Functions — github.com/huggingface/evaluate

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Functions785 in github.com/huggingface/evaluate

⨍ Functions 785◇ Types & classes 150↳ Endpoints 6

(self, task="token-classification", default_metric_name=None)

src/evaluate/evaluator/token_classification.py:102

(self, task="question-answering", default_metric_name=None)

src/evaluate/evaluator/question_answering.py:93

(self, task="text-classification", default_metric_name=None)

src/evaluate/evaluator/text_classification.py:62

(self, task="image-classification", default_metric_name=None)

src/evaluate/evaluator/image_classification.py:59

(self, task="text-generation", default_metric_name=None, predictions_prefix: str = "generated")

src/evaluate/evaluator/text_generation.py:49

src/evaluate/evaluation_suite/__init__.py:72

(self, prefix="generated", task="text-generation", num_return_sequences=1)

tests/test_evaluator.py:53

(self, prefix="generated", task="text2text-generation")

tests/test_evaluator.py:63

(self, sleep_time=None)

tests/test_evaluator.py:72

tests/test_evaluator.py:83

(self, v2: bool)

tests/test_evaluator.py:91

tests/test_evaluator.py:108

tests/test_evaluator.py:126

tests/test_evaluator.py:134

src/evaluate/utils/logging.py:178

src/evaluate/evaluator/utils.py:17

src/evaluate/evaluator/utils.py:77

Return the number of examples (predictions or predictions/references pair) currently stored in the evaluation module's cache.

src/evaluate/module.py:253

src/evaluate/evaluator/utils.py:11

src/evaluate/evaluator/utils.py:68

Method__post_init__

src/evaluate/info.py:63

Method__post_init__

src/evaluate/evaluation_suite/__init__.py:27

src/evaluate/module.py:259

src/evaluate/evaluation_suite/__init__.py:92

src/evaluate/module.py:52

Function_compute

Returns the scores

templates/{{ cookiecutter.module_slug }}/{{ cookiecutter.module_slug }}.py:89

Returns the number of unique words in the input data

measurements/word_count/word_count.py:63

( self, data, references=None, aggregation=None, )

measurements/regard/regard.py:149

(self, predictions, aggregation="all", toxic_label="hate", threshold=0.5)

measurements/toxicity/toxicity.py:134

( self, data, model_id, batch_size: int = 16, add_start_token: bool = True, device=None, max_length=No

measurements/perplexity/perplexity.py:104

Returns the average word length of the input data

measurements/word_length/word_length.py:92

(self, predictions, groups=None)

measurements/honest/honest.py:185

Returns the fraction of each label present in the data

measurements/label_distribution/label_distribution.py:85

Returns the duplicates contained in the input data and the number of times they are repeated.

measurements/text_duplicates/text_duplicates.py:80

(self, sources, predictions, references)

metrics/wiki_split/wiki_split.py:358

( self, references, prediction_scores, average="macro", sample_weight=

metrics/roc_auc/roc_auc.py:171

(self, sources, predictions, references)

metrics/sari/sari.py:281

(self, predictions, references)

metrics/bleurt/bleurt.py:123

Returns the TREC evaluation scores.

metrics/trec_eval/trec_eval.py:101

(self, predictions, references, labels=None, sample_weight=None, normalize=None)

metrics/confusion_matrix/confusion_matrix.py:83

(self, predictions, references, bleu_kwargs=None, wer_kwargs=None)

metrics/xtreme_s/xtreme_s.py:268

( self, timesteps, rewards, baseline="default", freq_thresh=0.01,

metrics/rl_reliability/rl_reliability.py:106

( self, predictions, references, suffix: bool = False, scheme: Optiona

metrics/seqeval/seqeval.py:120

(self, predictions, references)

metrics/cuad/cuad.py:99

(self, predictions, references, return_pvalue=False)

metrics/pearsonr/pearsonr.py:102

Returns the scores

metrics/frugalscore/frugalscore.py:81

Computes the coefficient of determination (R-squared) of predictions with respect to references. Parameters: predictions

metrics/r_squared/r_squared.py:86

(self, predictions=None, references=None, concatenate_texts=False)

metrics/wer/wer.py:96

(self, predictions, references)

metrics/indic_glue/indic_glue.py:148

(self, predictions, references, sample_weight=None, multioutput="uniform_average", squared=True)

metrics/mse/mse.py:113

(self, predictions, references, concatenate_texts=False)

metrics/cer/cer.py:140

( self, predictions, references, keep_singletons=True, NP_only=False, min_span=False, remove_nested=Fa

metrics/coval/coval.py:293

(self, predictions, references, sample_weight=None, average=None)

