o I h3h@sUddlZddlZddlZddlZddlZddlZddlZddlmZm Z m Z m Z m Z m Z ddlZddlmZddlmZddlmZddlmZmZddlZddlmZ gdZdd d Zhd Zd d Z dd:d;Z7dS)?N)FunctionSchema OperatorName SchemaKindBaseTypeListTypeBaseTy)get_ctx)autograd_kernel_indirectionconstruct_autograd_kernel) infer_schema) custom_opCustomOprCPUCUDA)cpucuda>atatenprimprimstorchpytorchcCstdtdS)Nzwtorch._custom_op is deprecated and will be removed in PyTorch 2.6, please use the equivalent torch.library API instead.)warningswarnDeprecationWarningrrI/var/www/vscode/kcb/lib/python3.10/site-packages/torch/_custom_op/impl.pywarn_deprecated-srqualname manual_schemareturncstfdd}|S)L This API is deprecated, please use torch.library.custom_op instead c s,t|stdt|t\}}t||j|kr,tdd|d|jddur6t|ddn}||}t |}t |durPt ||t |d}||t||j}t|||||d d }|j|_|j|_|j|_t ||jd tt|tj|ttt||S) NzDcustom_op(...)(func): Expected `func` to be a Python function, got: zcustom_op(qualname='z-', ...)(func): expected `func` to have name 'z ' but got 'zX'. Please either change the name of `func` or the qualname that is passed to `custom_op`r) mutates_argsFRAGMENTT_private_accessAutograd)inspect isfunction ValueErrortypeparse_qualnamevalidate_namespace__name__r rparsevalidate_schema validate_function_matches_schemalibraryLibrarydefinefind_ophandle_or_thrownamer __module____doc__impl_opnamer weakrefproxyr_C#_dispatch_set_report_error_callback functoolspartialreport_error_callback) funcnsr6schema schema_strfunction_schemalibophandleresultr rrrinner;sH          zcustom_op..inner)r)rr rKrrJrr 3s+r rglobal_registrycseZdZdZddfdd ZddZd,d d Zd d Zd dZddZ ddZ ddZ d,de j ee jefde jfddZddZde jfddZd,de jfddZdd Zd!d"Zd#d$Zd%d&Zd,d'd(Zd-d*d+ZZS).rr"Fr%csntt|std|d|}||_||_||_||_||_||_ d|_ i|_ d|_ |t |j <dS)Nz|The CustomOp constructor is private and we do not guarantee BC for it. Please use custom_op(...) to create a CustomOp object::F)super__init__r RuntimeError_schema_cpp_ns_lib _ophandler: _qualnamer._impls'_registered_autograd_kernel_indirectionrL)selfrGcpp_nsrD operator_namerHr&r6 __class__rrrOws" zCustomOp.__init__cCs0|jrJ|j|jtt|dd|_dS)Nr'T)rWrSr9r:r r;r<rXrrr%_register_autograd_kernel_indirections  z.CustomOp._register_autograd_kernel_indirectionc Cs||r%|j|}|dusJ|j}td|d|jd|d|d tt|}|j d|j }t |||j|<dS)NzAttempting to register a z impl for operator z that already has a z impl registered from Python at z. This is not supported.:) _has_implrVlocationrPrUr( getframeinfosys _getframefilenamelinenoFuncAndLocation)rXkindrB stacklevelfunc_and_locationrbframerrr_register_impls   zCustomOp._register_implcCs |j|SNrVrXrirrr _get_impl zCustomOp._get_implcCs ||jvSrnrorprrrrarrzCustomOp._has_implcCs6|`ttj|j}t||jrt||jt|j =dSrn) rSgetattrropsrRhasattrr:delattrrLrU)rX opnamespacerrr_destroys    zCustomOp._destroycCsd|jdS)Nz)rUr]rrr__repr__szCustomOp.__repr__cOstj|jg|Ri|}|Srn)r=_dispatch_call_boxedrT)rXargskwargsrIrrr__call__szCustomOp.__call__ device_typesr!cs6ttrgD]}t|q fdd}|S)T This API is deprecated, please use torch.library.custom_op instead csJtD]}|j||dt|}tjj||q|S)Nrj)set_check_doesnt_have_library_implrmSUPPORTED_DEVICE_TYPE_TO_KEYr2r9rSr:)f device_type dispatch_key _stacklevelr~rXrrrKs  zCustomOp.impl..inner) isinstancestrvalidate_device_type)rXr~rrrKrrrr9s  z CustomOp.implcCs@||rdSt|}t|j|rtd|d|jddS)Nzimpl(..., device_types=z): the operator zs already has an implementation for this device type via a pre-existing torch.library or TORCH_LIBRARY registration.)rarr=._dispatch_has_computed_kernel_for_dispatch_keyrUrP)rXrkeyrrrrs z(CustomOp._check_doesnt_have_library_implcsfdd}|S)z2Register an implementation for a factory function.cs&d|tjjd||S)Nfactory BackendSelect)rmr2r9rSr:rr]rrrKs z$CustomOp.impl_factory..innerr)rXrKrr]r impl_factorys zCustomOp.impl_factorycfdd}|S)rcsZjdddjjtfdd}jj |dS)NabstractrcsNfdd}tjj||i|WdS1s wYdS)Nctdd)Nz.inner..f_with_ctx..error_on_ctx)r_library fake_implset_ctx_getter)r{r|rrrbrrr f_with_ctxs $z9CustomOp.impl_abstract..inner..f_with_ctxMeta) $_check_doesnt_have_library_meta_implrmrqrbrUr?wrapsrSr9r:)rrrrXrrrKs