Create sacrebleu_manual.py

sacrebleu_manual.py

@@ -0,0 +1,69 @@
+"""
+NOTE: This file implements translation tasks using datasets from WMT conferences,
+provided by sacrebleu. Traditionally they are evaluated with BLEU scores. TER
+and CHRF are other options.
+
+We defer citations and descriptions of the many translations tasks used
+here to the SacreBLEU repo from which we've obtained the datasets:
+https://github.com/mjpost/sacrebleu/blob/master/sacrebleu/dataset.py
+
+Homepage: https://github.com/mjpost/sacrebleu/blob/master/sacrebleu/dataset.py
+"""
+import pycountry
+from sacrebleu import sacrebleu
+import datasets
+
+
+_CITATION = """
+@inproceedings{post-2018-call,
+    title = "A Call for Clarity in Reporting {BLEU} Scores",
+    author = "Post, Matt",
+    booktitle = "Proceedings of the Third Conference on Machine Translation: Research Papers",
+    month = oct,
+    year = "2018",
+    address = "Belgium, Brussels",
+    publisher = "Association for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/W18-6319",
+    pages = "186--191",
+}
+"""
+
+
+class Sacrebleu(datasets.GeneratorBasedBuilder):
+    """The Pile is a 825 GiB diverse, open source language modeling dataset."""
+
+    VERSION = datasets.Version("0.0.1")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name=f"{name}/{langpair}", version=VERSION, description="")
+            for langpair in sacrebleu.get_langpairs_for_testset(name)
+            for name in sacrebleu.get_available_testsets()
+        ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "translation": datasets.Value("dict"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=f"{_DESCRIPTION}\n{self.config.description}",
+            features=features,
+            homepage="",
+            license="",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={path: f"{self.config.name}.jsonl"},
+            )
+        ]
+
+    # 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)