| import os |
|
|
| import pyarrow as pa |
| import pyarrow.parquet as pq |
|
|
| import datasets |
|
|
| _REPO_NAME = 'Fsoft-AIC/the-vault' |
|
|
| _LANG_TO_EXTENSION = { |
| "Python": [".py"], |
| "C": [".c", ".h"], |
| "C#": [".cs"], |
| "C++": [".cpp", ".hpp", ".c++", ".h++", ".cc", ".hh", ".C", ".H"], |
| "Go": [".go"], |
| "Java": [".java"], |
| "JavaScript": [".js"], |
| "PHP": [".php", ".php3", ".php4", ".php5", ".phps", ".phpt"], |
| "Ruby": [".rb"], |
| "Rust": [".rs"], |
| } |
|
|
|
|
| _DESCRIPTION = """The Vault""" |
|
|
| _HOMEPAGE = "https://huggingface.co/Fsoft-AIC" |
|
|
|
|
| _EXTENSION_TO_LANG = {} |
| for lang in _LANG_TO_EXTENSION: |
| for extension in _LANG_TO_EXTENSION[lang]: |
| _EXTENSION_TO_LANG[extension] = lang |
|
|
|
|
| |
| _LANG_CONFIGS = ["all"] + list(_LANG_TO_EXTENSION.keys()) |
| |
| class TheVaultConfig(datasets.BuilderConfig): |
| """BuilderConfig for The Vault dataset.""" |
|
|
| def __init__(self, *args, languages=["all"], split= "all", **kwargs): |
| """BuilderConfig for the GitHub Code dataset. |
| Args: |
| languages (:obj:`List[str]`): List of languages to load. |
| **kwargs: keyword arguments forwarded to super. |
| """ |
| super().__init__( |
| *args, |
| name=split + "_" + "+".join(languages), |
| **kwargs, |
| ) |
| |
| languages = set(languages) |
| |
| assert all([language in _LANG_CONFIGS for language in languages]), f"Language not in {_LANG_CONFIGS}." |
| if split != "all": |
| assert split in num_shard_split, "Split not in {}.".format(list(num_shard_split.keys())) |
| |
| if "all" in languages: |
| assert len(languages)==1, f"Passed 'all' together with other languages. {languages}" |
| self.filter_languages = False |
| else: |
| self.filter_languages = True |
| |
| self.languages = set(languages) |
| self.split= split |
|
|
|
|
| num_shard_split = { |
| 'small': 2, |
| 'medium': 4 |
| } |
| splits = ["all"] + list(num_shard_split.keys()) |
|
|
| class TheVault(datasets.GeneratorBasedBuilder): |
| """The Vault dataset.""" |
|
|
| VERSION = datasets.Version("1.0.0") |
| |
| BUILDER_CONFIG_CLASS = TheVaultConfig |
| BUILDER_CONFIGS = [TheVaultConfig(languages=[lang], split=spl) for lang in _LANG_CONFIGS for spl in splits] |
| DEFAULT_CONFIG_NAME = "all-all" |
|
|
| |
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features({"original_string": datasets.Value("string"), |
| "original_docstring": datasets.Value("string"), |
| "code": datasets.Value("string"), |
| "docstring": datasets.Value("string"), |
| "code_tokens": datasets.Value("string"), |
| "docstring_tokens": datasets.Value("string"), |
| "short_docstring": datasets.Value("string"), |
| "comment": datasets.Value("string"), |
| "return_type": datasets.Value("string"), |
| "identifier": datasets.Value("string"), |
| "repo": datasets.Value("string"), |
| "path": datasets.Value("string"), |
| "language": datasets.Value("string"), |
| }), |
| supervised_keys=None, |
| homepage=_HOMEPAGE, |
| license="Multiple: see the 'license' field of each sample.", |
| |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| print(self.config.split) |
| if self.config.split == "all": |
| generators = [] |
| for split in num_shard_split: |
| num_shards = num_shard_split[split] |
| data_files = [ |
| f"data/{split}-{_index:05d}-of-{num_shards:05d}.parquet" |
| for _index in range(num_shards) |
| ] |
| files = dl_manager.download(data_files) |
| generators.append( |
| datasets.SplitGenerator( |
| name=split, |
| gen_kwargs={ |
| "files": files, |
| }, |
| ), |
| ) |
| return generators |
|
|
| else: |
| num_shards = num_shard_split[self.config.split] |
| data_files = [ |
| f"data/{self.config.split}-{_index:05d}-of-{num_shards:05d}.parquet" |
| for _index in range(num_shards) |
| ] |
| files = dl_manager.download(data_files) |
| return [ |
| datasets.SplitGenerator( |
| name=self.config.split, |
| gen_kwargs={ |
| "files": files, |
| }, |
| ), |
| ] |
|
|
| def _generate_examples(self, files): |
| key = 0 |
| for file_idx, file in enumerate(files): |
| with open(file, "rb") as f: |
| parquet_file = pq.ParquetFile(f) |
| for batch_idx, record_batch in enumerate(parquet_file.iter_batches(batch_size=10_000)): |
| pa_table = pa.Table.from_batches([record_batch]) |
| for row_index in range(pa_table.num_rows): |
| row = pa_table.slice(row_index, 1).to_pydict() |
| |
| lang = row['language'][0] |
| |
| if self.config.filter_languages and not lang in self.config.languages: |
| continue |
| |
| yield key, { |
| "original_string": datasets.Value("string"), |
| "original_docstring": datasets.Value("string"), |
| "code": datasets.Value("string"), |
| "docstring": datasets.Value("string"), |
| "code_tokens": datasets.Value("string"), |
| "docstring_tokens": datasets.Value("string"), |
| "short_docstring": datasets.Value("string"), |
| "comment": datasets.Value("string"), |
| "return_type": datasets.Value("string"), |
| "identifier": datasets.Value("string"), |
| "repo": datasets.Value("string"), |
| "path": datasets.Value("string"), |
| "language": datasets.Value("string"), |
| } |
| key += 1 |
|
|
| |
| def lang_from_name(name): |
| for extension in _EXTENSION_TO_LANG: |
| if name.endswith(extension): |
| return _EXTENSION_TO_LANG[extension] |