| 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()) | |
| num_shard_split = { | |
| 'train/small': 2, | |
| 'train/medium': 4 | |
| } | |
| _SPLIT_CONFIGS = ["all"] + list(num_shard_split.keys()) | |
| class TheVaultFunctionConfig(datasets.BuilderConfig): | |
| """BuilderConfig for The Vault dataset.""" | |
| def __init__(self, *args, languages=["all"], split_set= ["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= "+".join([split.replace("/", "_") for split in split_set]) + "-" + "+".join(languages), | |
| **kwargs, | |
| ) | |
| languages = set(languages) | |
| split_set = set(split_set) | |
| assert all([language in _LANG_CONFIGS for language in languages]), f"languages {languages} contains language not in {_LANG_CONFIGS}." | |
| assert all([split in _SPLIT_CONFIGS for split in split_set]), "split_set {} contains element not in {}.".format(split_set, _SPLIT_CONFIGS) | |
| if "all" in split_set: | |
| assert len(split_set)==1, f"Passed 'all' together with other split sets. {split_set}" | |
| 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_set= split_set | |
| class TheVaultFunction(datasets.GeneratorBasedBuilder): | |
| """The Vault dataset.""" | |
| VERSION = datasets.Version("1.0.0") | |
| BUILDER_CONFIG_CLASS = TheVaultFunctionConfig | |
| BUILDER_CONFIGS = [TheVaultFunctionConfig(languages=[lang], split_set=[spl]) for lang in _LANG_CONFIGS for spl in _SPLIT_CONFIGS] | |
| 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_set) | |
| generators = [] | |
| split_set = self.config.split_set | |
| if "all" in split_set: | |
| split_set = list(num_shard_split.keys()) | |
| for split in split_set: | |
| 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.replace("/", "_"), | |
| gen_kwargs={ | |
| "files": files, | |
| }, | |
| ), | |
| ) | |
| return generators | |
| 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] |