z%CustomOp.impl_abstract..innerrrXrrKrrr impl_abstractszCustomOp.impl_abstractc sfdd}jtjkr|dj}js|dt|dks'Jtdd|D}|r6|dttj d ttj d ttj d ttj d ttj d tttj ddi}jD]}|j|vrdq\|dt|d|jdq\dS)Ncstd|djd)NzCCannot use torch._custom_ops APIs to register backward formula for z. Got operator z with schema: )rPrU)detailrDrXrrerrorsz4CustomOp._check_can_register_backward..errorznon-functional operatorzoperator with no returnsrcss$|] }|jduo |jj VqdSrn) annotationis_write).0rrrr #s z8CustomOp._check_can_register_backward..zoperator that returns viewsintSymIntboolfloatTensorz List[Tensor]zoperator with return not in z (got ))rQrir functionalreturnslenanyrrrrrrrrr+listvalues)rXrretsis_non_mutating_viewallowed_return_typesretrrr_check_can_register_backwards2       "z%CustomOp._check_can_register_backwardcCs^|jrdSt|jdrtd|jddD]}t|j|r,td|jd|dqdS)NCompositeImplicitAutogradz3impl_backward/impl_save_for_backward: the operator a3 already has an implementation for this device type via a pre-existing registration to DispatchKey::CompositeImplicitAutograd.CompositeImplicitAutograd operators do not need an autograd formula; instead, the operator will decompose into its constituents and those can have autograd formulas defined on them.)r' AutogradCPU AutogradCUDAz; already has an Autograd kernel registered to DispatchKey::z vi a pre-existing torch.library or TORCH_LIBRARY registration. Please either remove those registrations or don't use the torch._custom_ops APIs)rWr=%_dispatch_has_kernel_for_dispatch_keyrUrP)rXrrrr(_check_doesnt_have_library_autograd_impl7s"  z1CustomOp._check_doesnt_have_library_autograd_implcCsr|drdSt|jdrt|jdsdSt|jdr'td|jdt|jdr7td|jddS)NrCompositeExplicitAutogradrrz!impl_abstract(...): the operator a- already has an implementation for this device type via a pre-existing registration to DispatchKey::CompositeImplicitAutograd.CompositeImplicitAutograd operators do not need an abstract impl; instead, the operator will decompose into its constituents and those can have abstract impls defined on them.z already has an DispatchKey::Meta implementation via a pre-existing torch.library or TORCH_LIBRARY registration. Please either remove that registration or don't call impl_abstract.)rar=rrUrPr]rrrrOs     z-CustomOp._check_doesnt_have_library_meta_implc CsX|dsJ|dsJt|j|j|t|j|dj|dj}|d|dS)Nbackwardsave_for_backwardautograd) rar rQ_output_differentiabilityget_oprUrqrBrm)rXkernelrrr_register_autograd_kernelxs  z"CustomOp._register_autograd_kernelcr)zyRegister a function that tells us what to save for backward. Please see impl_backward for more details. csHjsjd|ddr"dSdS)Nrrr)rrrWr^rmrarrrrrrKs  z.CustomOp.impl_save_for_backward..innerrrrrrimpl_save_for_backwardszCustomOp.impl_save_for_backwardNcsldur,fdd}tts|D] }t|ts|qtjjtkr,|fdd}|S)rNcstd)Nzimpl_backward(output_differentiability): expected output_differentiability to be a list of bools with length equal to the number of outputs of this CustomOp got: rr)output_differentiabilityrryells z$CustomOp.impl_backward..yellcsNjsjd|d_dr%dSdS)Nrrr)rrrWr^rmrrarrrrrXrrrKs  z%CustomOp.impl_backward..inner)rrrrrQr)rXrrrdiffrKrrr impl_backwards    zCustomOp.impl_backward)r_)Nr_)r.r7 __qualname__r8rOr^rmrqrarxryr}typingUnionrIterableCallabler9rrrrrrrrr __classcell__rrr[rrrs2    #%) c@s eZdZUejed<eed<dS)rhrBrbN)r.r7rrr__annotations__rrrrrrhs  rhrYrZcCs0|jdurdn|j}t|dt|j|S)NrM) overload_namer=_dispatch_find_schema_or_throwrr6)rYrZrrrrr5s r5rCcCs:d|vr td|d|tvrtd|d|ddS)N.zcustom_op(..., ns="zC"): expected ns to not contain any . (and be a valid variable name)zcustom_op(..., ns='z'): 'z9' is a reserved namespace, please choose something else. )r* RESERVED_NS)rCrrrr-s r-rDcCs:tjj|std||jjdurtd|dS)Nzcustom_op only supports functional operators (ops that do not mutate any inputs, do not return views of the inputs, and has at least one return). Got the following non-functional schema: zUcustom_op does not support