Update parquet files

.gitattributes

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-*.7z filter=lfs diff=lfs merge=lfs -text
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data.jsonl → default/pytorrent-standalone-train.parquet

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 version https://git-lfs.github.com/spec/v1
-oid sha256:1ff5aac58f49e2d31b4dd2fcd887133c4390e3c96b39da411cf9278ee218b831
-size 79818924
+oid sha256:a67d2dbc5e1233901d0018af43fc87eb9899dfc8c4b10bba341e6a9eff7f526d
+size 35597741

pytorrent-standalone.py

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-# coding=utf-8
-# 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.
-"""Wrapper for datasets in CodeXGLUE benchmark."""
-import csv
-import json
-import os
-import datasets
-
-_CITATION = """\
-@article{Bahrami2021,
-author = {Bahrami, Mehdi and Shrikanth, N. C. and Ruangwan, Shade and Liu, Lei and Mizobuchi, Yuji and Fukuyori, Masahiro and Chen, Wei-Peng and Munakata, Kazuki and Menzies, Tim},
-year = {2021},
-journal = {arXiv},
-title = {PyTorrent: A Python Library Corpus for Large-scale Language Models}
-}
-"""
-
-_DESCRIPTION = """\
-pytorrent-standalone is a subset of the PyTorrent dataset, where only functions that does not depend on external libraries
-are kept.
-"""
-
-_HOMEPAGE = ""
-
-_LICENSE = ""
-
-# The HuggingFace dataset library don't host the datasets but only point to the original files
-# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_URLs = {
-    'default': "data.jsonl",
-}
-
-
-# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
-class PyTorrentStandalone(datasets.GeneratorBasedBuilder):
-    """TODO: Short description of my dataset."""
-    VERSION = datasets.Version("1.0.0")
-    # This is an example of a dataset with multiple configurations.
-    # If you don't want/need to define several sub-sets in your dataset,
-    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
-    # If you need to make complex sub-parts in the datasets with configurable options
-    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
-    # BUILDER_CONFIG_CLASS = MyBuilderConfig
-    # You will be able to load one or the other configurations in the following list with
-    # data = datasets.load_dataset('my_dataset', 'first_domain')
-    # data = datasets.load_dataset('my_dataset', 'second_domain')
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="default", version=VERSION,
-                               description="The corpus."),
-    ]
-
-    DEFAULT_CONFIG_NAME = "default"  # It's not mandatory to have a default configuration. Just use one if it make sense.
-
-    def _info(self):
-        if self.config.name == "default":  # This is the name of the configuration selected in BUILDER_CONFIGS above
-            features = datasets.Features(
-                {
-                    "repo": datasets.Value("string"),
-                    "path": datasets.Value("string"),
-                    "code": datasets.Value("string"),
-                }
-            )
-        else:
-            assert False, f'Invalid config name: {self.config.name}'
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # This defines the different columns of the dataset and their types
-            features=features,  # Here we define them above because they are different between the two configurations
-            # If there's a common (input, target) tuple from the features,
-            # specify them here. They'll be used if as_supervised=True in
-            # builder.as_dataset.
-            supervised_keys=None,
-            # Homepage of the dataset for documentation
-            homepage=_HOMEPAGE,
-            # License for the dataset if available
-            license=_LICENSE,
-            # Citation for the dataset
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # If several configurations are possible (listed in BUILDER_CONFIGS),
-        # the configuration selected by the user is in self.config.name
-        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs
-        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with
-        # path to local files. By default the archives will be extracted and a path to a cached folder where they are
-        # extracted is returned instead of the archive
-        my_urls = _URLs[self.config.name]
-        data_path = dl_manager.download_and_extract(my_urls)
-        if self.config.name == 'default':
-            return [
-                datasets.SplitGenerator(
-                    name=datasets.Split.TRAIN,
-                    # These kwargs will be passed to _generate_examples
-                    gen_kwargs={
-                        'data_path': data_path
-                    }
-                ),
-            ]
-
-    def _generate_examples(
-            self, data_path
-    ):
-        """ Yields examples as (key, example) tuples. """
-        # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
-        # The `key` is here for legacy reason (tfds) and is not important in itself.
-        with open(data_path) as jsonl_file:
-            idx = 0
-            for jsonl in jsonl_file:
-                sample = json.loads(jsonl)
-                result = {
-                    'repo': sample['repo'],
-                    'path': sample['path'],
-                    'code': sample['original_string']
-                }
-                yield idx, result
-                idx += 1