Datasets:
				
			
			
	
			
	
		
			
	
		Tasks:
	
	
	
	
	Token Classification
	
	
	Modalities:
	
	
	
		
	
	Text
	
	
	Formats:
	
	
	
		
	
	parquet
	
	
	Sub-tasks:
	
	
	
	
	named-entity-recognition
	
	
	Size:
	
	
	
	
	1M - 10M
	
	
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Update files from the datasets library (from 1.16.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.16.0
- wikiann.py +31 -28
 
    	
        wikiann.py
    CHANGED
    
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         @@ -326,24 +326,24 @@ class Wikiann(datasets.GeneratorBasedBuilder): 
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                def _split_generators(self, dl_manager):
         
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                    wikiann_dl_dir = dl_manager.download_and_extract(_DATA_URL)
         
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                    lang = self.config.name
         
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                    return [
         
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                        datasets.SplitGenerator(
         
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                            name=datasets.Split.VALIDATION,
         
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                            gen_kwargs={"filepath":  
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                        ),
         
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                        datasets.SplitGenerator(
         
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                            name=datasets.Split.TEST,
         
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                            gen_kwargs={"filepath":  
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                        ),
         
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                        datasets.SplitGenerator(
         
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                            name=datasets.Split.TRAIN,
         
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                            gen_kwargs={"filepath":  
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                        ),
         
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                    ]
         
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                def _generate_examples(self, filepath):
         
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                    """Reads line by line format of the NER dataset and generates examples.
         
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                    Input Format:
         
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                    en:rick  B-PER
         
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         @@ -365,27 +365,30 @@ class Wikiann(datasets.GeneratorBasedBuilder): 
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                        Examples with the format listed above.
         
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                    """
         
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                    guid_index = 1
         
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                                splits = line.split("\t")
         
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                                # strip out en: prefix
         
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                                langs.append(splits[0].split(":")[0])
         
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                                tokens.append(":".join(splits[0].split(":")[1:]))
         
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                                if len(splits) > 1:
         
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                                    ner_tags.append(splits[-1].replace("\n", ""))
         
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                                else:
         
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                                    #  
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                def _split_generators(self, dl_manager):
         
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                    wikiann_dl_dir = dl_manager.download_and_extract(_DATA_URL)
         
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                    lang = self.config.name
         
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                    lang_archive = os.path.join(wikiann_dl_dir, lang + ".tar.gz")
         
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                    return [
         
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                        datasets.SplitGenerator(
         
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                            name=datasets.Split.VALIDATION,
         
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                            gen_kwargs={"filepath": "dev", "files": dl_manager.iter_archive(lang_archive)},
         
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                        ),
         
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                        datasets.SplitGenerator(
         
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                            name=datasets.Split.TEST,
         
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                            gen_kwargs={"filepath": "test", "files": dl_manager.iter_archive(lang_archive)},
         
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                        ),
         
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                        datasets.SplitGenerator(
         
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                            name=datasets.Split.TRAIN,
         
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                            gen_kwargs={"filepath": "train", "files": dl_manager.iter_archive(lang_archive)},
         
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                        ),
         
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                    ]
         
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                def _generate_examples(self, filepath, files):
         
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                    """Reads line by line format of the NER dataset and generates examples.
         
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                    Input Format:
         
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                    en:rick  B-PER
         
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                        Examples with the format listed above.
         
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                    """
         
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                    guid_index = 1
         
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                    for path, f in files:
         
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                        if path == filepath:
         
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                            tokens = []
         
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                            ner_tags = []
         
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                            langs = []
         
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                            for line in f:
         
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                                line = line.decode("utf-8")
         
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                                if line == "" or line == "\n":
         
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                                    if tokens:
         
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                                        spans = self._get_spans(tokens, ner_tags)
         
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                                        yield guid_index, {"tokens": tokens, "ner_tags": ner_tags, "langs": langs, "spans": spans}
         
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                                        guid_index += 1
         
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                                        tokens = []
         
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                                        ner_tags = []
         
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                                        langs = []
         
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                                else:
         
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                                    # wikiann data is tab separated
         
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                                    splits = line.split("\t")
         
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                                    # strip out en: prefix
         
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                                    langs.append(splits[0].split(":")[0])
         
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                                    tokens.append(":".join(splits[0].split(":")[1:]))
         
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                                    if len(splits) > 1:
         
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                                        ner_tags.append(splits[-1].replace("\n", ""))
         
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                                    else:
         
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                                        # examples have no label in test set
         
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                                        ner_tags.append("O")
         
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                            break
         
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