Add dataset loading script

olympiads-ref.py

@@ -0,0 +1,103 @@
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""AI-MO Olympiad Reference Dataset"""
+
+
+
+import re
+import json
+from pathlib import Path
+
+import datasets
+from huggingface_hub import HfApi
+
+
+# TODO: Add BibTeX citation
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = """"""
+
+# TODO: Add description of the dataset here
+# You can copy an official description
+_DESCRIPTION = """"""
+
+# TODO: Add a link to an official homepage for the dataset here
+_HOMEPAGE = ""
+
+# TODO: Add the licence for the dataset here if you can find it
+_LICENSE = ""
+
+
+class OlympiadReferenceDataset(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("0.0.1")
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self._hfapi = HfApi()
+        self.pattern = re.compile(r'.*/segmented/[^/]+\.jsonl$')
+
+    def _info(self):
+        features = datasets.Features(
+            {   
+                "problem_type": datasets.Value("string"),
+                "problem_label": datasets.Value("string"),
+                "problem": datasets.Value("string"),
+                "solution": datasets.Value("string"),
+                "year": datasets.Value("int32"),
+                "tier": datasets.Value("int32")
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        data_root_path = Path(dl_manager._base_path)
+
+        repo_files = self._hfapi.list_repo_files(repo_id="AI-MO/olympiads-ref", repo_type="dataset")
+        seg_jsonl_files = [s for s in repo_files if self.pattern.match(s)]
+
+        data_urls = [data_root_path / sjf for sjf in seg_jsonl_files]
+        data_files = dl_manager.download_and_extract(data_urls)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "jsonl_files": data_files,
+                    "split": "train",
+                },
+            )
+        ]
+
+    def _generate_examples(self, jsonl_files, split):
+        key = 0
+
+        for file in jsonl_files:
+            with open(file, "r", encoding="utf-8") as f:
+                for line in f:
+                    data = json.loads(line)
+                    yield key, {
+                        "problem_type": data.get("problem_type"),
+                        "problem_label": data.get("problem_label") or data.get("label"),
+                        "problem": data.get("problem"),
+                        "solution": data.get("solution"),
+                        "year": data.get("year"),
+                        "tier": data.get("tier"),
+                    }
+                    key += 1