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wikitext_103.py

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+import datasets
+import os
+import json
+
+
+_CITATION = ""
+_DESCRIPTION = """
+    Wikitext-103 dataset from this paper:
+    https://arxiv.org/pdf/1609.07843.pdf
+
+    Gopher's authors concatenate all the articles, set context length to n/2 (n = max_seq_len),
+    and use the "closed vocabulary" variant of the dataset for evaluation.
+
+    In contrast, we evaluate the model on each article independently, use single token contexts
+    (except for the last sequence in each document), and use the raw dataset.
+"""
+
+class Wikitext103(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "text": datasets.Value("string"),
+
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage="",
+            license="",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        test_json = dl_manager.download(os.path.join("data", "test.jsonl"))
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"path": test_json},
+            )
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, path):
+        with open(path, encoding="utf-8") as f:
+            for key, row in enumerate(f):
+                yield key, json.loads(row)