Node], bool]] = None, propagate_meta: bool = False) -> List[Node]
torch.fx.node.Node.replace_input_with(self, old_input: 'Node', new_input: 'Node') -> None
torch.fx.node.Node.update_arg(self, idx: int, arg: torch.fx.node.Argument) -> None
torch.fx.node.Node.update_kwarg(self, key: str, arg: torch.fx.node.Argument) -> None
torch.fx.node.map_aggregate(a: torch.fx.node.Argument, fn: Callable[[torch.fx.node.Argument], torch.fx.node.Argument]) -> torch.fx.node.Argument
torch.fx.node.map_arg(a: torch.fx.node.Argument, fn: Callable[[torch.fx.node.Node], torch.fx.node.Argument]) -> torch.fx.node.Argument
torch.fx.passes.reinplace.reinplace(gm: torch.fx.graph_module.GraphModule, *sample_args: Any) -> torch.fx.graph_module.GraphModule
torch.fx.passes.runtime_assert.insert_deferred_runtime_asserts(gm: torch.fx.graph_module.GraphModule, shape_env: Any, name: str, export: bool = False) -> None
torch.fx.passes.split_module.split_module(m: torch.fx.graph_module.GraphModule, root_m: torch.nn.modules.module.Module, split_callback: Callable[[torch.fx.node.Node], int], qualname_map: Optional[Dict[str, str]] = None, keep_original_order: Optional[bool] = False, keep_original_node_name: Optional[bool] = False, keep_original_input_name: bool = True, partition_affix: Optional[str] = None, tuple_return: bool = False) -> torch.fx.graph_module.GraphModule
torch.fx.proxy.Attribute.__init__(self, root: torch.fx.proxy.Proxy, attr: str) -> None
torch.fx.proxy.Proxy.__init__(self, node: torch.fx.node.Node, tracer: 'Optional[TracerBase]' = None) -> None
torch.fx.proxy.Proxy.keys(self) -> 'Proxy'
torch.fx.proxy.TracerBase.create_arg(self, a: Any) -> torch.fx.node.Argument
torch.fx.proxy.TracerBase.create_node(self, kind: str, target: torch.fx.node.Target, args: Tuple[torch.fx.node.Argument, ...], kwargs: Dict[str, torch.fx.node.Argument], name: Optional[str] = None, type_expr: Optional[Any] = None) -> torch.fx.node.Node
torch.fx.proxy.TracerBase.create_proxy(self, kind: str, target: torch.fx.node.Target, args: Tuple[Any, ...], kwargs: Dict[str, Any], name: Optional[str] = None, type_expr: Optional[Any] = None, proxy_factory_fn: Optional[Callable[[torch.fx.node.Node], Proxy]] = None) -> 'Proxy'
torch.fx.proxy.TracerBase.iter(self, obj: 'Proxy') -> Iterator
torch.fx.proxy.TracerBase.keys(self, obj: 'Proxy') -> 'Proxy'
torch.fx.proxy.TracerBase.proxy(self, node: torch.fx.node.Node) -> 'Proxy'
torch.fx.proxy.TracerBase.to_bool(self, obj: 'Proxy') -> bool
torch.fx.subgraph_rewriter.replace_pattern(gm: torch.fx.graph_module.GraphModule, pattern: Union[Callable[..., Any], torch.fx.graph_module.GraphModule], replacement: Union[Callable[..., Any], torch.fx.graph_module.GraphModule]) -> List[torch.fx.subgraph_rewriter.Match]