Update mindgames.py

mindgames.py

@@ -25,104 +25,40 @@ DESCRIPTION = """\
 mindgames json tasks
 """
 
-DATA_URL = "https://www.dropbox.com/s/xeh8k1gu1j51ktu/mindgames-v1.zip?dl=1"
+CONFIGS=['forehead','forehead_mirror','explicit','internal','all']
+_URLs = {(x,y):f'https://huggingface.co/datasets/sileod/mindgames/resolve/main/data/{x}-{y}.jsonl' for x in ['train','validation','test'] for y in CONFIGS}
+files = ['-'.join(x) for x in _URLs]
 
-CONFIGS=['forehead','forehead-mirror','explicit','internal','all']
 
-class mindgames_Config(datasets.BuilderConfig):
-    """BuilderConfig for mindgames."""
 
-    def __init__(
-        self,
-        text_features,
-        label_classes=None,
-        **kwargs,
-    ):
-        """BuilderConfig for mindgames.
-        Args:
-          text_features: `dict[string, string]`, map from the name of the feature
-            dict for each text field to the name of the column in the tsv file
-          data_url: `string`, url to download the zip file from
-          data_dir: `string`, the path to the folder containing the tsv files in the
-            downloaded zip
-          citation: `string`, citation for the data set
-          url: `string`, url for information about the data set
-        """
-
-        super(mindgames_Config, self).__init__(
-            version=datasets.Version("1.0.0", ""), **kwargs
-        )
-
-        self.text_features = text_features
-        self.data_url = DATA_URL
-        self.data_dir = self.name#os.path.join("", self.name)
-        self.citation = textwrap.dedent(CITATION)
-        self.description = ""
 
+class mindgamesConfig(datasets.BuilderConfig):
+    citation=CITATION
 
 class mindgames(datasets.GeneratorBasedBuilder):
-
-    """The General Language Understanding Evaluation (mindgames) benchmark."""
-
-    BUILDER_CONFIG_CLASS = mindgames_Config
-    DEFAULT_CONFIG_NAME = "all"
-
+    
     BUILDER_CONFIGS = [
-        mindgames_Config(
-            name=name,
-            text_features={"inputs": "inputs"},
-        ) for name in CONFIGS
+            mindgamesConfig(
+                name=n,
+                data_dir=n
+            ) for n in CONFIGS
     ]
 
-    def _info(self):
-        features = {
-            "hypothesis": datasets.Value("string"),
-            "premise": datasets.Value("string"),
-            "label": datasets.Value("int32"),
-            "n_announcements": datasets.Value("int32"),
-            "n_agents": datasets.Value("int32"),
-            "hypothesis_depth": datasets.Value("int32"), 
-            "index": datasets.Value("int32")
-
-        }       
-        for k in ['smcdel_problem',"pbcheck","names","setup","s-l","deberta_pred","deberta_confidence","difficulty"]:
-            features[k]=datasets.Value("string")
-        return datasets.DatasetInfo(
-            description=DESCRIPTION,
-            features=datasets.Features(features),
-            citation=self.config.citation + "\n" + CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        data_dir = dl_manager.download_and_extract(self.config.data_url)
-
+    def _split_generators(self, dl_manager: datasets.DownloadManager):
+        data_file = dl_manager.download(_URLs)
         return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "data_file": f"{data_dir}/train-{self.config.name}.jsonl",
-                    "split": "train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "data_file": f"{data_dir}/validation-{self.config.name}.jsonl",
-                    "split": "test",
-                },
-            ),           
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "data_file": f"{data_dir}/test-{self.config.name}.jsonl",
-                    "split": "validation",
-                },
-            ),
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_file['train',self.config.data_dir]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": data_file['validation',self.config.data_dir]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_file['test',self.config.data_dir]}),
+            
         ]
 
-    def _generate_examples(self, data_file,split):
+    def _info(self):
+        return datasets.DatasetInfo()
+    def _generate_examples(self, filepath):
+        print(filepath)
         """Yields examples."""
-        with open(data_file, "r", encoding="utf-8") as f:
+        with open(filepath, "r", encoding="utf-8") as f:
             for id_, line in enumerate(f):
                 line_dict = json.loads(line)
                 yield id_, line_dict