updata sweana

SuperLim.py

@@ -179,6 +179,16 @@ class SuperLim(datasets.GeneratorBasedBuilder):
                     # These are the features of your dataset like images, labels ...
                 }
             )
+        elif self.config.name == "sweana":
+            features = datasets.Features(
+                {
+                    "A": datasets.Value("string"),
+                    "B": datasets.Value("string"),
+                    "C": datasets.Value("string"),
+                    "D": datasets.Value("string"),
+                    "relation": datasets.Value("string"),
+                }
+            )
         else:  # This is an example to show how to have different features for "first_domain" and "second_domain"
             features = datasets.Features(
                 {
@@ -213,37 +223,49 @@ class SuperLim(datasets.GeneratorBasedBuilder):
         # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
         #urls = _URLS[self.config.name]
 
-        data_dir_test = dl_manager.download_and_extract(os.path.join(_URL,_TASKS[self.config.name],"test.csv"))
-        data_dir_train = dl_manager.download_and_extract(os.path.join(_URL,_TASKS[self.config.name],"train.csv"))
-        data_dir_dev = dl_manager.download_and_extract(os.path.join(_URL,_TASKS[self.config.name],"dev.csv"))
-    
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": data_dir_train,
-                    "split": "train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": data_dir_test,
-                    "split": "test"
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": data_dir_dev,
-                    "split": "dev",
-                },
-            ),
-        ]
+        if self.config.name == "dalaj":
+            data_dir_test = dl_manager.download_and_extract(os.path.join(_URL,_TASKS[self.config.name],"test.csv"))
+            data_dir_train = dl_manager.download_and_extract(os.path.join(_URL,_TASKS[self.config.name],"train.csv"))
+            data_dir_dev = dl_manager.download_and_extract(os.path.join(_URL,_TASKS[self.config.name],"dev.csv"))
 
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": data_dir_train,
+                        "split": "train",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": data_dir_test,
+                        "split": "test"
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.VALIDATION,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": data_dir_dev,
+                        "split": "dev",
+                    },
+                ),
+            ]
+        else:
+            data_dir_test = dl_manager.download_and_extract(os.path.join(_URL, _TASKS[self.config.name], "test.csv"))
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": data_dir_test,
+                        "split": "test"
+                    },
+                ),
+            ]
    
     # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
     def _generate_examples(self, filepath, split):
@@ -257,6 +279,14 @@ class SuperLim(datasets.GeneratorBasedBuilder):
                     "original sentence": row["original sentence"],
                     "corrected sentence": row["corrected sentence"],
                 }
+            elif self.config.name == "sweana":
+                yield key, {
+                    "A": row["A"],
+                    "B": row["B"],
+                    "C": row["C"],
+                    "D": row["D"],
+                    "relation": row["relation"],
+                }
             else:
                 yield key, {
                     "sentence": data["sentence"],

data/SweAna/dev.csv

@@ -1,2 +0,0 @@
-A,B,C,D,relation
-dummy,dummy,dummy,dummy,dummy

data/SweAna/train.csv

@@ -1,2 +0,0 @@
-A,B,C,D,relation
-dummy,dummy,dummy,dummy,dummy,

data/SweWgr/.~lock.test.csv#

@@ -1 +0,0 @@
-,severin,data,25.01.2022 14:43,file:///home/severin/.config/libreoffice/4;