import json import pandas as pd import datasets _DESCRIPTION = """\ This dataset consists of Suomi24 comments which have been labeled by human raters for toxic behavior. """ _HOMEPAGE = "https://turkunlp.org/" _URLS = { "test": "https://huggingface.co/datasets/TurkuNLP/Suomi24-toxicity-annotated/resolve/main/all_annotations.tsv" } class Suomi24ToxicityPred(datasets.GeneratorBasedBuilder): """This is a dataset of comments sampled from Suomi24 and annotated using jigsaw toxicity labels.""" VERSION = datasets.Version("1.1.0") def _info(self): return datasets.DatasetInfo( # This is the description that will appear on the datasets page. description=_DESCRIPTION, # This defines the different columns of the dataset and their types features=datasets.Features( { "text": datasets.Value("string"), "label": datasets.Value("string") # we only have one label for each text } ), # If there's a common (input, target) tuple from the features, # specify them here. They'll be used if as_supervised=True in # builder.as_dataset. supervised_keys=None, # Homepage of the dataset for documentation homepage=_HOMEPAGE ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" # This method is tasked with downloading/extracting the data and defining the splits depending on the configuration # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name urls_to_download = _URLS downloaded_files = dl_manager.download_and_extract(urls_to_download) return [ datasets.SplitGenerator( name="test", # These kwargs will be passed to _generate_examples gen_kwargs={ "filepath": downloaded_files["test"], "split": "test", }, ), ] def _generate_examples(self, filepath): """Yields examples.""" # This method will receive as arguments the `gen_kwargs` defined in the previous `_split_generators` method. # It is in charge of opening the given file and yielding (key, example) tuples from the dataset # The key is not important, it's more here for legacy reason (legacy from tfds) # read the tsv file with open(filepath, "r") as f: data = f.readlines() data = data[1:] for i in range(len(data)): data[i] = data[i].replace("\n", "") data[i] = data[i].split("\t") assert len(data[i]) == 3 from collections import Counter from itertools import count ids = [one[0] for one in data] c = Counter(ids) iters = {k: count(1) for k, v in c.items() if v > 1} output_list = [x+str(next(iters[x])) if x in iters else x for x in ids] count = 0 # here make the data into a proper thing for one in data: example = {} text_id = output_list[count] # change this somehow count = count + 1 example["text"] = one[2] example["label"] = one[1] yield (text_id, example)