init commit

cpt.py

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+# 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.
+import json
+import os
+
+import datasets
+import pandas as pd
+from datasets import DatasetInfo, DownloadManager
+
+#
+_CITATION = """\
+"""
+
+_DESCRIPTION = """\
+"""
+
+
+_LICENSE = ""
+
+_URL = r"https://huggingface.co/datasets/hkust-nlp/cpt/resolve/main/data.zip"
+
+
+Task_list = [
+    "python",
+    "cc",
+    "arxiv_math",
+]
+
+
+class CptConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super().__init__(version=datasets.Version("1.0.0"), **kwargs)
+
+
+class Cpt(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        CptConfig(
+            name=task_name,
+        )
+        for task_name in Task_list
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "content": datasets.Value("string"),
+                "subset": datasets.Value("string"),
+                "meta": datasets.features.Value("string"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            license=_LICENSE,
+        )
+
+    def _split_generators(self, dl_manager: DownloadManager):
+        data_dir = dl_manager.download_and_extract(_URL)
+        task_name = self.config.name
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TEST,
+                                    gen_kwargs={"filepath": os.path.join(data_dir, f"{task_name}.jsonl")})
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        with open(filepath,encoding="utf-8") as f:
+            for id_, row in enumerate(f):
+                cur_data = json.loads(row)
+                yield id_, {
+                    "content": cur_data["content"],
+                    "subset": cur_data["subset"],
+                    "meta": str(cur_data["meta"]),
+                }

data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:24adcf8f9823b91edadb75f233b2e269fb026463afc44ecd5087bef025c0cb33
+size 96958877