arguments named 'self'. Please rename your argument. Got: )rrutilsis_functional_schemar* argumentsself_arg)rDrrrr0s r0cCsR|dd}t|dkrtd|dd|dvr!td||d|dfS) NrMr r_z$Expected there to be a namespace in z;, i.e. The operator name should look something like ns::foorzThe torch.custom_ops APIs do not handle overloads, i.e. operator names with '.' in them. Please name your operator something like ns::foo. Got: r)splitrr*)rnamesrrrr,s   r,rcCs&|tvrtd|dtddS)NzCustomOp.impl(device_types=[z(, ...]): we only support device_type in r)rr*keys)rrrrrsrparamcCs|jtjjtjjfvSrn)rir( ParameterPOSITIONAL_OR_KEYWORD KEYWORD_ONLY)rrrrsupported_paramsrrBcst|tddjDstdtddjDs+jtjj ur2tdddjD}ddjD}fd d fd d fd d}||j j ||j j dS)Ncss|] \}}t|VqdSrn)rr_prrrrsz3validate_function_matches_schema..zcustom_op(..., manual_schema)(func): positional-only args, varargs, and kwargs are not supported. Please rewrite `func` to not have them. Got `func` with signature: css"|] \}}|jtjjuVqdSrn)rr(remptyrrrrrs  zcustom_op(..., manual_schema)(func): When passing in a manual schema, we expect `func` to have no type annotations to avoid ambiguity. Got `func` with signature: cS&g|]\}}|jtjjkr||fqSr)rir(rrrr6rrrr  z4validate_function_matches_schema..cSrr)rir(rrrrrrrrcr)Nzcustom_op(..., manual_schema)(func): When passing in a manual schema, we expect `func`'s signature to match `manual_schema` (aside from type annotations). func's signature: , manual_schema: r*rrDsigrrrz/validate_function_matches_schema..errorcr)Nzycustom_op(..., manual_schema)(func): neither func nor manual_schema should have default arguments. Got func's signature: rrrrrrerror_default_args'rz.error_default_argscs`t|t|kr t||D]\\}}}||jkr|jtjjus*|jdur-qdSrn)rzipr6defaultr(rr)sig_args schema_argsr6rarg)rrrrcompare/s z1validate_function_matches_schema..compare) r( signatureall parametersitemsr*rreturn_annotation Signaturerrflat_positionalflat_kwarg_only)rDrB positional kwargonlyrr)rrrDrrr1s8  r1rc Csp|dkr t|d|dkrt|d|dvr.|}t|d|d|d|d t|d |d ) N Undefineda: There were no Tensor inputs to this operator (e.g. you passed an empty list of Tensors). If your operator is a factory function (that is, it takes no Tensors and constructs a new one), then please use CustomOp.impl_factory to register an implementation for itrz: when running with device='Meta' tensors: there is no abstract impl registered for this CustomOp. Please register one via CustomOp.impl_abstract to get this CustomOp to work with Meta tensors)rrz: when running with device='z' tensors: there is no zW impl registered for this CustomOp. Please register one via CustomOp.impl(device_type='z')z%: No implementation for dispatch key z. It is likely that we have not added this functionality yet, please either open an issue or if you're feeling adventurous, use the low-level torch.library API)NotImplementedErrorlower)r rdevicerrrrA<s( rAcCs\|j}tj|d}|dd}t|j}|dd}t |}t |||||ddS)Nr$rMTr%) namespacerr2r3r6rrrQrr/r)oprCrGr6rErDrrrcustom_op_from_existingZs  r csffdd}t\}}ttj|s|ttj|}t||s#|t||}t|ds0||jS)Ncstdd)NzCould not find the operator z~. Please make sure you have already registered the operator and (if registered from C++) loaded it via torch.ops.load_library.rrrrrerror_not_foundfs zget_op..error_not_foundr)r,rurrtrsr)rr rCr6rwpacketrr rres       rFcCs8|tvrt|S|std|dt|}t|}|S)NzCould not find custom op "z5". Did you register it via the torch._custom_ops API?)rLrPrr )ralso_check_torch_libraryoverloadrIrrr_find_custom_opxs rcCsF|tjjjvr dStjjj|}|durdS|dsdS|djS)Nr)r _custom_opr9rLrarqrB)rr rrrget_abstract_impls  rTc Cs|d\}}||}t|}t||rtjjjgng}t |d}|j ||dt ||j } t ||||| dd} | tj| ttt| t|S)NrMr$)tagsTr%)rrr/r0rr=Tagneeds_fixed_stride_orderr2r3r4r5r6rr^r>r?r@rAr;r<r) rrDrrCr6rErFrrGrHrIrrr_custom_op_with_schemas    rrn)F)T)8 dataclassesr?r(rdrr;rtorchgen.modelrrrrrrrtorch._Cr= torch.libraryr2rrr r torch._library.infer_schemar __all__rrrrOptionalrr rLdictrr dataclassrhr5r-r0tupler,rrrrr1AnyrAr rrrrrrrrsn        <C    A