Upload stock11.py

stock11.py

@@ -0,0 +1,104 @@
+
+from datasets import Value, ClassLabel,Sequence
+import datasets
+
+
+_STOCK11_CITATION = """\
+
+"""
+
+_STOCK11_DESCRIPTION = """\
+GLUE, the General Language Understanding Evaluation benchmark
+(https://gluebenchmark.com/) is a collection of resources for training,
+evaluating, and analyzing natural language understanding systems.
+"""
+
+class STOCK11Config(datasets.BuilderConfig):
+
+    def __init__(
+        self,
+        text_features,
+        label_column,
+        data_url,
+        data_dir,
+        citation,
+        url,
+        label_classes=None,
+        process_label=lambda x: x,
+        **kwargs,
+    ):
+        super(STOCK11Config, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
+        
+        self.text_features = text_features
+        self.label_column = label_column
+        self.label_classes = label_classes
+        self.data_url = data_url
+        self.data_dir = data_dir
+        self.citation = citation
+        self.url = url
+        self.process_label = process_label
+
+class STOCK11(datasets.GeneratorBasedBuilder):
+    domain_list = ['airline', 'car', 'communication', 'energy', 'finance', 'manufacture', 'medical', 'Real estate', 'tech', 'traffic', 'wine']
+
+    BUILDER_CONFIGS  = [
+        STOCK11Config(name=domain_name, 
+                    description= f'comments of {domain_name}.', 
+                    text_features={'sentence':'sentence', 'domain':'domain'}, 
+                    label_classes=['POS','NEG', 'NEU'], 
+                    label_column='label',
+                    citation="",
+                    data_dir= "",
+                    data_url = r"https://huggingface.co/datasets/kuroneko3578/stock11/blob/main/data.7z",
+                    url='https://github.com/ws719547997/LNB-DA')
+        for domain_name in domain_list
+    ]
+
+    def _info(self):
+        features = {'id':Value(dtype='int32', id=None),
+            'domain':Value(dtype='string', id=None),
+            'label':ClassLabel(num_classes=3, names=['POS','NEG', 'NEU'], names_file=None, id=None),
+            'rank':Value(dtype='int32', id=None),
+            'sentence':Value(dtype='string', id=None)}
+
+        return datasets.DatasetInfo(
+            description=_STOCK11_DESCRIPTION,
+            features=datasets.Features(features),
+            homepage=self.config.url,
+            citation=self.config.citation + "\n" + _STOCK11_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded_file = dl_manager.download_and_extract(self.config.data_url)
+        print(downloaded_file)
+
+        test_file = rf'{downloaded_file}\data\test\{self.config.name}.txt'
+        dev_file = rf'{downloaded_file}\data\dev\{self.config.name}.txt'
+        train_file = rf'{downloaded_file}\data\train\{self.config.name}.txt'
+        return [datasets.SplitGenerator(name=datasets.Split.TEST,
+                                        gen_kwargs={
+                                            "data_file": test_file,
+                                            "split": "test",
+                                        },), 
+                datasets.SplitGenerator(name=datasets.Split.VALIDATION,
+                                        gen_kwargs={
+                                            "data_file": dev_file,
+                                            "split": "dev",
+                                        },), 
+                datasets.SplitGenerator(name=datasets.Split.TRAIN,
+                                        gen_kwargs={
+                                            "data_file": train_file,
+                                            "split": "train",
+                                        },)]
+
+    def _generate_examples(self, data_file, split):
+        with open(data_file, 'r', encoding='utf-8') as f:
+            for line in f:
+                lin = line.strip()
+                if not lin:
+                    continue
+                lin_sp = lin.split('\t')
+                if len(lin_sp) < 5:
+                    continue
+                # id, {example}
+                yield lin_sp[0], {'sentence':lin_sp[4],'domain':lin_sp[1], 'label':lin_sp[2], 'id':lin_sp[0], 'rank':lin_sp[3]}