a ==ic"@s"ddlZddlmZddlmZmZmZmZm Z ddlmm Z ddl m Z ddl mZmZmZddlZddlmZmZddlZddlZddlmZeeeefejeeeefddd Zeeed d d Zd dZGdddeZedddZ eedddZ!eedddZ"ddZ#dS)N)Number NumberType TensorLikeTensorLikeTypeELEMENTWISE_TYPE_PROMOTION_KIND) tree_flatten)CallableSequenceUnion)wrapsreduce)chain)adtypereturncsrt|tr$|jkr t|S|St|tr!z*_maybe_convert_to_dtype..z7Received type {0} that is neither a tensor or a number!) isinstancerrprimsZconvert_element_typerutilsZ dtype_to_typer tuple ValueErrorformattype)rrrrrrs      r)rtyprcCsRt|ts dt|}t|tt||sJd|t||}t|||S)Nz6Found unknown type {0} when trying to convert scalars!z9Scalar {0} of type {1} cannot be safely cast to type {2}!)rrr r!rrZis_weakly_lesser_type)rr"msgrrr_maybe_convert_to_type(s  r$cCs4t|dr,|jD]}t||drdSqdS||uS)N__args__)r" annotationTF)hasattrr%_annotation_has_type)r"r&rrrrr(5s    r(c@s:eZdZdZddeeedddZeeddd Z dS) "elementwise_type_promotion_wrappera Adds elementwise type promotion to a Python reference implementation. Takes two kwargs, type_promoting_args and type_promotion_kind. type_promoting_args must be a string Sequence specifiying the argument names of all arguments that participate in type promotion (and should be type promoted). If the arg specifies a Sequence-type then every element of the Sequence will participate in type promotion. type_promotion_kind must be one of the kinds specified by ELEMENTWISE_TYPE_PROMOTION_KIND. See its documentation for details. Other type promotion behavior, like validating the Python type of scalar arguments, must be handled separately. N)type_promoting_args)type_promotion_kindr*cCs||_||_dSr)type_promoting_arg_namesr+)selfr+r*rrr__init__Qsz+elementwise_type_promotion_wrapper.__init__fnrcs,ttfdd}|_|S)Ncsj|i|tfddjD}t|d}tj|dji\}fddjD}j|fij}t |t sJt ||S)Nc3s&|]}|jvrj|VqdSr) argumentskeysr)boundrrr`szKelementwise_type_promotion_wrapper.__call__.._fn..rr+cs,i|]$}|jvr|tj|qSr)r1r2rrr3Z compute_dtyperr lszLelementwise_type_promotion_wrapper.__call__.._fn..) bindrr,rrZelementwise_dtypesr+r1updaterrr)argskwargsr*Zflattened_type_promoting_argsZ result_dtypeZ promoted_argsresultr0r-sigr4r_fn]s"     z8elementwise_type_promotion_wrapper.__call__.._fn)inspect signaturer __signature__)r-r0r=rr;r__call__Zs  z+elementwise_type_promotion_wrapper.__call__) __name__ __module__ __qualname____doc__rr strr.rrArrrrr)?s r)outcCs^|dkrt||S|ttj|dkrZdt|jt|}t |t||S|S)NraYAn output with one or more elements was resized since it had shape {0} which does not match the required output shape {1}. This behavior is deprecated, and in a future PyTorch release outputs will not be resized unless they have zero elements. You can explicitly reuse an out tensor t by resizing it, inplace, to zero elements with t.resize_(0).) Znumelrresizer operatormulr rFshapewarningswarn)rHrMr#rrr_maybe_resize_out~s    rP copy_fromcopy_tocCsZ|j|jkr$d|j|j}t|tj|j|jdsNd|j|j}t|t||S)NzZAttempting to copy from device {0} to device {1}, but cross-device copies are not allowed!)Z cast_fromZcast_tozhAttempting to cast from {0} to out tensor with dtype {1}, but this can't be cast because it is not safe!)Zdevicer RuntimeErrorrZcan_safe_cast_torrrS)rRrSr#rrr_safe_copy_outs rUr/csttddfdd }t}tjdtjjdtd}t|j|f}tj ||j d|_ j |_ t|j d<|S)z Adds the out parameter to a Python reference. Note that this currently only supports operations that return a single tensor. NrGcs@|i|}|dur._fnrHkinddefaultr& parametersreturn_annotation) r r>r? Parameter KEYWORD_ONLYrr r\values Signaturer]r@__annotations__)r0r=r<Z out_paramparamsrrWr out_wrappers   rdcsttdfdd }|S)Nr/c stfdd}t}g}D] }|tj|tjjdtdq(t|j |}tj ||j d|_ j |_ D]}t|j |<qx|S)Nc si}d}D]>}||d||<|dur6||du}q |||duks Jq |i|}t|tshJ|rg}tD]D\}}||}t|tsJt|||j}|t|||dqxt|S|SrV) poprr enumeraterrPrMappendrU) r8r9Z out_kwargsZhas_out_kwargsor:Z final_resultirH)r0 out_namesrrr=s$z*out_wrapper_multi..go.._fnrXr[)r r>r?rgr^r_rr r\r`rar]r@rb)r0r=r<Z out_paramsrhrcrjrWrgos*  zout_wrapper_multi..go)r)rjrlrrkrout_wrapper_multis,rm)$ZtorchZ torch._primsZ_primsrZtorch._prims.utilsrrrrrrZtorch.utils._pytreertypingrr r r> functoolsr r rKrN itertoolsr rrr!r$r(objectr)rPrUrdrmrrrrs(      ?!