IЦiA* SSKrSSKrSSKJrJrJrJr SSKrSSKJrJrJ r J r SSK J r \ "S5SS.S\RS\\S \4S jj5rS rS r\ S \R\ S\S\S\S\ R*S0rSr\"5rS\R2S \4SjrS\R6\R8S \R6\R4Sjrg)N)ListOptionalSequenceUnion)devicedtypeTensortypes) exposed_inz torch.library)op_nameprototype_functionr returnc ^^Sn[R"U5mU4SjmS[4U4Sjjn/n[5nSn[ TR R 55GHunup[U 5(dT"S5 U R[RR:XaU(dURS5 SnU R[RRLa T"S U S 35 U Rn [U 5[:XaU"U 5n U [R!5;aU R"[$La]['U 5n S n U [R!5;aS U S 3n T"S U SU RSU S[R!5S3 5 O.T"S U SU RS[R!5S35 [U n[U5[:Xa;X:wa [)S5eUR+S5(aSUSU[-S5S3nO;X;a6UR+S5(d T"S U S35 SUSU[-S5S3nUR/U 5 U R0[RRLaURUSU 35 GMVSnU R0b*[3U R0[4[6[845(a[U R05nO[3U R0[[:R<45(aSU R0S3nO[3U R0[:R>5(a>[U R05nSnUR+U5(deU[-U5SnO"T"S U S[U R05S35 URUSU SU35 GM X:wa([U5U- n[-U5S:a T"US 35 TR@n[U5[:XaU"U5n[CUT5nUbUS!S"REU5S#U3$S!S"REU5S#U3$)$aParses the schema of a given function with type hints. The schema is inferred from the function's type hints, and can be used to define a new operator. We make the following assumptions: * None of the outputs alias any of the inputs or each other. * | String type annotations "device, dtype, Tensor, types" without library specification are | assumed to be torch.*. Similarly, string type annotations "Optional, List, Sequence, Union" | without library specification are assumed to be typing.*. * | Only the args listed in ``mutates_args`` are being mutated. If ``mutates_args`` is "unknown", | it assumes that all inputs to the operator are being mutates. Callers (e.g. the custom ops API) are responsible for checking these assumptions. Args: prototype_function: The function from which to infer a schema for from its type annotations. op_name (Optional[str]): The name of the operator in the schema. If ``name`` is None, then the name is not included in the inferred schema. Note that the input schema to ``torch.library.Library.define`` requires a operator name. mutates_args ("unknown" | Iterable[str]): The arguments that are mutated in the function. Returns: The inferred schema. Example: >>> def foo_impl(x: torch.Tensor) -> torch.Tensor: >>> return x.sin() >>> >>> infer_schema(foo_impl, op_name="foo", mutates_args={}) foo(Tensor x) -> Tensor >>> >>> infer_schema(foo_impl, mutates_args={}) (Tensor x) -> Tensor unknownc(>[SUSTS35e)Nzinfer_schema(func): z Got func with signature )) ValueError)whatsigs Z/var/www/html/ai-image-ml/venv/lib/python3.13/site-packages/torch/_library/infer_schema.pyerror_fninfer_schema..error_fn9s#"4&(EcU! L  annotation_typecb>[U5$![anT"SUS35 SnAgSnAff=f)NzUnsupported type annotation z. It is not a type.)eval Exception)rers rconvert_type_string)infer_schema..convert_type_string>s> ( (  ..??RS   s  . ).Fz>We do not support positional-only args, varargs, or varkwargs.