metrics/matthews_correlation/matthews_correlation.py:124

(self, predictions, references, n: int = 5, lowercase=False, western_lang=True)

metrics/nist_mt/nist_mt.py:114

(self, predictions, references, return_pvalue=False)

metrics/spearmanr/spearmanr.py:115

(self, predictions, references, sample_weight=None, multioutput="uniform_average")

metrics/mape/mape.py:109

(self, predictions, references)

metrics/xnli/xnli.py:87

( self, predictions, references, labels=None, pos_label=1, ave

metrics/recall/recall.py:116

(self, predictions, references, sample_weight=None, multioutput="uniform_average")

metrics/smape/smape.py:149

( self, predictions: List[str], references: List[List[str]], tokenizer=Tokeniz

metrics/google_bleu/google_bleu.py:150

(self, predictions, references, no_answer_threshold=1.0)

metrics/squad_v2/squad_v2.py:116

( self, predictions, references, normalized: bool = False, ignore_punc

metrics/ter/ter.py:186

( self, predictions, references, num_labels: int, ignore_index: bool,

metrics/mean_iou/mean_iou.py:294

( self, predictions, references, training, periodicity=1, samp

metrics/mase/mase.py:117

(self, X, reference_distribution)

metrics/mahalanobis/mahalanobis.py:74

(self, predictions, references, alpha=0.9, beta=3, gamma=0.5)

metrics/meteor/meteor.py:130

Returns the scores

metrics/competition_math/competition_math.py:87

( self, predictions: Iterable[str], references: Union[Iterable[str], Iterable[Iterable

metrics/character/character.py:117

( self, predictions, model_id, batch_size: int = 16, add_start_token: bool = True, device=None, max_le

metrics/perplexity/perplexity.py:103

(self, predictions, references, normalize=True, sample_weight=None)

metrics/accuracy/accuracy.py:101

( self, predictions, references, lang=None, model_type=None, n

metrics/bertscore/bertscore.py:129

(self, predictions, references, labels=None, pos_label=1, average="binary", sample_weight=None)

metrics/f1/f1.py:126

( self, predictions, references, p_features=None, q_features=None,

metrics/mauve/mauve.py:115

(self, sources, predictions, references, gpus=None, progress_bar=False)

metrics/comet/comet.py:161

( self, predictions, references, zero_division: Union[str, int] = "warn",

metrics/poseval/poseval.py:100

( self, predictions, references, smooth_method="exp", smooth_value=Non

metrics/sacrebleu/sacrebleu.py:140

( self, predictions, references, labels=None, pos_label=1, ave

metrics/precision/precision.py:126

Returns the scores

metrics/code_eval/code_eval.py:155

( self, predictions, references, regexes_to_ignore=None, ignore_case=F

metrics/exact_match/exact_match.py:102

( self, predictions, references, char_order: int = CHRF.CHAR_ORDER, wo

metrics/chrf/chrf.py:159

(self, predictions: Iterable[str], references: Iterable[str])

metrics/charcut_mt/charcut_mt.py:88

(self, predictions, references, sample_weight=None, multioutput="uniform_average")

metrics/mae/mae.py:109

( self, predictions, references, rouge_types=None, use_aggregator=True, use_stemmer=False, tokenizer=N

metrics/rouge/rouge.py:121

(self, predictions, references)

metrics/super_glue/super_glue.py:213

(self, references, predictions, sample_weight=None, pos_label=1)

metrics/brier_score/brier_score.py:130

(self, predictions, references, tokenizer=Tokenizer13a(), max_order=4, smooth=False)

metrics/bleu/bleu.py:115

(self, predictions, references)

metrics/glue/glue.py:142

(self, predictions, references)

metrics/squad/squad.py:93

(self, predictions1, predictions2, references)

comparisons/mcnemar/mcnemar.py:80

(self, predictions1, predictions2)

comparisons/exact_match/exact_match.py:63

(self, predictions1, predictions2)

comparisons/wilcoxon/wilcoxon.py:72

(self, predictions, references)

tests/test_metric.py:24

(self, predictions, references)

tests/test_metric.py:81

(self, predictions=None, references=None)

tests/test_metric.py:582

(self, inputs, targets)

tests/test_metric.py:627

Function_download_and_prepare

Optional: download external resources useful to compute the scores

templates/{{ cookiecutter.module_slug }}/{{ cookiecutter.module_slug }}.py:84

Method_download_and_prepare

(self, dl_manager)

measurements/regard/regard.py:142

Method_download_and_prepare

(self, dl_manager)

measurements/toxicity/toxicity.py:126

Method_download_and_prepare

(self, dl_manager)

measurements/word_length/word_length.py:84

Method_download_and_prepare

(self, dl_manager)

measurements/honest/honest.py:131

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