Datasets:
rcds
/

File size: 4,017 Bytes
6f4e2b6
16f6032
 
6f4e2b6
16f6032
6f4e2b6
 
 
 
 
16f6032
6f4e2b6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
58be895
6f4e2b6
 
58be895
6f4e2b6
 
 
 
58be895
6f4e2b6
58be895
6f4e2b6
 
58be895
6f4e2b6
 
 
 
 
 
 
4b9bb52
dc144a2
6f4e2b6
 
 
581a7d6
6f4e2b6
16f6032
6f4e2b6
dc144a2
 
6f4e2b6
 
 
 
 
 
 
4b9bb52
 
6f4e2b6
 
 
 
 
 
 
 
 
 
16f6032
6f4e2b6
 
 
 
 
 
 
 
 
 
af0f917
6f4e2b6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
import json

import datasets
import pandas as pd
from huggingface_hub.file_download import hf_hub_url

try:
    import lzma as xz
except ImportError:
    import pylzma as xz

datasets.logging.set_verbosity_info()
logger = datasets.logging.get_logger(__name__)

_DESCRIPTION ="""\

    """

_HOMEPAGE =  ""

_LICENSE = ""

_CITATION = ""

_URL = {
    'data/'
}
_LANGUAGES = [
    "fr","it","es","en","de","pt"
]

_TYPES = [
    "laws", "judgements"
]

_SOURCES = [
    "MultiLegalPile", "Wipolex", "Jug", "BVA", "CC", "IP", "SCOTUS", "SwissJudgementPrediction"
    "Gesetz", "Constitution", "CivilCode", "CriminalCode",
]

_HIGHEST_NUMBER_OF_SHARDS = 4
class MultiLegalSBDConfig(datasets.BuilderConfig):
    
    def __init__(self, name:str, **kwargs):
        super( MultiLegalSBDConfig, self).__init__(**kwargs)
        self.name = name
        self.language = name.split("_")[0]
        self.type = name.split("_")[1]

class MultiLegalSBD(datasets.GeneratorBasedBuilder):

    BUILDER_CONFIG_CLASS = MultiLegalSBDConfig
    
    BUILDER_CONFIGS = [
        MultiLegalSBDConfig(f"{language}_{type}")
        for language in _LANGUAGES + ['all']
        for type in _TYPES  + ["all"]
    ]
    DEFAULT_CONFIG_NAME = 'all_all'
    def _info(self):
        features = datasets.Features(
            {   
                "text": datasets.Value("string"),        
                "spans": [
                    {
                        "start": datasets.Value("int64"),
                        "end": datasets.Value("int64"),
                        "label": datasets.Value("string"),
                        "token_start": datasets.Value("int64"),
                        "token_end": datasets.Value("int64")                    
                    }
                ],
                "tokens": [
                    {
                        "text": datasets.Value("string"),
                        "start": datasets.Value("int64"),
                        "end": datasets.Value("int64"),
                        "id": datasets.Value("int64"),
                        "ws": datasets.Value("bool")
                    }
                ],
                "source": datasets.Value("string")
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features = features,
            homepage = _HOMEPAGE,
            citation=_CITATION
        )
    
    def _split_generators(self, dl_manager):
        
        languages = _LANGUAGES if self.config.language == "all" else [self.config.language]
        types = _TYPES if self.config.type == 'all' else [self.config.type]

        split_generators = []
        for split in [datasets.Split.TRAIN]:
            filepaths = []
            for language in languages:
                for type in types:
                    for shard in range(_HIGHEST_NUMBER_OF_SHARDS):
                        try:
                            filepaths.append(dl_manager.download((f'data/{language}_{type}_{shard}.jsonl.xz')))
                        except:
                            break

            split_generators.append(
                datasets.SplitGenerator(name=split, gen_kwargs={'filepaths': filepaths})
            )
            
        return split_generators     

    def _generate_examples(self,filepaths):
        id_ = 0
        for filepath in filepaths:
            if filepath:
                logger.info("Generating examples from = %s", filepath)
                try:
                    with xz.open(open(filepath,'rb'), 'rt', encoding='utf-8') as f:
                        json_list = list(f)
                    
                    for json_str in json_list:
                        example = json.loads(json_str)
                        if example is not None and isinstance(example, dict):
                            yield id_, example
                            id_ +=1

                except Exception:
                    logger.exception("Error while processing file %s", filepath)