o H h4S@sUddlZddlZddlZddlZddlZddlZddlmZmZmZm Z m Z m Z ddl Z ddl mZddlmZmZddlmZe rIddlmZgdZed d Gd d d e ZiZeeeejfed <ddZeee j<GdddZe j e j!e j"ej#e j$j%ej&e j'ee(de j)e*dd Z+e,eD] Z-e.ee-e+e-<qdddefddZ/de j0j1dejfddZ2iZ3ee4e5e5fejfed<de j0j1dejfddZ6ed d ded e4d!d"ee5d#ffd$d%Z7ed d dd6e j=j>de5d e4ed"e ee5efd3e8de ef d7d8Z?d9ejd e4ed0fd"ee5efd3e8de ef d:d;Z@dS)?N)AnyCallablecast NamedTupleOptional TYPE_CHECKING)boolean_dispatched) OpOverloadOpOverloadPacket) compatibility)Argument)ArgsKwargsPaircheck_for_mutable_operationget_signature_for_torch_opcreate_type_hint type_matchesnormalize_functionnormalize_moduleF)is_backward_compatiblec@s2eZdZUdZeedfed<eeefed<dS)rz< Simple named tuple for wrapping args/kwargs pairs. .argskwargsN) __name__ __module__ __qualname____doc__tupler__annotations__dictstrr r M/var/www/vscode/kcb/lib/python3.10/site-packages/torch/fx/operator_schemas.pyrs r_manual_overridescCs>g}dd}|t|dtfdd}|t||S)NcSdSNr )selfr r r!nonzero/z!_nonzero_schemas..nonzeroas_tuplecSr#r$r )r%r(r r r!r&4r')appendinspect signaturebool) signaturesr&r r r!_nonzero_schemas,s r.c@seZdZddZdS)_FakeGlobalNamespacecCs|dkrtStd)Ntorchz!Expected a torch namespace lookup)r0 RuntimeError)r%namer r r! __getattr__@sz _FakeGlobalNamespace.__getattr__N)rrrr3r r r r!r/?s r/t) TensorDeviceLayoutnumberFuture AnyEnumTypeQScheme __torch__NoneTypeStorager4ts_typeztorch._C.JitTypereturncCs t|jtS)z Convert a TorchScript type to a Python type (including subtypes) via eval'ing the annotation_str. _type_eval_globals sets up expressions like "List" and "Future" to map to actual types (typing.List and jit.Future) )evalannotation_str_type_eval_globals)r?r r r! _torchscript_type_to_python_typeWs rD ts_schemac Csddlm}g}|jD]\}t|j}|r|jn|j}|jdkr$|jnd}|j r,|j n|j }|dkr\||j ks:J|j }t |D]\}} | j|j ksMJ|| j|j | j| jd||<qA||||||dq dd|jD} t| dkryd} nt| d kr| d} nt| } tj|| d S) Nr) Parameterr%inputfrom)r2kinddefault annotationcSsg|]}t|jqSr )rDtype).0retr r r! s z9_torchscript_schema_to_signature_impl..r )return_annotation)r*rF argumentsrDrLhas_default_value default_valueemptyr2 kwarg_only KEYWORD_ONLYPOSITIONAL_OR_KEYWORDPOSITIONAL_ONLY enumeraterIrJrKr)returnslenr Signature) rErF parametersargarg_typerJr2rIidxp return_types return_typer r r!%_torchscript_schema_to_signature_impl`sB       rd_SCHEMA_TO_SIGNATURE_CACHEcCs6|j|jf}t|}|dur|St|}|t|<|Sr$)r2 overload_nameregetrd)rE cache_key cache_valresr r r! _torchscript_schema_to_signatures  rktargetr)r .rr c Cst|dd\}}|rS|rUg}t||D]\}}z|j|i||||fWqty1Yqwdd}t|dkr>dSt|dkrP|d\} } || dS dSdSdS)NT)return_schemascSs|jr td|ddS)Nz!Tried to trace mutable operation z|. FX only supports functional code, so operations that mutate operands in-place (e.g. via `out` arguments) are not supported) is_mutabler1)schemar r r!throw_if_mutables  z5check_for_mutable_operation..throw_if_mutablerr )rzipbindr) TypeErrorr[) rlrrr-schemasmatched_schemascandidate_signaturerorp_schema_to_checkr r r!rs$     roprmcsttr jg}n7ttrfddD}n&t}|r*|r(|dfSdStjj }|dur;|r9dSdStj |}dd|D}|rN||fS|S)a Given an operator on the `torch` namespace, return a list of `inspect.Signature` objects corresponding to the overloads of that op.. May return `None` if a signature could not be retrieved. Args: op (Callable): An operator on the `torch` namespace to look up a signature for Returns: Optional[List[inspect.Signature]]: A list of signatures for the overloads of this operator, or None if the operator signatures could not be retrieved. If return_schemas=True, returns a tuple containing the optional Python signatures and the optional TorchScript Function signature csg|]}t|jqSr )getattr_schema)rMoverloadryr r!rOsz.get_signature_for_torch_op..N)NNcSsg|]}t|qSr )rkrMror r r!rOs) isinstancer r{r overloadsr"rgr0jit _builtins _find_builtin_C_jit_get_schemas_for_operator)ryrmrtoverrideaten_fnr-r r}r!rs      rcCszEt|ttfrCt|trdd}ndd}t|dkr!|tWS|d}|D]}t||r/q't||r7|}q'|tWS||WSW|StyWtd|Y|Sw)a Produces a type hint for the given argument. The :func:`create_type_hint` looks for a type hint compatible with the input argument `x`. If `x` is a `list` or `tuple`, it looks for an object in the list whose type is a superclass of the rest, and uses that as `base_type` for the `List` or `Tuple` to be returned. If no such object is found, it defaults to `List[Any]`. If `x` is neither a `list` nor a `tuple`, it returns `x`. cSst|Sr$)listxr r r!ret_typesz"create_type_hint..ret_typecSs t|dfS)N.)rrr r r!rs rz@We were not able to successfully create type hint from the type ) rrrr[r issubclass Exceptionwarningswarn)rr base_typer4r r r!rs.         rsignature_type argument_typecst|d|}|ur dS|tjur#|kr#|j}tfdd|DSt|ddturd|jdtur:tur:dStsJt d|ddStddturZt jdSfd d }|S|turot j urodS|tjur|tthvr|dStrt|rt |SdS) N __origin__Tc3s|]}t|VqdSr$)rrMc)rr r! 'ztype_matches..rz.Does not support nested parametric types, got z. Please file a bug.Fcs>t|ddtur dS|j}|jdkrdStfdd|DS)NrF)r Tc3s"|] }|tup t|VqdSr$)Ellipsisrr sig_el_typer r!r>s z=type_matches..is_homogeneous_tuple..)rzr__args__all)r4 containedrr r!is_homogeneous_tuple8s  z*type_matches..is_homogeneous_tuple)rztypingUnionranyrintr*isclassrrrr0dtypenumbersNumberfloat)rrsig_origin_type sig_containedrr )rrr!rs4       r. arg_types kwarg_typesnormalize_to_only_use_kwargsc Cs |duri}d}t|tjsVt|ttfsV|}|tvr?t|tr"Jt|}|d|d} } t| j t| j kr=dS| }t |sEJtt |} t | |||}|St |s\Jt |} g} | r| D]}z|j|i|| |WqgtyYqgwt| dkr |St| dkrt | d|||}|S|dus|dur|r|ntttd}|r|ni}| D]=}d}z!|j|i|}|jD]\}}|j |}|ot|j|}qWn tyd}Ynw|rt ||||}|Sq|Sd d d | D}td t|d ||S)a Returns normalized arguments to PyTorch functions. This means that `args/kwargs` will be matched up to the functional's signature and return exclusively kwargs in positional order if `normalize_to_only_use_kwargs` is True. Also populates default values. Does not support positional-only parameters or varargs parameters (*args, **kwargs). Does not support modules. May require `arg_types` and `kwarg_types` in order to disambiguate overloads. Args: target (Callable): Function that we are normalizing args (Tuple[Any]): Tuple