o .wi6.@sddlZddlmZddlmZmZmZmZmZm Z ddl Z ddl m Z ddl m Z ddlmZddlmZddlmZdd lmZdd lmZdd lmZdd lmZdd lmZddlmZddl m!Z!ddl"m#Z#ddl$m%Z%ddl&m'Z'ddl(m)Z)ddl*m+Z+ddl,m-Z-ddl.m/Z/ddl0m1Z1ddgiZ2e/sddgZ3e4e5e e5e4e5e e6e5e6e7ffffZ8e e8e6e8fZ9                d{d!e e6e5e4e5e ffd"e e6e5e4e5e ffd#ee5d$ee7d%e:d&ee d'ed(eee e4e5e fge fd)e:d*e:d+ee e5e j;fd,e7d-e7d.e7d/e:d0e5d1e:d2ee5d3ee5d4e4e5e e e6e<e5fff(d5dZ=   d|d!e e5ee5fd"ee e5ee5fd6e7d7e:d8eee<d4e f d9d:Z>d!e e5e6e5fd"e e5e6e5fd4e fd;d<Z? = > ?   d}d!e e5ee5fd"ee e5ee5fd@e7dAe7dBe>> preds = ["hello there", "general kenobi"] >>> target = ["hello there", "master kenobi"] >>> score = _bert_score(preds, target) >>> from pprint import pprint >>> pprint(score) {'f1': tensor([1.0000, 0.9961]), 'precision': tensor([1.0000, 0.9961]), 'recall': tensor([1.0000, 0.9961])} r textr%r&r'r(r)r*r+r,r-r.r/r0r1r2r3r4r5r6r7N)rr )r%r&r'r(r)r*r+r,r-r.r/r0r1r2r3r4r5r6r7r:r:e/home/ubuntu/sommelier/.venv/lib/python3.10/site-packages/torchmetrics/functional/text/_deprecated.pyr'sP !     n_gramsmoothweightscCstddt|||||dS)zWrapper for deprecated import. >>> preds = ['the cat is on the mat'] >>> target = [['there is a cat on the mat', 'a cat is on the mat']] >>> _bleu_score(preds, target) tensor(0.7598) r r9r%r&r<r=r>)rr r?r:r:r; _bleu_score`s r@cCtddt||dS)zWrapper for deprecated import. >>> preds = ["this is the prediction", "there is an other sample"] >>> target = ["this is the reference", "there is another one"] >>> _char_error_rate(preds=preds, target=target) tensor(0.3415) r r9r%r&)rr rBr:r:r;_char_error_rates rC@ n_char_order n_word_orderbeta lowercase whitespacereturn_sentence_level_scorec C"tddt||||||||dS)zWrapper for deprecated import. >>> preds = ['the cat is on the mat'] >>> target = [['there is a cat on the mat', 'a cat is on the mat']] >>> _chrf_score(preds, target) tensor(0.8640) rr9r%r&rHrIrJrKrLrM)rrrOr:r:r; _chrf_score rP333333?皙??language)r$jaalpharhodeletion insertionc CrN)zWrapper for deprecated import. >>> preds = ["this is the prediction", "here is an other sample"] >>> target = ["this is the reference", "here is another one"] >>> _extended_edit_distance(preds=preds, target=target) tensor(0.3078) rr9r%r&rUrMrWrXrYrZ)rrr[r:r:r;_extended_edit_distancerQr\bert-base-uncased? kl_divergenceT temperatureinformation_measurecCs.tddt|||||||||| | | | | dS)a<Wrapper for deprecated import. >>> preds = ['he read the book because he was interested in world history'] >>> target = ['he was interested in world history because he read the book'] >>> _infolm(preds, target, model_name_or_path='google/bert_uncased_L-2_H-128_A-2', idf=False) tensor(-0.1784) rr9r%r&r'r`rar.rWrJr/r0r1r2r-rM)rrrbr:r:r;r s" cCrA)zWrapper for deprecated import. >>> preds = ["this is the prediction", "there is an other sample"] >>> target = ["this is the reference", "there is another one"] >>> _match_error_rate(preds=preds, target=target) tensor(0.4444) rr9rB)rrrBr:r:r;_match_error_raterDrc ignore_indexcCstddt|||dS)zWrapper for deprecated import. >>> from torch import rand, randint >>> preds = rand(2, 8, 5) >>> target = randint(5, (2, 8)) >>> target[0, 6:] = -100 >>> _perplexity(preds, target, ignore_index=-100) tensor(5.8540) rr9r%r&rd)rrrer:r:r; _perplexitys rfbestrouge1rouge2rougeL rougeLsum accumulate)avgrg use_stemmer normalizer tokenizer rouge_keys.c C