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EC ???d k""$ G'/'BBF,K !+ . .F   C 63 r+cht|}ttj|d}|S)zMake array interface str.rQ)rrRrSrTrUs r)array_interfacers.$T**I$*Y//99M r+fieldcZd|jvr|jdtd|dSdS)z(Make sure no missing value in meta data.r<Nz"Missing value is not allowed for: )r4rL)r7rs r)check_cudf_metarsE $///  )& 1 =EeEEFFF 0/ = =r+c eZdZdZdejfdejfdejfdejfdejfdejejfdejfd ejfd ejfg Z d S) ArrowSchemaz#The Schema type from arrow C array.formatnamemetadatar n_childrenchildren dictionaryrelease private_dataN) r,r-r.rfrwrc_int64POINTERrx_fields_r&r+r)rrs-- 6?# ! V_% &.! v~& ^V^FO445 v' FO$ ) HHHr+rceZdZdZdS) ArrowArrayz"The Array type from arrow C array.N)r,r-r.rfr&r+r)rrs,,,,r+rr} null_countr n_buffersrrrrr r cbeZdZdZdefdejfdejfdejfdejdzfgZ dS) ArrowDeviceArrayz)The Array type from arrow C device array.rk device_id device_type sync_eventreservedr5N) r,r-r.rfrrwr c_int32rxr r&r+r)rrsR33 * fn% ' v' V^a'( HHHr+r event_hdlc<ddlm}tj|tjtj}|t|jj |j \}||j j kr'| |\}}t|dS)z&Wait for CUDA event exported by arrow.r)runtimeN) cuda.bindingsrrwrr r cudaStreamWaitEventr{contentsrycudaEventWaitDefault cudaError_t cudaSuccesscudaGetErrorStringrL)rcudarteventstatusrmsgs r) wait_eventr's0///// K 6>&.#A#A B BE** #IV #///**6223oo0/r+ct}||j|jp||j|j}|r%t |}t |}||||ffS|jd}|\}}t|t|} t|t|} tj | tj tj} t!| j| jdksJ| j} | jd| jd| jd}}} | J| jdksJ| jdksJ| jdksJtj | tj t0j}|jdvsJ|jd vr t5|d | jdzt8}n)|jd krt;d t;d t5|ddt8}||d}t |}|||ffS)z4Obtain the cuda array interface for cuDF categories.read)moderprrNr5)uUvu)r+r-rr,z9Large string for category index (names) is not supported.zDUnexpected type for category index. It's neither numeric nor string.rr@)rrrErrrOr to_pylibcudf__arrow_c_device_array__PyCapsule_GetPointerPyCapsule_GetNamerwrr rrr'rrrkrrrrrrrr}r{r)rrcp is_num_idx cats_ainf codes_ainf arrow_colschemark array_ptr schema_ptrarrow_device_array arrow_arrayr<rr7 arrow_schemarrrrs r) cudf_cat_infr= s Btz2;772== BJ<<J4-d33 .u55 *tUm33 ))v)66I6688MFE$U,=e,D,DEEI%f.?.G.GHHJ 6>"233!,---  )Q . . . .$*KAAA&D <<<  !Q & & & &  A % % % %   " " " ";z6>++F+FGGPL  "5 5 5 5 5m++ . E;-13D! !    $ $STTT R   )ua9JKKEF 'u - -F 6I< ''r+ceZdZdZdeejegdffdee ddfdZ de fdZ de fdZ defd Zd d ZdS) CategoriesaAn internal storage class for categories returned by the DMatrix and the Booster. This class is designed to be opaque. It is intended to be used exclusively by XGBoost as an intermediate storage for re-coding categorical data. The categories are saved along with the booster object. As a result, users don't need to preserve this class for re-coding. Use the booster model IO instead if you want to preserve the categories in a stable format. .. versionadded:: 3.1.0 .. warning:: This class is internal. .. code-block:: python Xy = xgboost.QuantileDMatrix(X, y, enable_categorical=True) booster = xgboost.train({}, Xy) categories = booster.get_categories() # Get categories # Use categories as a reference for re-coding Xy_new = xgboost.QuantileDMatrix( X_new, y_new, feature_types=categories, enable_categorical=True, ref=Xy ) # Categories will be part of the `model.json`. booster.save_model("model.json") handleN arrow_arraysr"c2|\|_|_||_dSr%)_handle_free _arrow_arrays)r(r@rAs r)__init__zCategories.__init__s $*  dj)r+c<|jtd|jS)aoGet the categories in the dataset. The results are stored in a list of (feature name, arrow array) pairs, with one array for each categorical feature. If a feature is numerical, then the corresponding column in the list is None. A value error will be raised if this container was created without the `export_to_arrow` option. NzHThe `export_to_arrow` option of the `get_categories` method is required.)rErLr's r)rzCategories.to_arrows/   %  !!r+c|jjduS)z$Returns True if there's no category.NrCryr's r)rtzCategories.emptys|!T))r+c6|jjsJ|jjS)z*Internal method for retrieving the handle.rIr's r) get_handlezCategories.get_handles|!!!!|!!r+cJ|jjdS|dSr%)rCryrDr's r)__del__zCategories.__del__s# <  % F r+)r"N)r,r-r.rfrrwrxrr rrFrboolrtrvrKrMr&r+r)r?r?`s> *foxD'99: *|, *  * * * * ", " " " "*t****"C"""" r+r? feature_typescBt|tr|}d}nd}||fS)zGet the optional reference categories from the `feature_types`. This is used by various `DMatrix` where the `feature_types` is reused for specifying the reference categories. N)rur?)rOref_categoriess r)get_ref_categoriesrRs2-,,&  . ((r+AifTypeceZdZUdZgZeeed<dee de ddfdZ de fdZ eedeeeffd ZdS) TransformedDfzInternal class for storing transformed dataframe. 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