Update loading script

medal.py

@@ -18,13 +18,11 @@
 
 
 import csv
+import os.path
 
 import datasets
 
 
-logger = datasets.logging.get_logger(__name__)
-
-
 _CITATION = """\
 @inproceedings{wen-etal-2020-medal,
     title = "{M}e{DAL}: Medical Abbreviation Disambiguation Dataset for Natural Language Understanding Pretraining",
@@ -45,12 +43,15 @@ _DESCRIPTION = """\
 A large medical text dataset (14Go) curated to 4Go for abbreviation disambiguation, designed for natural language understanding pre-training in the medical domain. For example, DHF can be disambiguated to dihydrofolate, diastolic heart failure, dengue hemorragic fever or dihydroxyfumarate
 """
 
-_URL = "https://zenodo.org/record/4482922/files/"
 _URLS = {
-    "train": _URL + "train.csv",
-    "test": _URL + "test.csv",
-    "valid": _URL + "valid.csv",
-    "full": _URL + "full_data.csv",
+    "pretrain": "data/pretrain_subset.zip",
+    "full": "data/full_data.csv.zip"
+}
+_FILENAMES = {
+    "train": "train.csv",
+    "test": "test.csv",
+    "valid": "valid.csv",
+    "full": "full_data.csv",
 }
 
 
@@ -86,35 +87,28 @@ class Medal(datasets.GeneratorBasedBuilder):
         """Returns SplitGenerators."""
         # dl_manager is a datasets.download.DownloadManager that can be used to
         # download and extract URLs
-        urls_to_dl = _URLS
-        try:
-            dl_dir = dl_manager.download_and_extract(urls_to_dl)
-        except Exception:
-            logger.warning(
-                "This dataset is downloaded through Zenodo which is flaky. If this download failed try a few times before reporting an issue"
-            )
-            raise
+        dl_dir = dl_manager.download_and_extract(_URLS)
 
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": dl_dir["train"], "split": "train"},
+                gen_kwargs={"filepath": os.path.join(dl_dir["pretrain"], _FILENAMES["train"]), "split": "train"},
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": dl_dir["test"], "split": "test"},
+                gen_kwargs={"filepath": os.path.join(dl_dir["pretrain"], _FILENAMES["test"]), "split": "test"},
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
                 # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": dl_dir["valid"], "split": "val"},
+                gen_kwargs={"filepath": os.path.join(dl_dir["pretrain"], _FILENAMES["valid"]), "split": "val"},
             ),
             datasets.SplitGenerator(
                 name="full",
                 # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": dl_dir["full"], "split": "full"},
+                gen_kwargs={"filepath": os.path.join(dl_dir["full"], _FILENAMES["full"]), "split": "full"},
             ),
         ]