Uploaded two files

DiscoEval.py

@@ -35,7 +35,6 @@ This dataset contains all tasks of the DiscoEval benchmark for sentence represen
 
 _HOMEPAGE = "https://github.com/ZeweiChu/DiscoEval"
 
-
 # TODO: Add link to the official dataset URLs here
 # The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
@@ -180,48 +179,26 @@ class DiscoEvalSentence(datasets.GeneratorBasedBuilder):
         # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
         # 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 = dl_manager.download_and_extract(urls)
-
+        data_dir = ''
+        train_name = ''
+        valid_name = ''
+        test_name = ''
         if self.config.name in [constants.SPARXIV, constants.SPROCSTORY, constants.SPWIKI]:
-            # subfolder = os.path.join(constants.SP_DATA_DIR, constants.SP_DIRS[self.config.name])
             data_dir = constants.SP_DATA_DIR + "/" + constants.SP_DIRS[self.config.name]
-            test_dowload = snapshot_download(
-                repo_id="OfekGlick/DiscoEval",
-                repo_type="dataset",
-                local_dir='./',
-                ignore_patterns=["*.py", "*.gitignore", "*.gitattributes", "*.DS_Store", "*.md"],
-            )
-            # train_url = hf_hub_download(
-            #     repo_id="OfekGlick/DiscoEval",
-            #     filename=constants.SP_TRAIN_NAME,
-            #     subfolder=subfolder,
-            #     repo_type="dataset",
-            #     local_dir='./',
-            # )
-            #
-            # valid_url = hf_hub_download(
-            #     repo_id="OfekGlick/DiscoEval",
-            #     filename=constants.SP_VALID_NAME,
-            #     subfolder=subfolder,
-            #     repo_type="dataset",
-            #     local_dir='./',
-            # )
-            # text_url = hf_hub_download(
-            #     repo_id="OfekGlick/DiscoEval",
-            #     filename=constants.SP_TEST_NAME,
-            #     subfolder=subfolder,
-            #     repo_type="dataset",
-            #     local_dir='./',
-            # )
-            # data_dir = dl_manager.download_and_extract(urls)
             train_name = constants.SP_TRAIN_NAME
             valid_name = constants.SP_VALID_NAME
             test_name = constants.SP_TEST_NAME
 
+        elif self.config.name in [constants.BSOARXIV, constants.BSOWIKI, constants.BSOROCSTORY]:
+            data_dir = constants.BSO_DATA_DIR + "/" + constants.BSO_DIRS[self.config.name]
+            train_name = constants.BSO_TRAIN_NAME
+            valid_name = constants.BSO_VALID_NAME
+            test_name = constants.BSO_TEST_NAME
+
         elif self.config.name in [constants.DCCHAT, constants.DCWIKI]:
-            data_dir = os.path.join(constants.DC_DATA_DIR, constants.DC_DIRS[self.config.name])
+            data_dir = constants.DC_DATA_DIR + "/" + constants.DC_DIRS[self.config.name]
             train_name = constants.DC_TRAIN_NAME
             valid_name = constants.DC_VALID_NAME
             test_name = constants.DC_TEST_NAME
@@ -244,12 +221,23 @@ class DiscoEvalSentence(datasets.GeneratorBasedBuilder):
             valid_name = constants.SSPABS_VALID_NAME
             test_name = constants.SSPABS_TEST_NAME
 