*Tz Parameter z must have a type annotation.z z For example, z. z has unsupported type z]. We do not support Tuple inputs in schema. As a workaround, please try to use List instead. zThe valid types are: .. The valid types are: zomutates_args must either be a sequence of the names of the arguments that are mutated or the string 'unknown'. r zTensor(az!)NzM is in mutable_args but only Tensors or collections of Tensors can be mutated "ztorch.z' has an unsupported default value type z;. Please file an issue on GitHub so we can prioritize this.=rz in mutates_args were not found in the custom op's signature. mutates_args should contain the names of all args that the custom op mutates, or just the string 'unknown' if you don't know.(, z) -> )#inspect signaturestrset enumerate parametersitemssupported_paramkind Parameter KEYWORD_ONLYappend annotationemptytypeSUPPORTED_PARAM_TYPESkeys __origin__tuple tuple_to_listr startswithlenadddefault isinstanceintfloatbooltorchrrreturn_annotation parse_returnjoin)r mutates_argsr UNKNOWN_MUTATESrparams seen_argssaw_kwarg_only_argidxnameparamr list_typeexample_type_str schema_type default_repr dtype_repr torch_dotmutates_args_not_seenrFretrrs @@r infer_schemarY slT O   . /C SFI'(<(<(>?]du%% U V ::**77 7% c"%)"   w0066 6 z$'DE F **  C '1/BO "7"<"<"> >))U2)/: #)  5 : : <<)6yk'G$ &??!"5==/3 EMM5;;77 / $ !,,Y7777)#i.*:;  &MdSXS`S`NaMbcPQ MM[M4&,@ AQ@R& #L 1I = $ % ) ()*UV  -- #%/0AB (( 3C!DIIf-.eC599 tyy !se ,,rcX^UT4[RUTS34/nSnU(a!URU4SjU"U555 U(a2URU4SjU"[RU555 U(a!URU4SjU"U555 U$)N?cN[RU[RU/$N)typingrr)typs rderived_seq_types(derived_types..derived_seq_typess$ OOC KK   rc30># UH oTS34v M g7f)z[]N.0seq_typcpp_types r derived_types..s 6R7 "o &6Rsc32># UH nUTS34v M g7f)z?[]Nrcrds rrhris$ H #& 'Hsc3T># UHn[RUTS34v M g7f)z[]?N)r^rrds rrhris- 7__W %(3'7 87s%()r^rextend) base_typerg list_baseoptional_base_listoptional_list_baseresultr`s ` r derived_typesrrs H  #z^4F    6G 6R    ,V__Y-GH    ,Y7   Mrc [SSSS4[SSSS4[SSSS4[SSSS4[SSSS4[ R SSSS4[S SSS4[S SSS4/n/nUHnUR[U65 M [U5$) Nr TFSymIntrCrDr+Scalar ScalarTypeDevice) r rBrCrDr+r Numberrrrlrrdict)datarqlines rget_supported_param_typesr|s 4u- heT* ud+ vtUD) eUE5) xue4  eUE2 5%/ DF mT*+ <rr zTensor[]rtrCrDrucUcgU[RRLaU"S5 [R"U5nU[ La4U[ R5;aU"SUS[ S35 [ U$[R"U5nUH"nU[ ;dMU"SUS[ S35 M$ SSRUVs/sH n[ UPM sn5-S-$s snf) Nz()z7No return type annotation was provided. Please add one.zReturn has unsupported type r#r"r'r(r) r)r2r6r^ get_originr;SUPPORTED_RETURN_TYPESr9get_argsrH)r5roriginargsargs rrGrGsW&&,,,JK   z *F U 388: : .zl;((>'?qB &j11 ??: &D , , .zl;((>'?qB  4H4C2374HI IC OOHs C* rPcUR[RR[RR4;$r])r1r)r2POSITIONAL_OR_KEYWORDr3)rPs rr0r0s6 :://&& r tuple_typecz[USS5nU[RLd US:XdUc[R$[ U5S:Xa[RUS$[ U5S:Xa"US[ La[RUS$[R[R [U5$)zu Convert `tuple_type` into a list type with the same type arguments. Assumes that `tuple_type` is typing.Tuple type. __args__Nrcr)getattrr^Tuplerr>Ellipsisrr;)r type_argss rr<r<s J5IV\\!Y"_ 8I{{ Y1 {{9Q<(( Y1 1!9{{9Q<(({{6<<i(89::r)r)r^rrrrrErrr r torch.utils._exposed_inr Callabler+rYrrr|rBrCrDrxrrGr8r2r0Typerr<rcrrrs 22 ... O " T-T- c] T-  T-T-n>& H KK 7& LL( P6237,,;fkk&,,7;FKK