Create MultiLegalNeg.py

MultiLegalNeg.py

@@ -0,0 +1,120 @@
+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 = [
+    "german", "french"
+]
+
+
+class MultiLegalNegConfig(datasets.BuilderConfig):
+    
+    def __init__(self, name:str, **kwargs):
+        super( MultiLegalNegConfig, self).__init__(**kwargs)
+        self.name = name
+        self.language = name.split("_")[0]
+
+class MultiLegalNeg(datasets.GeneratorBasedBuilder):
+
+    BUILDER_CONFIG_CLASS = MultiLegalNegConfig
+    
+    BUILDER_CONFIGS = [
+        MultiLegalNegConfig(f"{language}")
+        for language in _LANGUAGES + ['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"),
+                        "token_start": datasets.Value("int64"),
+                        "token_end": datasets.Value("int64"),
+                        "label": datasets.Value("string"),
+                        "text": datasets.Value("string"),
+                        "pattern": datasets.Value("int64")
+                    }
+                ],
+                "tokens": [
+                    {
+                        "text": datasets.Value("string"),
+                        "start": datasets.Value("int64"),
+                        "end": datasets.Value("int64"),
+                        "id": datasets.Value("int64"),
+                        "ws": datasets.Value("bool")
+                    }
+                ],
+                "multineg": datasets.Value("bool")
+            }
+        )
+        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]
+
+        split_generators = []
+        for split in [datasets.Split.TRAIN]:
+            filepaths = []
+            for language in languages:
+                try:
+                    filepaths.append(dl_manager.download((f'data/{language}.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)
+
+