updated loader.

xscitldr_staging.py

@@ -123,7 +123,7 @@ class XSciTLDRStaging(datasets.GeneratorBasedBuilder):
                 name=datasets.Split.TRAIN,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filedir": data_path_train,
+                    "filepath": data_path_train,
                     "split": "train",
                 },
             ),
@@ -131,7 +131,7 @@ class XSciTLDRStaging(datasets.GeneratorBasedBuilder):
                 name=datasets.Split.TEST,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filedir": data_path_test,
+                    "filepath": data_path_test,
                     "split": "test"
                 },
             ),
@@ -139,17 +139,17 @@ class XSciTLDRStaging(datasets.GeneratorBasedBuilder):
                 name=datasets.Split.VALIDATION,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filedir": data_path_dev,
+                    "filepath": data_path_dev,
                     "split": "dev",
                 },
             ),
         ]
 
     # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def _generate_examples(self, filedir, split):
+    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.
-        with open(os.path.join(filedir, f"{split}.jsonl"), encoding="utf-8") as f:
+        with open(filepath, encoding="utf-8") as f:
             for key, row in enumerate(f):
                 data = json.loads(row)
                 yield key, {