+        urls_to_download = {
+            "train": data_dir + "/" + train_name,
+            "valid": data_dir + "/" + valid_name,
+            "test": data_dir + "/" + test_name,
+        }
+        logger = logging.getLogger(__name__)
+        data_dirs = dl_manager.download_and_extract(urls_to_download)
+        logger.info(f"Data directories: {data_dirs}")
+        downloaded_files = dl_manager.download_and_extract(data_dirs)
+        logger.info(f"Downloading Completed")
+
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filepath": os.path.join(data_dir, train_name),
+                    "filepath": downloaded_files['train'],
                     "split": "train",
                 },
             ),
@@ -257,7 +245,7 @@ class DiscoEvalSentence(datasets.GeneratorBasedBuilder):
                 name=datasets.Split.VALIDATION,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filepath": os.path.join(data_dir, valid_name),
+                    "filepath": downloaded_files['valid'],
                     "split": "dev",
                 },
             ),
@@ -265,53 +253,31 @@ class DiscoEvalSentence(datasets.GeneratorBasedBuilder):
                 name=datasets.Split.TEST,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filepath": os.path.join(data_dir, test_name),
+                    "filepath": downloaded_files['test'],
                     "split": "test"
                 },
             ),
         ]
 
-
-
-
     # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
     def _generate_examples(self, filepath, split):
-        # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
-        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
         logger = logging.getLogger(__name__)
         logger.info(f"Current working dir: {os.getcwd()}")
         logger.info("generating examples from = %s", filepath)
         print(f"Current working dir: {os.getcwd()}")
         print(f"Current working dir: {os.listdir(os.getcwd())}")
 
-
-        if self.config.name in [constants.SPARXIV, constants.SPROCSTORY, constants.SPWIKI,
-                                constants.DCWIKI, constants.DCCHAT,
-                                constants.PDTB_E, constants.PDTB_I,
-                                constants.SSPABS]:
-            with io.open(filepath, mode='r', encoding='utf-8') as f:
-                for key, line in enumerate(f):
-                    line = line.strip().split("\t")
-                    example = {constants.TEXT_COLUMN_NAME[i]: sent for i, sent in enumerate(line[1:])}
-                    example[constants.LABEL_NAME] = line[0]
-                    yield key, example
-
-        elif self.config.name in [constants.RST]:
+        if self.config.name in [constants.RST]:
             data = pickle.load(open(filepath, "rb"))
             for key, line in enumerate(data):
                 example = {constants.TEXT_COLUMN_NAME[i]: sent for i, sent in enumerate(line[1:])}
                 example[constants.LABEL_NAME] = line[0]
                 yield key, example
 
-        # TODO: implement other datasets
         else:
-            yield 0, {
-                "sentence": 'example sentences',
-                "option2": 'another example sentence',
-                "second_domain_answer": "" if split == "test" else 'label',
-            }
-
-
-if __name__ == '__main__':
-    temp = os.path.join(constants.SP_DATA_DIR, constants.SP_DIRS[constants.SPARXIV])
-    ofek = 5
+            with io.open(filepath, mode='r', encoding='utf-8') as f:
+                for key, line in enumerate(f):
+                    line = line.strip().split("\t")
+                    example = {constants.TEXT_COLUMN_NAME[i]: sent for i, sent in enumerate(line[1:])}
+                    example[constants.LABEL_NAME] = line[0]
+                    yield key, example

constants.py

@@ -62,6 +62,18 @@ SP_DIRS = {SPARXIV: 'arxiv/', SPROCSTORY: 'rocstory/', SPWIKI: 'wiki/'}
 SP_LABELS = ["0", "1", "2", "3", "4"]
 SP_TEXT_COLUMNS = 5
 
+# BSO Constants:
+BSOARXIV = 'BSOarxiv'
+BSOROCSTORY = 'BSOrocstory'
+BSOWIKI = 'BSOwiki'
+BSO_TRAIN_NAME = 'train.txt'
+BSO_VALID_NAME = 'valid.txt'
+BSO_TEST_NAME = 'test.txt'
+BSO_DATA_DIR = 'data/BSO'
+BSO_DIRS = {BSOARXIV: 'arxiv/', BSOROCSTORY: 'rocstory/', BSOWIKI: 'wiki/'}
+BSO_LABELS = ["0", "1"]
+BSO_TEXT_COLUMNS = 2
+
 # DC Constants:
 DCCHAT = 'DCchat'
 DCWIKI = 'DCwiki'