hN5dZddlZddlmZddlZddlmZddlmZddl m Z dZ d Z d Z d Zd Zd ZGddZdZdZGddZeZdZdZddddZdZdZdS)zTools to support array_api.Nwraps) get_config) parse_versionc|rd ddl}n#t$rtdwxYwttj}d}|t|krtd|ddSdS)zCheck that array_api_compat is installed and NumPy version is compatible. array_api_compat follows NEP29, which has a higher minimum NumPy version than scikit-learn. rNzKarray_api_compat is required to dispatch arrays using the API specificationz1.21zNumPy must be z7 or newer to dispatch array using the API specification)array_api_compat ImportErrorrnumpy __version__)array_api_dispatchr numpy_versionmin_numpy_versions `/var/www/html/services/rag-service/venv/lib/python3.11/site-packages/sklearn/utils/_array_api.py_check_array_api_dispatchr s   # # # # #   !   &e&788 " =):;; ; ;)!2)))  < ;s #c`t|tjtjfrdS|jS)aHardware device the array data resides on. Parameters ---------- x : array Array instance from NumPy or an array API compatible library. Returns ------- out : device `device` object (see the "Device Support" section of the array API spec). cpu) isinstancer ndarraygenericdevicexs rrr$s+!emU]344u 8Oc4tj|jS)zReturn the total number of elements of x. Parameters ---------- x : array Array instance from NumPy or an array API compatible library. Returns ------- out : int Total number of elements. )mathprodshapers rsizer 6s 9QW  rc|jdvS)z%Return True if xp is backed by NumPy.>array_api_compat.numpyr numpy.array_api)__name__xps r_is_numpy_namespacer'Fs ;P PPrct|trtfd|DSt|S)zReturns a boolean indicating whether a provided dtype is of type "kind". 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Got rrc g|] }| Srcr.iXs r z)_ArrayAPIWrapper.take..s222QAaD222rc(g|]}|ddfSrVrcrds rrgz)_ArrayAPIWrapper.take..s%555AadG555rc(g|]}dd|fSrVrcrds rrgz)_ArrayAPIWrapper.take..s%111A!!!Q$111r)rWr$r takeasarrayrQndimstack)rXrfindicesr`X_npselecteds ` rrjz_ArrayAPIWrapper.takes  ? #'8 8 8:at444D?**400 0 v  LdLLMM M 6  PPPQQ Q 199v{{2222'2225555W5551111111H$$XD$999rc0t|||jSNr%)r5rWrXr0r4s rr5z_ArrayAPIWrapper.isdtypesudt7777rN)r$ __module__ __qualname____doc__rZr^rjr5rcrrrTrTzsi  ***...():::::088888rrTc2|dvrtd|dS)N>NrzUnsupported device for NumPy: )rQ)rs r_check_device_cpurxs, ]""D&DDEEE#"rc<tfd}|S)NcZt|dd|i|S)Nr)rxpop)argskwargsfuncs r wrapped_funcz(_accept_device_cpu..wrapped_funcs4&**Xt44555tT$V$$$rr)r~rs` r_accept_device_cpurs4 4[[%%%%[% rceZdZdZhdZhdZdZedZdddd Z d d d d d Z d Z dZ dZ d ddZd ddZdZd S)_NumPyAPIWrapperaRArray API compat wrapper for any numpy version NumPy < 1.22 does not expose the numpy.array_api namespace. This wrapper makes it possible to write code that uses the standard Array API while working with any version of NumPy supported by scikit-learn. See the `get_namespace()` public function for more details. > eyefullonesemptyzerosarangelinspace full_like ones_like empty_like zeros_like> rDrErFrGrHrIrJrKrLrMr?r@ctt|}||jvrt|S||jvrtj|S|SrV)r\r _CREATION_FUNCSr_DTYPESr0)rXr]attrs rr^z_NumPyAPIWrapper.__getattr__sSud## 4' ' '%d++ + 4<  ;t$$ $ rctjSrV)r bool_)rXs rr7z_NumPyAPIWrapper.bools {rTunsafecopycastingc2||||S)Nr)astype)rXrr0rrs rrz_NumPyAPIWrapper.astypesxxD'x:::rN)r0rrct||durtj|d|Stj||S)NT)rr0)r0)rxr arrayrk)rXrr0rrs rrkz_NumPyAPIWrapper.asarraysE&!!! 