sg!ddlZddlZddlmZmZddlmZddlZddl Z ddl m Z ddl m Z mZmZmZmZmZmZmZmZmZmZmZmZmZddlmZeeeeeeeefZeeeeefZdge rdgngzZGd d e Z d Z!d Z"d Z#dZ$dZ%ddZ&dZ'y)N)partialwraps)Sequence) TEST_CUDA)_dispatch_dtypes all_types all_types_andall_types_and_complexall_types_and_complex_andall_types_and_half complex_typesfloating_and_complex_typesfloating_and_complex_types_andfloating_typesfloating_types_andfloating_types_and_halfintegral_typesintegral_types_and)torch_to_numpy_dtype_dictcpucudac eZdZy)_dynamic_dispatch_dtypesN)__name__ __module__ __qualname__W/var/www/html/venv/lib/python3.12/site-packages/torch/testing/_internal/opinfo/utils.pyrr6srrc4|dvsJts%|dk(r tjdtdSt }t t jt jt jD]V} ||||d}d}|D]-} ||jg|ji|j/|sF|j|Xt|S#t$rtjd|d|YwxYw#t$r }d}Yd}~\d}~wwxYw) N)rrrzGWARNING: CUDA is not available, empty_dtypes dispatch will be returned!rFz.WARNING: Unable to generate sample for device:z and dtype:T)rwarningswarnrsetr torchboolbfloat16half RuntimeErrorinputargskwargsadd) opsample_inputs_fn device_typesupported_dtypesdtypesamples supportedsampleres rget_supported_dtypesr6;s  / )) ) . U (++u*5::u~~uzzR( &r;uEG  F 6<<?&++??     '3(6 $$4 551  MM@ [Y^X_`      !  s*7 C *D$C>=C> D DDc ptjdd}t|dk(r |ddSt|}tD]-}t||k(s|||j dzcSd}d}t D]9}t|}|j|s%t|}||kDs6|}|};||dt|S|tgtt|t|z |j ttt|t|z zS)N return_typezdispatch_fn dispatch_fn_strrrz()g) collections namedtuplelenr#COMPLETE_DTYPES_DISPATCHrEXTENSIBLE_DTYPE_DISPATCHissubsetstrrtuple)dtypesr8 set_dtypesdispatchchosen_dispatchchosen_dispatch_scoredispatch_dtypesscores rdtypes_dispatch_hintrHcs6((8UVK 6{a2t$$VJ,C xz?j (x):):T)AB BC O-'hj/'' 3 O$ ( ($) !&O'2s6{++ @5Vs8:!>?@Cc&kC O&C DEE rc|jSN)dynamic_dtypes)r-s ris_dynamic_dtype_setrLs   rcd|jdt|jjdt|jjd}|S)Nz OpInfo(z, dtypes=z, dtypesIfCUDA=z, ) )namerHrAdispatch_fn_str dtypesIfCUDA)r-fmt_strs rstr_format_dynamic_dtyperRsYy+BII6FFGH1"//BRRST  G Nrc8dtfd}|S)Nc|tjttjtjtj tj tjfvSrJ)npbool_r%uint8int8int16int32int64)r1s r is_integralz=np_unary_ufunc_integer_promotion_wrapper..is_integralsA HH  HH GG HH HH HH   rcttj}|jr|j |S|SrJ)rr$get_default_dtyper1astype)xnp_dtypefnr\s r wrapped_fnz.wrapped_fnsA-U-D-D-FG qww ahhx() )!u r)r)rbrcr\s` @r(np_unary_ufunc_integer_promotion_wrapperrds(   2Y rcTtdtjffd }|S)aAWraps a NumPy reduction operator. The wrapper function will forward dim, keepdim, mask, and identity kwargs to the wrapped function as the NumPy equivalent axis, keepdims, where, and initiak kwargs, respectively. Args: f: NumPy reduction operator to wrap supports_keepdims (bool, optional): Whether the NumPy operator accepts keepdims parameter. If it does not, the wrapper will manually unsqueeze the reduced dimensions if it was called with keepdim=True. Defaults to True. Returns: Wrapped function r`czt|j}|jdd}|jdd}d|vr;t|tr t |n|}|j dk(r |dvrd|d<n||d<d|vr r||d<d|vrS|jd}|@|jtjk(sJ|jj|d <d |vr|jd }|m|jtjur.|jjtj}n|j}|j|d < |g|i|}|rI sG|j dkDr8|t!t#|j n|}t%j&||}|S) NdimkeepdimFr>rrrkaxiskeepdimsmaskwhereidentityinitial)r#keyspop isinstancerr@ndimlayoutr$stridedrnumpyr1r&tofloat32listrangerU expand_dims) r`r*r+rrrgrhrnrpresultfsupports_keepdimss rwrapperz*reference_reduction_numpy..wrappers6;;=!jj%**Y. D= *3 9%*sCvv{s&::!%v!$v  !2!(F:  T>::f%D{{emm333"&((*"2"2"4w  zz*-H#>>U^^3'||~00?H'||~H$,NN$4y!1&t&v& ,!),$uQVV}%#C^^FC0F r)rrUndarray)rrrs`` rreference_reduction_numpyrs.$ 1X*2::**X Nrcd|vrtj|jtjr |j tj }nMtj|jtj r|j tj}ttj}||g|i|S)aR The function will call np.prod with type as np.int64 if the input type is int or uint64 if is uint. This is necessary because windows np.prod uses by default int32 while on linux it uses int64. This is for fixing integer overflow https://github.com/pytorch/pytorch/issues/77320 Returns: np.prod of input r1) rU issubdtyper1 signedintegerr_r[unsignedintegeruint64rprod)ar*r+rbs r prod_numpyrsf ==""2"2 3"A ]]177B$6$6 7#A "277 +B a !$ !& !!r)T)(r9r! functoolsrrtypingrrxrUr$#torch.testing._internal.common_cudar$torch.testing._internal.common_dtyperrr r r r r rrrrrrr$torch.testing._internal.common_utilsrr<r=DEVICESrr6rHrLrRrdrrrrrrs$ 9 K "  'fX 3 / %6P#L !H?D"r