tddt|||||||dS)aWrapper for deprecated import. >>> preds = "My name is John" >>> target = "Is your name John" >>> from pprint import pprint >>> pprint(_rouge_score(preds, target)) {'rouge1_fmeasure': tensor(0.7500), 'rouge1_precision': tensor(0.7500), 'rouge1_recall': tensor(0.7500), 'rouge2_fmeasure': tensor(0.), 'rouge2_precision': tensor(0.), 'rouge2_recall': tensor(0.), 'rougeL_fmeasure': tensor(0.5000), 'rougeL_precision': tensor(0.5000), 'rougeL_recall': tensor(0.5000), 'rougeLsum_fmeasure': tensor(0.5000), 'rougeLsum_precision': tensor(0.5000), 'rougeLsum_recall': tensor(0.5000)} rr9r%r&rmrorprqrr)rrrtr:r:r;rs 13atokenize)noneruzhintlcharc Crs)zWrapper for deprecated import. >>> preds = ['the cat is on the mat'] >>> target = [['there is a cat on the mat', 'a cat is on the mat']] >>> _sacre_bleu_score(preds, target) tensor(0.7598) rr9r%r&r<r=rvrKr>)rrr{r:r:r;_sacre_bleu_score. r|cCrA)a3Wrapper for deprecated import. >>> preds = [{"prediction_text": "1976", "id": "56e10a3be3433e1400422b22"}] >>> target = [{"answers": {"answer_start": [97], "text": ["1976"]},"id": "56e10a3be3433e1400422b22"}] >>> _squad(preds, target) {'exact_match': tensor(100.), 'f1': tensor(100.)} rr9rB)rrrBr:r:r;_squadKrDr~ normalizeno_punctuation asian_supportc Crs)zWrapper for deprecated import. >>> preds = ['the cat is on the mat'] >>> target = [['there is a cat on the mat', 'a cat is on the mat']] >>> _translation_edit_rate(preds, target) tensor(0.1538) rr9r%r&rrrKrrM)rrrr:r:r;_translation_edit_rateXr}rcCrA)zWrapper for deprecated import. >>> preds = ["this is the prediction", "there is an other sample"] >>> target = ["this is the reference", "there is another one"] >>> _word_error_rate(preds=preds, target=target) tensor(0.5000) rr9rB)rrrBr:r:r;_word_error_rateurDrcCrA)zWrapper for deprecated import. >>> preds = ["this is the prediction", "there is an other sample"] >>> target = ["this is the reference", "there is another one"] >>> _word_information_lost(preds, target) tensor(0.6528) rr9rB)rrrBr:r:r;_word_information_lostrDrcCrA)zWrapper for deprecated import. >>> preds = ["this is the prediction", "there is an other sample"] >>> target = ["this is the reference", "there is another one"] >>> _word_information_preserved(preds, target) tensor(0.3472) rr9rB)rrrBr:r:r;_word_information_preservedrDr)NNFNNNFFNr!r"r#Fr$FNN)r#FN)rErFrGFFF)r$FrGrRrSrT) r]r^r_TNNNNr"rTF)N)rgFNNrh)r#FruFN)FFTFF)Noscollections.abcrtypingrrrrrrtorchr torch.nnr !torchmetrics.functional.text.bertr !torchmetrics.functional.text.bleur torchmetrics.functional.text.cerr !torchmetrics.functional.text.chrfr torchmetrics.functional.text.eedr#torchmetrics.functional.text.infolmr+_INFOLM_ALLOWED_INFORMATION_MEASURE_LITERALr torchmetrics.functional.text.merr'torchmetrics.functional.text.perplexityr"torchmetrics.functional.text.rouger'torchmetrics.functional.text.sacre_bleur"torchmetrics.functional.text.squadr torchmetrics.functional.text.terr torchmetrics.functional.text.werr torchmetrics.functional.text.wilr torchmetrics.functional.text.wiprtorchmetrics.utilities.importsrtorchmetrics.utilities.printsr__doctest_requires____doctest_skip__dictstrlistintSQUAD_SINGLE_TARGET_TYPESQUAD_TARGETS_TYPEboolr/floatrr@rCtuplerPr\PathLiker rcrfrr|r~rrrrr:r:r:r;s                       ,      <  . 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