4<<;qt5999 9=%000 0rc.tj|dS)NT)return_inverser uniquerXrs runique_inversez_NumPyAPIWrapper.unique_inverses|Ad3333rc.tj|dS)NT) return_countsrrs r unique_countsz_NumPyAPIWrapper.unique_countss|AT2222rc*tj|SrVrrs r unique_valuesz_NumPyAPIWrapper.unique_valuess|Arr_c.tj||S)Nr_)r concatenate)rXarraysr`s rconcatz_NumPyAPIWrapper.concats d3333r)rct|ts"td|dt||dur|}t j||S)zGives a new shape to an array without changing its data. The Array API specification requires shape to be a tuple. https://data-apis.org/array-api/latest/API_specification/generated/array_api.reshape.html zshape must be a tuple, got z of type T)rr2 TypeErrortyperr reshape)rXrrrs rrz_NumPyAPIWrapper.reshape sk %'' MeMMU MM  4<<A}Q&&&rc&t|||Srr)r5rss rr5z_NumPyAPIWrapper.isdtypesudt,,,,r)r$rtrurvrrr^propertyr7rrkrrrrrr5rcrrrrs$   O   G   X(,X;;;;;#'t$11111444333&*44444)- ' ' ' ' '-----rrctd}|s tdfSt|ddl}|j|d}}|jdvrt |}||fS)aGet namespace of arrays. Introspect `arrays` arguments and return their common Array API compatible namespace object, if any. NumPy 1.22 and later can construct such containers using the `numpy.array_api` namespace for instance. See: https://numpy.org/neps/nep-0047-array-api-standard.html If `arrays` are regular numpy arrays, an instance of the `_NumPyAPIWrapper` compatibility wrapper is returned instead. Namespace support is not enabled by default. To enabled it call: sklearn.set_config(array_api_dispatch=True) or: with sklearn.config_context(array_api_dispatch=True): # your code here Otherwise an instance of the `_NumPyAPIWrapper` compatibility wrapper is always returned irrespective of the fact that arrays implement the `__array_namespace__` protocol or not. Parameters ---------- *arrays : array objects Array objects. Returns ------- namespace : module Namespace shared by array objects. If any of the `arrays` are not arrays, the namespace defaults to NumPy. is_array_api_compliant : bool True if the arrays are containers that implement the Array API spec. Always False when array_api_dispatch=False. rFrNT>cupy.array_apir#)r_NUMPY_API_WRAPPER_INSTANCErr get_namespacer$rT)rrr namespaceis_array_api_compliants rrr!sV$&:; 2*E110111 (F(8(F(OQU%IBBB$Y// , ,,rct|\}}t|r9|tjt j|Sdd|| zz S)Ng?)rr'rkspecialexpitr exp)rfr&_s r_expitr`se !  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NT)orderr0)r0r)rr'r rrk)rr0rrr&rs r_asarray_with_orderrhs ze$$A2 9 4<<KU%@@@EEM%uEBBBEzz%   zz%u4z888rc|j}|dvr&|S|dkr|jS|dvr|Stj|S)z*Convert X into a NumPy ndarray on the CPU.>array_api_compat.torchtorchr>array_api_compat.cupycupy)r$rr _arraygetrk)rr&xp_names r_convert_to_numpyrsykG555yy{{  """ $ $ $|!!! 5 5 5yy{{ =  rcddlm}||}t|D]K\}}t |dst |t jr ||}t|||L|S)aCreate new estimator which converting all attributes that are arrays. The converter is called on all NumPy arrays and arrays that support the `DLPack interface `__. Parameters ---------- estimator : Estimator Estimator to convert converter : callable Callable that takes an array attribute and returns the converted array. Returns ------- new_estimator : Estimator Convert estimator r)clone __dlpack__) sklearn.baservarsitemsrOrr rsetattr) estimator converterr new_estimatorkey attributes r _estimator_with_converted_arraysrs&#"""""E)$$My////11//Y 9l + + -z)U]/S/S -! ),,I sI.... r)NNN)rvr functoolsrr scipy.specialr_configrfixesrrrr r'r5r,rTrxrrrrrrrrrcrrrs!!   0$    QQQ 3 3 3   F-8-8-8-8-8-8-8-8`FFF c-c-c-c-c-c-c-c-L/.00<-<-<-~$$$999999:    r