hBSSKrSSKrSSKJr SSKJrJrJrJrJ r J r SSK J r J r SSKJr SSKJr SSKJr SS KJr SS KJr SS KJrJr SS KJr SS KJr SSKJ r Sr!\ "5RE\!5Sr#Sr$Sr%S\\S\\&\44Sjr'Sr("SS\ 5r)Sr*g)N)islice)AnyCallableDictIterableListOptional)ConfigModel)Floats2d)Errors)Language)Scorer)Doc)Examplevalidate_get_examples)registry)Vocab)TextCategorizeraX [model] @architectures = "spacy.TextCatEnsemble.v2" [model.tok2vec] @architectures = "spacy.Tok2Vec.v2" [model.tok2vec.embed] @architectures = "spacy.MultiHashEmbed.v2" width = 64 rows = [2000, 2000, 500, 1000, 500] attrs = ["NORM", "LOWER", "PREFIX", "SUFFIX", "SHAPE"] include_static_vectors = false [model.tok2vec.encode] @architectures = "spacy.MaxoutWindowEncoder.v2" width = ${model.tok2vec.embed.width} window_size = 1 maxout_pieces = 3 depth = 2 [model.linear_model] @architectures = "spacy.TextCatBOW.v3" exclusive_classes = false length = 262144 ngram_size = 1 no_output_layer = false modelzq [model] @architectures = "spacy.TextCatBOW.v3" exclusive_classes = false ngram_size = 1 no_output_layer = false aa [model] @architectures = "spacy.TextCatReduce.v1" exclusive_classes = false use_reduce_first = false use_reduce_last = false use_reduce_max = false use_reduce_mean = true [model.tok2vec] @architectures = "spacy.HashEmbedCNN.v2" pretrained_vectors = null width = 96 depth = 4 embed_size = 2000 window_size = 1 maxout_pieces = 3 subword_features = true examplesreturnc 6[R"US4SS0UD6$)Ncats multi_labelT)r score_cats)rkwargss [/home/james-whalen/.local/lib/python3.13/site-packages/spacy/pipeline/textcat_multilabel.pytextcat_multilabel_scorer!Ms/        c[$)N)r!r"r make_textcat_multilabel_scorerr%Vs ##r"c\rSrSrSrS\S.S\S\S\S\ S\ \ S S 4 S jjjr \ S 5rS S S .S\ /\\4S\ \S\ \\4SjjrS\\4SjrSrg )MultiLabel_TextCategorizerZzdPipeline component for multi-label text classification. DOCS: https://spacy.io/api/textcategorizer )scorervocabrname thresholdr)rNclXlX lX0lSUl/US.n[ U5UlXPlg)aInitialize a text categorizer for multi-label classification. vocab (Vocab): The shared vocabulary. model (thinc.api.Model): The Thinc Model powering the pipeline component. name (str): The component instance name, used to add entries to the losses during training. threshold (float): Cutoff to consider a prediction "positive". scorer (Optional[Callable]): The scoring method. DOCS: https://spacy.io/api/textcategorizer#init N)labelsr,)r*rr+_rehearsal_modeldictcfgr))selfr*rr+r,r)r1s r __init__#MultiLabel_TextCategorizer.__init__`s5(   $)49 r"cg)NTr$)r2s r support_missing_values1MultiLabel_TextCategorizer.support_missing_values|sr")nlpr. get_examplesr8r.c[US5 Uc=U"5H1nURRHnURU5 M M3 OUHnURU5 M [ [ U"5S55nUR U5 UVs/sHoRPM n nURU5upUR5 [U 5S:d,[RRURS95e[U 5S:d,[RRURS95eURR!XS9 gs snf)aInitialize the pipe for training, using a representative set of data examples. get_examples (Callable[[], Iterable[Example]]): Function that returns a representative sample of gold-standard Example objects. nlp (Language): The current nlp object the component is part of. labels: The labels to add to the component, typically generated by the `init labels` command. If no labels are provided, the get_examples callback is used to extract the labels from the data. DOCS: https://spacy.io/api/textcategorizer#initialize z%MultiLabel_TextCategorizer.initializeN r)r+)XY)ryr add_labellistr_validate_categories reference_examples_to_truth_require_labelslenrE923formatr+r initialize) r2r9r8r.examplecatlabelsubbatcheg doc_sample label_sample_s r rH%MultiLabel_TextCategorizer.initializes & l,ST >'>"99>>CNN3'** u% |~r23 !!(+-56XrllX 611(;  :"FFKK$6$6DII$6$FF"< 1$Hfkk&8&8dii&8&HH$  ; 7sE rcUHbnURRR5H7nUS:XaM US:XaM[[R R US95e Md g)zThis component allows any type of single- or multi-label annotations. This method overwrites the more strict one from 'textcat'.g?g)valN)rBrvalues ValueErrorrE851rG)r2rexrSs r rA/MultiLabel_TextCategorizer._validate_categoriessUB||((//1s cSj$V[[%7%7C%7%@AA2r")r/r1rr+r)r*)textcat_multilabel)__name__ __module__ __qualname____firstlineno____doc__r!rr strfloatr rr3propertyr6rrrrHrA__static_attributes__r$r"r r'r'Zs) &>   " 8#'*. #<r8G#445#<h  #< #' #Br"r'c|US:Xa"[R"S5nUR$[S[SU35e)Nmake_multilabel_textcatzspacy.pipeline.factorieszmodule z has no attribute ) importlib import_modulerdAttributeErrorrZ)r+modules r __getattr__risA (((()CD--- 78*,>tfE FFr")+resys itertoolsrtypingrrrrrr thinc.apir r thinc.typesr errorsrlanguagerr)rtokensrtrainingrrutilrr*rtextcatrmulti_label_default_configfrom_strDEFAULT_MULTI_TEXTCAT_MODELmulti_label_bow_configmulti_label_cnn_configr_r!r%r'rir$r"r rzs @@# 5$8%h//0JKGT*x'8tCQTH~$RBRBlGr"