of args to the function kwargs (Optional[Dict[str, Any]]): Dict of kwargs to the function arg_types (Optional[Tuple[Any]]): Tuple of arg types for the args kwarg_types (Optional[Dict[str, Any]]): Dict of arg types for the kwargs normalize_to_only_use_kwargs (bool): Whether to normalize to only use kwargs. Returns: Returns normalized_args_and_kwargs, or `None` if not successful. Nif_trueif_falserr r TF css|]}t|VqdSr$)rr~r r r!rs z%normalize_function..z Tried to normalize arguments to zy but the schema match was ambiguous! Please provide argument types to the normalize_arguments() call. Available schemas: )rtypesBuiltinFunctionTyper r rrr*r+r]callableunwrap&_args_kwargs_to_normalized_args_kwargsrrrr)rsr[rrrrQitemsrrKjoinr1r0typename)rlrrrrrnew_args_and_kwargstarget_for_analysis dispatchedrrsigtorch_op_schemasrurv sig_matches bound_typesarg_namer_paramschema_printoutsr r r!rOs     A   -  *     rrootc Csz||}Wnty}z td|d|d}~wwt|jdrI|jj}ttj|d|jkrIt t |j }|dur@i}t ||||} | SdS)a( Returns normalized arguments to PyTorch modules. This means that `args/kwargs` will be matched up to the functional's signature and return exclusively kwargs in positional order if `normalize_to_only_use_kwargs` is True. Also populates default values. Does not support positional-only parameters or varargs parameters (*args, **kwargs). Args: root (nn.Module): root module upon which we query modules target (Callable): Function that we are normalizing args (Tuple[Any]): Tuple of args to the function kwargs (Optional[Dict[str, Any]]): Dict of kwargs to the function normalize_to_only_use_kwargs (bool): Whether to normalize to only use kwargs. Returns: Returns normalized_args_and_kwargs, or `None` if not successful. z$Tried to normalize node with target z# but root did not have that target!Nr) get_submoduleAttributeErrorr1hasattr __class__rrzr0nnr*r+rforwardr) rrlrrrsubmode classnamerrr r r!rs*  rrc stjjtjjhtfdd|jDr#t|jgdkr#dS|j |i|}| i}g}t |jD]\}}|sM|t |krM| |j|q8|j|||<q8tt||S)a Given a call target, args, and kwargs, return the arguments normalized into an ArgsKwargsPair, or None if the type signature is not supported by this normalization. Args: sig (inspect.Signature): Signature object for the target args (Tuple): Arguments that appear at the callsite for `target` kwargs (Dict): Keyword arguments that appear at the callsite for `target` normalize_to_only_use_kwargs (bool): Whether to normalize to only use kwargs. Returns: Optional[ArgsKwargsPair]: Normalized args and kwargs for `target`, or `None` if this target is not supported. c3s|]}|jvVqdSr$)rI)rMrasupported_parameter_typesr r!rrz9_args_kwargs_to_normalized_args_kwargs..)rGrHto generatorN)r*rFrWrVrr]valuesrkeysrrapply_defaultsrYr[r)rQrr) rrrr bound_args new_kwargsnew_argsirr rr!rsr)F)NNNF)NF)Aenumr*rrrrrrrrrrr0torch._jit_internalr torch._opsr r _compatibilityr noder __all__rr"rrr\rr.r&r/r5devicelayoutrrr9EnumqschemerLUntypedStorageTypeVarrCdirkrzrDrFunctionSchemardrerrrkrr,rrrrrModulerrr r r r!s           3   '" ,2   z .