Datasets:
Tasks:
Text Classification
Formats:
parquet
Sub-tasks:
semantic-similarity-classification
Languages:
code
Size:
1M - 10M
License:
Commit
•
35e27b7
1
Parent(s):
55824d8
Delete loading script auxiliary file
Browse files
common.py
DELETED
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from typing import List
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import datasets
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# Citation, taken from https://github.com/microsoft/CodeXGLUE
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_DEFAULT_CITATION = """@article{CodeXGLUE,
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title={CodeXGLUE: A Benchmark Dataset and Open Challenge for Code Intelligence},
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year={2020},}"""
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class Child:
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_DESCRIPTION = None
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_FEATURES = None
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_CITATION = None
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SPLITS = {"train": datasets.Split.TRAIN}
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_SUPERVISED_KEYS = None
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def __init__(self, info):
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self.info = info
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def homepage(self):
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return self.info["project_url"]
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def _info(self):
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# This is the description that will appear on the datasets page.
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return datasets.DatasetInfo(
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description=self.info["description"] + "\n\n" + self._DESCRIPTION,
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features=datasets.Features(self._FEATURES),
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homepage=self.homepage(),
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citation=self._CITATION or _DEFAULT_CITATION,
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supervised_keys=self._SUPERVISED_KEYS,
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)
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def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
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SPLITS = self.SPLITS
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_URL = self.info["raw_url"]
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urls_to_download = {}
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for split in SPLITS:
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if split not in urls_to_download:
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urls_to_download[split] = {}
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for key, url in self.generate_urls(split):
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if not url.startswith("http"):
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url = _URL + "/" + url
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urls_to_download[split][key] = url
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downloaded_files = {}
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for k, v in urls_to_download.items():
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downloaded_files[k] = dl_manager.download_and_extract(v)
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return [
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datasets.SplitGenerator(
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name=SPLITS[k],
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gen_kwargs={"split_name": k, "file_paths": downloaded_files[k]},
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)
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for k in SPLITS
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]
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def check_empty(self, entries):
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all_empty = all([v == "" for v in entries.values()])
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all_non_empty = all([v != "" for v in entries.values()])
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if not all_non_empty and not all_empty:
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raise RuntimeError("Parallel data files should have the same number of lines.")
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return all_empty
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class TrainValidTestChild(Child):
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SPLITS = {
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"train": datasets.Split.TRAIN,
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"valid": datasets.Split.VALIDATION,
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"test": datasets.Split.TEST,
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}
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