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import os |
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import sys |
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import csv |
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import datasets |
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csv.field_size_limit(sys.maxsize) |
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_DESCRIPTION = "Java 8M Methods :: A collection 8 million java methods" |
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_CITATION = "NOT AVAILABLE" |
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_HOMEPAGE = "NOT AVAILABLE" |
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_LICENSE = "MIT" |
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_BASE_TRAIN_FILE_URL = "https://huggingface.co/datasets/anjandash/java-8m-methods-v1/resolve/main/train.csv" |
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_BASE_VALID_FILE_URL = "https://huggingface.co/datasets/anjandash/java-8m-methods-v1/resolve/main/valid.csv" |
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_BASE_TEST_FILE_URL = "https://huggingface.co/datasets/anjandash/java-8m-methods-v1/resolve/main/test.csv" |
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_URLS = { |
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"train": _BASE_TRAIN_FILE_URL, |
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"valid": _BASE_VALID_FILE_URL, |
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"test": _BASE_TEST_FILE_URL |
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} |
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class Java8mMethodsV1(datasets.GeneratorBasedBuilder): |
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"""Java 8M Methods""" |
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def _info(self): |
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"""Returns Info""" |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"id": datasets.Value("string"), |
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"text": datasets.Value("string"), |
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} |
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), |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators""" |
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data_file = dl_manager.download(_URLS) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_file["train"]}), |
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": data_file["valid"]}), |
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_file["test"] }), |
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] |
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def _generate_examples(self, filepath): |
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"""Yields Examples""" |
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with open(filepath, encoding="utf-8") as f: |
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reader = csv.reader(f) |
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for id_, row in enumerate(reader): |
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if id_ == 0: |
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continue |
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yield id_, { |
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"id": row[0], |
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"text": row[1], |
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} |
